Architecture
An overview of the architecture for OpenShift Container Platform
Abstract
Chapter 1. Architecture overview
OpenShift Container Platform is a cloud-based Kubernetes container platform. The foundation of OpenShift Container Platform is based on Kubernetes and therefore shares the same technology. To learn more about OpenShift Container Platform and Kubernetes, see product architecture.
1.1. Glossary of common terms for OpenShift Container Platform architecture
This glossary defines common terms that are used in the architecture content.
- access policies
- A set of roles that dictate how users, applications, and entities within a cluster interacts with one another. An access policy increases cluster security.
- admission plugins
- Admission plugins enforce security policies, resource limitations, or configuration requirements.
- authentication
- To control access to an OpenShift Container Platform cluster, a cluster administrator can configure user authentication and ensure only approved users access the cluster. To interact with an OpenShift Container Platform cluster, you must authenticate to the OpenShift Container Platform API. You can authenticate by providing an OAuth access token or an X.509 client certificate in your requests to the OpenShift Container Platform API.
- bootstrap
- A temporary machine that runs minimal Kubernetes and deploys the OpenShift Container Platform control plane.
- certificate signing requests (CSRs)
- A resource requests a denoted signer to sign a certificate. This request might get approved or denied.
- Cluster Version Operator (CVO)
- An Operator that checks with the OpenShift Container Platform Update Service to see the valid updates and update paths based on current component versions and information in the graph.
- compute nodes
- Nodes that are responsible for executing workloads for cluster users. Compute nodes are also known as worker nodes.
- configuration drift
- A situation where the configuration on a node does not match what the machine config specifies.
- containers
- Lightweight and executable images that consist software and all its dependencies. Because containers virtualize the operating system, you can run containers anywhere, from a data center to a public or private cloud to your local host.
- container orchestration engine
- Software that automates the deployment, management, scaling, and networking of containers.
- container workloads
- Applications that are packaged and deployed in containers.
- control groups (cgroups)
- Partitions sets of processes into groups to manage and limit the resources processes consume.
- control plane
- A container orchestration layer that exposes the API and interfaces to define, deploy, and manage the life cycle of containers. Control planes are also known as control plane machines.
- CRI-O
- A Kubernetes native container runtime implementation that integrates with the operating system to deliver an efficient Kubernetes experience.
- deployment
- A Kubernetes resource object that maintains the life cycle of an application.
- Dockerfile
- A text file that contains the user commands to perform on a terminal to assemble the image.
- hosted control planes
A OpenShift Container Platform feature that enables hosting a control plane on the OpenShift Container Platform cluster from its data plane and workers. This model performs following actions:
- Optimize infrastructure costs required for the control planes.
- Improve the cluster creation time.
- Enable hosting the control plane using the Kubernetes native high level primitives. For example, deployments, stateful sets.
- Allow a strong network segmentation between the control plane and workloads.
- hybrid cloud deployments
- Deployments that deliver a consistent platform across bare metal, virtual, private, and public cloud environments. This offers speed, agility, and portability.
- Ignition
- A utility that RHCOS uses to manipulate disks during initial configuration. It completes common disk tasks, including partitioning disks, formatting partitions, writing files, and configuring users.
- installer-provisioned infrastructure
- The installation program deploys and configures the infrastructure that the cluster runs on.
- kubelet
- A primary node agent that runs on each node in the cluster to ensure that containers are running in a pod.
- kubernetes manifest
- Specifications of a Kubernetes API object in a JSON or YAML format. A configuration file can include deployments, config maps, secrets, daemon sets.
- Machine Config Daemon (MCD)
- A daemon that regularly checks the nodes for configuration drift.
- Machine Config Operator (MCO)
- An Operator that applies the new configuration to your cluster machines.
- machine config pools (MCP)
- A group of machines, such as control plane components or user workloads, that are based on the resources that they handle.
- metadata
- Additional information about cluster deployment artifacts.
- microservices
- An approach to writing software. Applications can be separated into the smallest components, independent from each other by using microservices.
- mirror registry
- A registry that holds the mirror of OpenShift Container Platform images.
- monolithic applications
- Applications that are self-contained, built, and packaged as a single piece.
- namespaces
- A namespace isolates specific system resources that are visible to all processes. Inside a namespace, only processes that are members of that namespace can see those resources.
- networking
- Network information of OpenShift Container Platform cluster.
- node
- A worker machine in the OpenShift Container Platform cluster. A node is either a virtual machine (VM) or a physical machine.
- OpenShift Container Platform Update Service (OSUS)
- For clusters with internet access, Red Hat Enterprise Linux (RHEL) provides over-the-air updates by using an OpenShift Container Platform update service as a hosted service located behind public APIs.
- OpenShift CLI (
oc
) - A command line tool to run OpenShift Container Platform commands on the terminal.
- OpenShift Dedicated
- A managed RHEL OpenShift Container Platform offering on Amazon Web Services (AWS) and Google Cloud Platform (GCP). OpenShift Dedicated focuses on building and scaling applications.
- OpenShift image registry
- A registry provided by OpenShift Container Platform to manage images.
- Operator
- The preferred method of packaging, deploying, and managing a Kubernetes application in an OpenShift Container Platform cluster. An Operator takes human operational knowledge and encodes it into software that is packaged and shared with customers.
- OperatorHub
- A platform that contains various OpenShift Container Platform Operators to install.
- Operator Lifecycle Manager (OLM)
- OLM helps you to install, update, and manage the lifecycle of Kubernetes native applications. OLM is an open source toolkit designed to manage Operators in an effective, automated, and scalable way.
- OSTree
- An upgrade system for Linux-based operating systems that performs atomic upgrades of complete file system trees. OSTree tracks meaningful changes to the file system tree using an addressable object store, and is designed to complement existing package management systems.
- over-the-air (OTA) updates
- The OpenShift Container Platform Update Service (OSUS) provides over-the-air updates to OpenShift Container Platform, including Red Hat Enterprise Linux CoreOS (RHCOS).
- pod
- One or more containers with shared resources, such as volume and IP addresses, running in your OpenShift Container Platform cluster. A pod is the smallest compute unit defined, deployed, and managed.
- private registry
- OpenShift Container Platform can use any server implementing the container image registry API as a source of the image which allows the developers to push and pull their private container images.
- public registry
- OpenShift Container Platform can use any server implementing the container image registry API as a source of the image which allows the developers to push and pull their public container images.
- RHEL OpenShift Container Platform Cluster Manager
- A managed service where you can install, modify, operate, and upgrade your OpenShift Container Platform clusters.
- RHEL Quay Container Registry
- A Quay.io container registry that serves most of the container images and Operators to OpenShift Container Platform clusters.
- replication controllers
- An asset that indicates how many pod replicas are required to run at a time.
- role-based access control (RBAC)
- A key security control to ensure that cluster users and workloads have only access to resources required to execute their roles.
- route
- Routes expose a service to allow for network access to pods from users and applications outside the OpenShift Container Platform instance.
- scaling
- The increasing or decreasing of resource capacity.
- service
- A service exposes a running application on a set of pods.
- Source-to-Image (S2I) image
- An image created based on the programming language of the application source code in OpenShift Container Platform to deploy applications.
- storage
- OpenShift Container Platform supports many types of storage, both for on-premise and cloud providers. You can manage container storage for persistent and non-persistent data in an OpenShift Container Platform cluster.
- Telemetry
- A component to collect information such as size, health, and status of OpenShift Container Platform.
- template
- A template describes a set of objects that can be parameterized and processed to produce a list of objects for creation by OpenShift Container Platform.
- user-provisioned infrastructure
- You can install OpenShift Container Platform on the infrastructure that you provide. You can use the installation program to generate the assets required to provision the cluster infrastructure, create the cluster infrastructure, and then deploy the cluster to the infrastructure that you provided.
- web console
- A user interface (UI) to manage OpenShift Container Platform.
- worker node
- Nodes that are responsible for executing workloads for cluster users. Worker nodes are also known as compute nodes.
Additional resources
- For more information on networking, see OpenShift Container Platform networking.
- For more information on storage, see OpenShift Container Platform storage.
- For more information on authentication, see OpenShift Container Platform authentication.
- For more information on Operator Lifecycle Manager (OLM), see OLM.
- For more information on logging, see About Logging.
- For more information on over-the-air (OTA) updates, see Introduction to OpenShift updates.
1.2. About installation and updates
As a cluster administrator, you can use the OpenShift Container Platform installation program to install and deploy a cluster by using one of the following methods:
- Installer-provisioned infrastructure
- User-provisioned infrastructure
1.3. About the control plane
The control plane manages the worker nodes and the pods in your cluster. You can configure nodes with the use of machine config pools (MCPs). MCPs are groups of machines, such as control plane components or user workloads, that are based on the resources that they handle. OpenShift Container Platform assigns different roles to hosts. These roles define the function of a machine in a cluster. The cluster contains definitions for the standard control plane and worker role types.
You can use Operators to package, deploy, and manage services on the control plane. Operators are important components in OpenShift Container Platform because they provide the following services:
- Perform health checks
- Provide ways to watch applications
- Manage over-the-air updates
- Ensure applications stay in the specified state
1.4. About containerized applications for developers
As a developer, you can use different tools, methods, and formats to develop your containerized application based on your unique requirements, for example:
- Use various build-tool, base-image, and registry options to build a simple container application.
- Use supporting components such as OperatorHub and templates to develop your application.
- Package and deploy your application as an Operator.
You can also create a Kubernetes manifest and store it in a Git repository. Kubernetes works on basic units called pods. A pod is a single instance of a running process in your cluster. Pods can contain one or more containers. You can create a service by grouping a set of pods and their access policies. Services provide permanent internal IP addresses and host names for other applications to use as pods are created and destroyed. Kubernetes defines workloads based on the type of your application.
1.5. About Red Hat Enterprise Linux CoreOS (RHCOS) and Ignition
As a cluster administrator, you can perform the following Red Hat Enterprise Linux CoreOS (RHCOS) tasks:
- Learn about the next generation of single-purpose container operating system technology.
- Choose how to configure Red Hat Enterprise Linux CoreOS (RHCOS)
Choose how to deploy Red Hat Enterprise Linux CoreOS (RHCOS):
- Installer-provisioned deployment
- User-provisioned deployment
The OpenShift Container Platform installation program creates the Ignition configuration files that you need to deploy your cluster. Red Hat Enterprise Linux CoreOS (RHCOS) uses Ignition during the initial configuration to perform common disk tasks, such as partitioning, formatting, writing files, and configuring users. During the first boot, Ignition reads its configuration from the installation media or the location that you specify and applies the configuration to the machines.
You can learn how Ignition works, the process for a Red Hat Enterprise Linux CoreOS (RHCOS) machine in an OpenShift Container Platform cluster, view Ignition configuration files, and change Ignition configuration after an installation.
1.6. About admission plugins
You can use admission plugins to regulate how OpenShift Container Platform functions. After a resource request is authenticated and authorized, admission plugins intercept the resource request to the master API to validate resource requests and to ensure that scaling policies are adhered to. Admission plugins are used to enforce security policies, resource limitations, or configuration requirements.
Chapter 2. OpenShift Container Platform architecture
2.1. Introduction to OpenShift Container Platform
OpenShift Container Platform is a platform for developing and running containerized applications. It is designed to allow applications and the data centers that support them to expand from just a few machines and applications to thousands of machines that serve millions of clients.
With its foundation in Kubernetes, OpenShift Container Platform incorporates the same technology that serves as the engine for massive telecommunications, streaming video, gaming, banking, and other applications. Its implementation in open Red Hat technologies lets you extend your containerized applications beyond a single cloud to on-premise and multi-cloud environments.
![Red Hat OpenShift Kubernetes Engine](https://access.redhat.com/webassets/avalon/d/OpenShift_Container_Platform-4.14-Architecture-en-US/images/9fe72426e6a05242626a8a5c7bb976fc/ocp_arch.png)
2.1.1. About Kubernetes
Although container images and the containers that run from them are the primary building blocks for modern application development, to run them at scale requires a reliable and flexible distribution system. Kubernetes is the defacto standard for orchestrating containers.
Kubernetes is an open source container orchestration engine for automating deployment, scaling, and management of containerized applications. The general concept of Kubernetes is fairly simple:
- Start with one or more worker nodes to run the container workloads.
- Manage the deployment of those workloads from one or more control plane nodes.
- Wrap containers in a deployment unit called a pod. Using pods provides extra metadata with the container and offers the ability to group several containers in a single deployment entity.
- Create special kinds of assets. For example, services are represented by a set of pods and a policy that defines how they are accessed. This policy allows containers to connect to the services that they need even if they do not have the specific IP addresses for the services. Replication controllers are another special asset that indicates how many pod replicas are required to run at a time. You can use this capability to automatically scale your application to adapt to its current demand.
In only a few years, Kubernetes has seen massive cloud and on-premise adoption. The open source development model allows many people to extend Kubernetes by implementing different technologies for components such as networking, storage, and authentication.
2.1.2. The benefits of containerized applications
Using containerized applications offers many advantages over using traditional deployment methods. Where applications were once expected to be installed on operating systems that included all their dependencies, containers let an application carry their dependencies with them. Creating containerized applications offers many benefits.
2.1.2.1. Operating system benefits
Containers use small, dedicated Linux operating systems without a kernel. Their file system, networking, cgroups, process tables, and namespaces are separate from the host Linux system, but the containers can integrate with the hosts seamlessly when necessary. Being based on Linux allows containers to use all the advantages that come with the open source development model of rapid innovation.
Because each container uses a dedicated operating system, you can deploy applications that require conflicting software dependencies on the same host. Each container carries its own dependent software and manages its own interfaces, such as networking and file systems, so applications never need to compete for those assets.
2.1.2.2. Deployment and scaling benefits
If you employ rolling upgrades between major releases of your application, you can continuously improve your applications without downtime and still maintain compatibility with the current release.
You can also deploy and test a new version of an application alongside the existing version. If the container passes your tests, simply deploy more new containers and remove the old ones.
Since all the software dependencies for an application are resolved within the container itself, you can use a standardized operating system on each host in your data center. You do not need to configure a specific operating system for each application host. When your data center needs more capacity, you can deploy another generic host system.
Similarly, scaling containerized applications is simple. OpenShift Container Platform offers a simple, standard way of scaling any containerized service. For example, if you build applications as a set of microservices rather than large, monolithic applications, you can scale the individual microservices individually to meet demand. This capability allows you to scale only the required services instead of the entire application, which can allow you to meet application demands while using minimal resources.
2.1.3. OpenShift Container Platform overview
OpenShift Container Platform provides enterprise-ready enhancements to Kubernetes, including the following enhancements:
- Hybrid cloud deployments. You can deploy OpenShift Container Platform clusters to a variety of public cloud platforms or in your data center.
- Integrated Red Hat technology. Major components in OpenShift Container Platform come from Red Hat Enterprise Linux (RHEL) and related Red Hat technologies. OpenShift Container Platform benefits from the intense testing and certification initiatives for Red Hat’s enterprise quality software.
- Open source development model. Development is completed in the open, and the source code is available from public software repositories. This open collaboration fosters rapid innovation and development.
Although Kubernetes excels at managing your applications, it does not specify or manage platform-level requirements or deployment processes. Powerful and flexible platform management tools and processes are important benefits that OpenShift Container Platform 4.14 offers. The following sections describe some unique features and benefits of OpenShift Container Platform.
2.1.3.1. Custom operating system
OpenShift Container Platform uses Red Hat Enterprise Linux CoreOS (RHCOS), a container-oriented operating system that is specifically designed for running containerized applications from OpenShift Container Platform and works with new tools to provide fast installation, Operator-based management, and simplified upgrades.
RHCOS includes:
- Ignition, which OpenShift Container Platform uses as a firstboot system configuration for initially bringing up and configuring machines.
- CRI-O, a Kubernetes native container runtime implementation that integrates closely with the operating system to deliver an efficient and optimized Kubernetes experience. CRI-O provides facilities for running, stopping, and restarting containers. It fully replaces the Docker Container Engine, which was used in OpenShift Container Platform 3.
- Kubelet, the primary node agent for Kubernetes that is responsible for launching and monitoring containers.
In OpenShift Container Platform 4.14, you must use RHCOS for all control plane machines, but you can use Red Hat Enterprise Linux (RHEL) as the operating system for compute machines, which are also known as worker machines. If you choose to use RHEL workers, you must perform more system maintenance than if you use RHCOS for all of the cluster machines.
2.1.3.2. Simplified installation and update process
With OpenShift Container Platform 4.14, if you have an account with the right permissions, you can deploy a production cluster in supported clouds by running a single command and providing a few values. You can also customize your cloud installation or install your cluster in your data center if you use a supported platform.
For clusters that use RHCOS for all machines, updating, or upgrading, OpenShift Container Platform is a simple, highly-automated process. Because OpenShift Container Platform completely controls the systems and services that run on each machine, including the operating system itself, from a central control plane, upgrades are designed to become automatic events. If your cluster contains RHEL worker machines, the control plane benefits from the streamlined update process, but you must perform more tasks to upgrade the RHEL machines.
2.1.3.3. Other key features
Operators are both the fundamental unit of the OpenShift Container Platform 4.14 code base and a convenient way to deploy applications and software components for your applications to use. In OpenShift Container Platform, Operators serve as the platform foundation and remove the need for manual upgrades of operating systems and control plane applications. OpenShift Container Platform Operators such as the Cluster Version Operator and Machine Config Operator allow simplified, cluster-wide management of those critical components.
Operator Lifecycle Manager (OLM) and the OperatorHub provide facilities for storing and distributing Operators to people developing and deploying applications.
The Red Hat Quay Container Registry is a Quay.io container registry that serves most of the container images and Operators to OpenShift Container Platform clusters. Quay.io is a public registry version of Red Hat Quay that stores millions of images and tags.
Other enhancements to Kubernetes in OpenShift Container Platform include improvements in software defined networking (SDN), authentication, log aggregation, monitoring, and routing. OpenShift Container Platform also offers a comprehensive web console and the custom OpenShift CLI (oc
) interface.
2.1.3.4. OpenShift Container Platform lifecycle
The following figure illustrates the basic OpenShift Container Platform lifecycle:
- Creating an OpenShift Container Platform cluster
- Managing the cluster
- Developing and deploying applications
- Scaling up applications
Figure 2.1. High level OpenShift Container Platform overview
![High-level OpenShift Container Platform flow](https://access.redhat.com/webassets/avalon/d/OpenShift_Container_Platform-4.14-Architecture-en-US/images/81d412906026bcfe261fe3fc8c77327b/ocp_arch_lifecycle.png)
2.1.4. Internet access for OpenShift Container Platform
In OpenShift Container Platform 4.14, you require access to the internet to install your cluster.
You must have internet access to:
- Access OpenShift Cluster Manager to download the installation program and perform subscription management. If the cluster has internet access and you do not disable Telemetry, that service automatically entitles your cluster.
- Access Quay.io to obtain the packages that are required to install your cluster.
- Obtain the packages that are required to perform cluster updates.
If your cluster cannot have direct internet access, you can perform a restricted network installation on some types of infrastructure that you provision. During that process, you download the required content and use it to populate a mirror registry with the installation packages. With some installation types, the environment that you install your cluster in will not require internet access. Before you update the cluster, you update the content of the mirror registry.
Chapter 3. Installation and update
3.1. About OpenShift Container Platform installation
The OpenShift Container Platform installation program offers four methods for deploying a cluster which are detailed in the following list:
- Interactive: You can deploy a cluster with the web-based Assisted Installer. This is an ideal approach for clusters with networks connected to the internet. The Assisted Installer is the easiest way to install OpenShift Container Platform, it provides smart defaults, and it performs pre-flight validations before installing the cluster. It also provides a RESTful API for automation and advanced configuration scenarios.
- Local Agent-based: You can deploy a cluster locally with the Agent-based Installer for disconnected environments or restricted networks. It provides many of the benefits of the Assisted Installer, but you must download and configure the Agent-based Installer first. Configuration is done with a command-line interface. This approach is ideal for disconnected environments.
- Automated: You can deploy a cluster on installer-provisioned infrastructure. The installation program uses each cluster host’s baseboard management controller (BMC) for provisioning. You can deploy clusters in connected or disconnected environments.
- Full control: You can deploy a cluster on infrastructure that you prepare and maintain, which provides maximum customizability. You can deploy clusters in connected or disconnected environments.
Each method deploys a cluster with the following characteristics:
- Highly available infrastructure with no single points of failure, which is available by default.
- Administrators can control what updates are applied and when.
3.1.1. About the installation program
You can use the installation program to deploy each type of cluster. The installation program generates the main assets, such as Ignition config files for the bootstrap, control plane, and compute machines. You can start an OpenShift Container Platform cluster with these three machine configurations, provided you correctly configured the infrastructure.
The OpenShift Container Platform installation program uses a set of targets and dependencies to manage cluster installations. The installation program has a set of targets that it must achieve, and each target has a set of dependencies. Because each target is only concerned with its own dependencies, the installation program can act to achieve multiple targets in parallel with the ultimate target being a running cluster. The installation program recognizes and uses existing components instead of running commands to create them again because the program meets the dependencies.
Figure 3.1. OpenShift Container Platform installation targets and dependencies
![OpenShift Container Platform installation targets and dependencies](https://access.redhat.com/webassets/avalon/d/OpenShift_Container_Platform-4.14-Architecture-en-US/images/6527feee3673861daba1c8118bcfa1b6/targets-and-dependencies.png)
3.1.2. About Red Hat Enterprise Linux CoreOS (RHCOS)
Post-installation, each cluster machine uses Red Hat Enterprise Linux CoreOS (RHCOS) as the operating system. RHCOS is the immutable container host version of Red Hat Enterprise Linux (RHEL) and features a RHEL kernel with SELinux enabled by default. RHCOS includes the kubelet
, which is the Kubernetes node agent, and the CRI-O container runtime, which is optimized for Kubernetes.
Every control plane machine in an OpenShift Container Platform 4.14 cluster must use RHCOS, which includes a critical first-boot provisioning tool called Ignition. This tool enables the cluster to configure the machines. Operating system updates are delivered as a bootable container image, using OSTree as a backend, that is deployed across the cluster by the Machine Config Operator. Actual operating system changes are made in-place on each machine as an atomic operation by using rpm-ostree. Together, these technologies enable OpenShift Container Platform to manage the operating system like it manages any other application on the cluster, by in-place upgrades that keep the entire platform up to date. These in-place updates can reduce the burden on operations teams.
If you use RHCOS as the operating system for all cluster machines, the cluster manages all aspects of its components and machines, including the operating system. Because of this, only the installation program and the Machine Config Operator can change machines. The installation program uses Ignition config files to set the exact state of each machine, and the Machine Config Operator completes more changes to the machines, such as the application of new certificates or keys, after installation.
3.1.3. Supported platforms for OpenShift Container Platform clusters
In OpenShift Container Platform 4.14, you can install a cluster that uses installer-provisioned infrastructure on the following platforms:
- Alibaba Cloud
- Amazon Web Services (AWS)
- Bare metal
- Google Cloud Platform (GCP)
- IBM Cloud®
- Microsoft Azure
- Microsoft Azure Stack Hub
- Nutanix
Red Hat OpenStack Platform (RHOSP)
- The latest OpenShift Container Platform release supports both the latest RHOSP long-life release and intermediate release. For complete RHOSP release compatibility, see the OpenShift Container Platform on RHOSP support matrix.
- VMware vSphere
For these clusters, all machines, including the computer that you run the installation process on, must have direct internet access to pull images for platform containers and provide telemetry data to Red Hat.
After installation, the following changes are not supported:
- Mixing cloud provider platforms.
- Mixing cloud provider components. For example, using a persistent storage framework from a another platform on the platform where you installed the cluster.
In OpenShift Container Platform 4.14, you can install a cluster that uses user-provisioned infrastructure on the following platforms:
- AWS
- Azure
- Azure Stack Hub
- Bare metal
- GCP
- IBM Power®
- IBM Z® or IBM® LinuxONE
RHOSP
- The latest OpenShift Container Platform release supports both the latest RHOSP long-life release and intermediate release. For complete RHOSP release compatibility, see the OpenShift Container Platform on RHOSP support matrix.
- VMware Cloud on AWS
- VMware vSphere
Depending on the supported cases for the platform, you can perform installations on user-provisioned infrastructure, so that you can run machines with full internet access, place your cluster behind a proxy, or perform a disconnected installation.
In a disconnected installation, you can download the images that are required to install a cluster, place them in a mirror registry, and use that data to install your cluster. While you require internet access to pull images for platform containers, with a disconnected installation on vSphere or bare metal infrastructure, your cluster machines do not require direct internet access.
The OpenShift Container Platform 4.x Tested Integrations page contains details about integration testing for different platforms.
3.1.4. Installation process
Except for the Assisted Installer, when you install an OpenShift Container Platform cluster, you must download the installation program from the appropriate Cluster Type page on the OpenShift Cluster Manager Hybrid Cloud Console. This console manages:
- REST API for accounts.
- Registry tokens, which are the pull secrets that you use to obtain the required components.
- Cluster registration, which associates the cluster identity to your Red Hat account to facilitate the gathering of usage metrics.
In OpenShift Container Platform 4.14, the installation program is a Go binary file that performs a series of file transformations on a set of assets. The way you interact with the installation program differs depending on your installation type. Consider the following installation use cases:
- To deploy a cluster with the Assisted Installer, you must configure the cluster settings by using the Assisted Installer. There is no installation program to download and configure. After you finish setting the cluster configuration, you download a discovery ISO and then boot cluster machines with that image. You can install clusters with the Assisted Installer on Nutanix, vSphere, and bare metal with full integration, and other platforms without integration. If you install on bare metal, you must provide all of the cluster infrastructure and resources, including the networking, load balancing, storage, and individual cluster machines.
- To deploy clusters with the Agent-based Installer, you can download the Agent-based Installer first. You can then configure the cluster and generate a discovery image. You boot cluster machines with the discovery image, which installs an agent that communicates with the installation program and handles the provisioning for you instead of you interacting with the installation program or setting up a provisioner machine yourself. You must provide all of the cluster infrastructure and resources, including the networking, load balancing, storage, and individual cluster machines. This approach is ideal for disconnected environments.
- For clusters with installer-provisioned infrastructure, you delegate the infrastructure bootstrapping and provisioning to the installation program instead of doing it yourself. The installation program creates all of the networking, machines, and operating systems that are required to support the cluster, except if you install on bare metal. If you install on bare metal, you must provide all of the cluster infrastructure and resources, including the bootstrap machine, networking, load balancing, storage, and individual cluster machines.
- If you provision and manage the infrastructure for your cluster, you must provide all of the cluster infrastructure and resources, including the bootstrap machine, networking, load balancing, storage, and individual cluster machines.
For the installation program, the program uses three sets of files during installation: an installation configuration file that is named install-config.yaml
, Kubernetes manifests, and Ignition config files for your machine types.
You can modify Kubernetes and the Ignition config files that control the underlying RHCOS operating system during installation. However, no validation is available to confirm the suitability of any modifications that you make to these objects. If you modify these objects, you might render your cluster non-functional. Because of this risk, modifying Kubernetes and Ignition config files is not supported unless you are following documented procedures or are instructed to do so by Red Hat support.
The installation configuration file is transformed into Kubernetes manifests, and then the manifests are wrapped into Ignition config files. The installation program uses these Ignition config files to create the cluster.
The installation configuration files are all pruned when you run the installation program, so be sure to back up all the configuration files that you want to use again.
You cannot modify the parameters that you set during installation, but you can modify many cluster attributes after installation.
The installation process with the Assisted Installer
Installation with the Assisted Installer involves creating a cluster configuration interactively by using the web-based user interface or the RESTful API. The Assisted Installer user interface prompts you for required values and provides reasonable default values for the remaining parameters, unless you change them in the user interface or with the API. The Assisted Installer generates a discovery image, which you download and use to boot the cluster machines. The image installs RHCOS and an agent, and the agent handles the provisioning for you. You can install OpenShift Container Platform with the Assisted Installer and full integration on Nutanix, vSphere, and bare metal. Additionally, you can install OpenShift Container Platform with the Assisted Installer on other platforms without integration.
OpenShift Container Platform manages all aspects of the cluster, including the operating system itself. Each machine boots with a configuration that references resources hosted in the cluster that it joins. This configuration allows the cluster to manage itself as updates are applied.
If possible, use the Assisted Installer feature to avoid having to download and configure the Agent-based Installer.
The installation process with Agent-based infrastructure
Agent-based installation is similar to using the Assisted Installer, except that you must initially download and install the Agent-based Installer. An Agent-based installation is useful when you want the convenience of the Assisted Installer, but you need to install a cluster in a disconnected environment.
If possible, use the Agent-based installation feature to avoid having to create a provisioner machine with a bootstrap VM, and then provision and maintain the cluster infrastructure.
The installation process with installer-provisioned infrastructure
The default installation type uses installer-provisioned infrastructure. By default, the installation program acts as an installation wizard, prompting you for values that it cannot determine on its own and providing reasonable default values for the remaining parameters. You can also customize the installation process to support advanced infrastructure scenarios. The installation program provisions the underlying infrastructure for the cluster.
You can install either a standard cluster or a customized cluster. With a standard cluster, you provide minimum details that are required to install the cluster. With a customized cluster, you can specify more details about the platform, such as the number of machines that the control plane uses, the type of virtual machine that the cluster deploys, or the CIDR range for the Kubernetes service network.
If possible, use this feature to avoid having to provision and maintain the cluster infrastructure. In all other environments, you use the installation program to generate the assets that you require to provision your cluster infrastructure.
With installer-provisioned infrastructure clusters, OpenShift Container Platform manages all aspects of the cluster, including the operating system itself. Each machine boots with a configuration that references resources hosted in the cluster that it joins. This configuration allows the cluster to manage itself as updates are applied.
The installation process with user-provisioned infrastructure
You can also install OpenShift Container Platform on infrastructure that you provide. You use the installation program to generate the assets that you require to provision the cluster infrastructure, create the cluster infrastructure, and then deploy the cluster to the infrastructure that you provided.
If you do not use infrastructure that the installation program provisioned, you must manage and maintain the cluster resources yourself. The following list details some of these self-managed resources:
- The underlying infrastructure for the control plane and compute machines that make up the cluster
- Load balancers
- Cluster networking, including the DNS records and required subnets
- Storage for the cluster infrastructure and applications
If your cluster uses user-provisioned infrastructure, you have the option of adding RHEL compute machines to your cluster.
Installation process details
When a cluster is provisioned, each machine in the cluster requires information about the cluster. OpenShift Container Platform uses a temporary bootstrap machine during initial configuration to provide the required information to the permanent control plane. The temporary bootstrap machine boots by using an Ignition config file that describes how to create the cluster. The bootstrap machine creates the control plane machines that make up the control plane. The control plane machines then create the compute machines, which are also known as worker machines. The following figure illustrates this process:
Figure 3.2. Creating the bootstrap, control plane, and compute machines
![Creating bootstrap](https://access.redhat.com/webassets/avalon/d/OpenShift_Container_Platform-4.14-Architecture-en-US/images/9fb14e59171a618c486862da6b1ae17b/create-nodes.png)
After the cluster machines initialize, the bootstrap machine is destroyed. All clusters use the bootstrap process to initialize the cluster, but if you provision the infrastructure for your cluster, you must complete many of the steps manually.
-
The Ignition config files that the installation program generates contain certificates that expire after 24 hours, which are then renewed at that time. If the cluster is shut down before renewing the certificates and the cluster is later restarted after the 24 hours have elapsed, the cluster automatically recovers the expired certificates. The exception is that you must manually approve the pending
node-bootstrapper
certificate signing requests (CSRs) to recover kubelet certificates. See the documentation for Recovering from expired control plane certificates for more information. - Consider using Ignition config files within 12 hours after they are generated, because the 24-hour certificate rotates from 16 to 22 hours after the cluster is installed. By using the Ignition config files within 12 hours, you can avoid installation failure if the certificate update runs during installation.
Bootstrapping a cluster involves the following steps:
- The bootstrap machine boots and starts hosting the remote resources required for the control plane machines to boot. If you provision the infrastructure, this step requires manual intervention.
- The bootstrap machine starts a single-node etcd cluster and a temporary Kubernetes control plane.
- The control plane machines fetch the remote resources from the bootstrap machine and finish booting. If you provision the infrastructure, this step requires manual intervention.
- The temporary control plane schedules the production control plane to the production control plane machines.
- The Cluster Version Operator (CVO) comes online and installs the etcd Operator. The etcd Operator scales up etcd on all control plane nodes.
- The temporary control plane shuts down and passes control to the production control plane.
- The bootstrap machine injects OpenShift Container Platform components into the production control plane.
- The installation program shuts down the bootstrap machine. If you provision the infrastructure, this step requires manual intervention.
- The control plane sets up the compute nodes.
- The control plane installs additional services in the form of a set of Operators.
The result of this bootstrapping process is a running OpenShift Container Platform cluster. The cluster then downloads and configures remaining components needed for the day-to-day operations, including the creation of compute machines in supported environments.
Installation scope
The scope of the OpenShift Container Platform installation program is intentionally narrow. It is designed for simplicity and ensured success. You can complete many more configuration tasks after installation completes.
Additional resources
- See Available cluster customizations for details about OpenShift Container Platform configuration resources.
3.2. About the OpenShift Update Service
The OpenShift Update Service (OSUS) provides update recommendations to OpenShift Container Platform, including Red Hat Enterprise Linux CoreOS (RHCOS). It provides a graph, or diagram, that contains the vertices of component Operators and the edges that connect them. The edges in the graph show which versions you can safely update to. The vertices are update payloads that specify the intended state of the managed cluster components.
The Cluster Version Operator (CVO) in your cluster checks with the OpenShift Update Service to see the valid updates and update paths based on current component versions and information in the graph. When you request an update, the CVO uses the corresponding release image to update your cluster. The release artifacts are hosted in Quay as container images.
To allow the OpenShift Update Service to provide only compatible updates, a release verification pipeline drives automation. Each release artifact is verified for compatibility with supported cloud platforms and system architectures, as well as other component packages. After the pipeline confirms the suitability of a release, the OpenShift Update Service notifies you that it is available.
The OpenShift Update Service displays all recommended updates for your current cluster. If an update path is not recommended by the OpenShift Update Service, it might be because of a known issue with the update or the target release.
Two controllers run during continuous update mode. The first controller continuously updates the payload manifests, applies the manifests to the cluster, and outputs the controlled rollout status of the Operators to indicate whether they are available, upgrading, or failed. The second controller polls the OpenShift Update Service to determine if updates are available.
Only updating to a newer version is supported. Reverting or rolling back your cluster to a previous version is not supported. If your update fails, contact Red Hat support.
During the update process, the Machine Config Operator (MCO) applies the new configuration to your cluster machines. The MCO cordons the number of nodes specified by the maxUnavailable
field on the machine configuration pool and marks them unavailable. By default, this value is set to 1
. The MCO updates the affected nodes alphabetically by zone, based on the topology.kubernetes.io/zone
label. If a zone has more than one node, the oldest nodes are updated first. For nodes that do not use zones, such as in bare metal deployments, the nodes are updated by age, with the oldest nodes updated first. The MCO updates the number of nodes as specified by the maxUnavailable
field on the machine configuration pool at a time. The MCO then applies the new configuration and reboots the machine.
The default setting for maxUnavailable
is 1
for all the machine config pools in OpenShift Container Platform. It is recommended to not change this value and update one control plane node at a time. Do not change this value to 3
for the control plane pool.
If you use Red Hat Enterprise Linux (RHEL) machines as workers, the MCO does not update the kubelet because you must update the OpenShift API on the machines first.
With the specification for the new version applied to the old kubelet, the RHEL machine cannot return to the Ready
state. You cannot complete the update until the machines are available. However, the maximum number of unavailable nodes is set to ensure that normal cluster operations can continue with that number of machines out of service.
The OpenShift Update Service is composed of an Operator and one or more application instances.
3.3. Support policy for unmanaged Operators
The management state of an Operator determines whether an Operator is actively managing the resources for its related component in the cluster as designed. If an Operator is set to an unmanaged state, it does not respond to changes in configuration nor does it receive updates.
While this can be helpful in non-production clusters or during debugging, Operators in an unmanaged state are unsupported and the cluster administrator assumes full control of the individual component configurations and upgrades.
An Operator can be set to an unmanaged state using the following methods:
Individual Operator configuration
Individual Operators have a
managementState
parameter in their configuration. This can be accessed in different ways, depending on the Operator. For example, the Red Hat OpenShift Logging Operator accomplishes this by modifying a custom resource (CR) that it manages, while the Cluster Samples Operator uses a cluster-wide configuration resource.Changing the
managementState
parameter toUnmanaged
means that the Operator is not actively managing its resources and will take no action related to the related component. Some Operators might not support this management state as it might damage the cluster and require manual recovery.WarningChanging individual Operators to the
Unmanaged
state renders that particular component and functionality unsupported. Reported issues must be reproduced inManaged
state for support to proceed.Cluster Version Operator (CVO) overrides
The
spec.overrides
parameter can be added to the CVO’s configuration to allow administrators to provide a list of overrides to the CVO’s behavior for a component. Setting thespec.overrides[].unmanaged
parameter totrue
for a component blocks cluster upgrades and alerts the administrator after a CVO override has been set:Disabling ownership via cluster version overrides prevents upgrades. Please remove overrides before continuing.
WarningSetting a CVO override puts the entire cluster in an unsupported state. Reported issues must be reproduced after removing any overrides for support to proceed.
3.4. Next steps
Chapter 4. Red Hat OpenShift Cluster Manager
Red Hat OpenShift Cluster Manager is a managed service where you can install, modify, operate, and upgrade your Red Hat OpenShift clusters. This service allows you to work with all of your organization’s clusters from a single dashboard.
OpenShift Cluster Manager guides you to install OpenShift Container Platform, Red Hat OpenShift Service on AWS (ROSA), and OpenShift Dedicated clusters. It is also responsible for managing both OpenShift Container Platform clusters after self-installation as well as your ROSA and OpenShift Dedicated clusters.
You can use OpenShift Cluster Manager to do the following actions:
- Create new clusters
- View cluster details and metrics
- Manage your clusters with tasks such as scaling, changing node labels, networking, authentication
- Manage access control
- Monitor clusters
- Schedule upgrades
4.1. Accessing Red Hat OpenShift Cluster Manager
You can access OpenShift Cluster Manager with your configured OpenShift account.
Prerequisites
- You have an account that is part of an OpenShift organization.
- If you are creating a cluster, your organization has specified quota.
Procedure
- Log in to OpenShift Cluster Manager using your login credentials.
4.2. General actions
On the top right of the cluster page, there are some actions that a user can perform on the entire cluster:
- Open console launches a web console so that the cluster owner can issue commands to the cluster.
- Actions drop-down menu allows the cluster owner to rename the display name of the cluster, change the amount of load balancers and persistent storage on the cluster, if applicable, manually set the node count, and delete the cluster.
- Refresh icon forces a refresh of the cluster.
4.3. Cluster tabs
Selecting an active, installed cluster shows tabs associated with that cluster. The following tabs display after the cluster’s installation completes:
- Overview
- Access control
- Add-ons
- Networking
- Insights Advisor
- Machine pools
- Support
- Settings
4.3.1. Overview tab
The Overview tab provides information about how your cluster was configured:
- Cluster ID is the unique identification for the created cluster. This ID can be used when issuing commands to the cluster from the command line.
- Type shows the OpenShift version that the cluster is using.
- Region is the server region.
- Provider shows which cloud provider that the cluster was built upon.
- Availability shows which type of availability zone that the cluster uses, either single or multizone.
- Version is the OpenShift version that is installed on the cluster. If there is an update available, you can update from this field.
- Created at shows the date and time that the cluster was created.
- Owner identifies who created the cluster and has owner rights.
- Subscription type shows the subscription model that was selected on creation.
- Infrastructure type is the type of account that the cluster uses.
- Status displays the current status of the cluster.
- Total vCPU shows the total available virtual CPU for this cluster.
- Total memory shows the total available memory for this cluster.
- Load balancers
- Persistent storage displays the amount of storage that is available on this cluster.
- Nodes shows the actual and desired nodes on the cluster. These numbers might not match due to cluster scaling.
- Network field shows the address and prefixes for network connectivity.
- Resource usage section of the tab displays the resources in use with a graph.
- Advisor recommendations section gives insight in relation to security, performance, availability, and stability. This section requires the use of remote health functionality. See Using Insights to identify issues with your cluster in the Additional resources section.
- Cluster history section shows everything that has been done with the cluster including creation and when a new version is identified.
4.3.2. Access control tab
The Access control tab allows the cluster owner to set up an identity provider, grant elevated permissions, and grant roles to other users.
Prerequisites
- You must be the cluster owner or have the correct permissions to grant roles on the cluster.
Procedure
- Select the Grant role button.
- Enter the Red Hat account login for the user that you wish to grant a role on the cluster.
- Select the Grant role button on the dialog box.
- The dialog box closes, and the selected user shows the "Cluster Editor" access.
4.3.3. Add-ons tab
The Add-ons tab displays all of the optional add-ons that can be added to the cluster. Select the desired add-on, and then select Install below the description for the add-on that displays.
4.3.4. Insights Advisor tab
The Insights Advisor tab uses the Remote Health functionality of the OpenShift Container Platform to identify and mitigate risks to security, performance, availability, and stability. See Using Insights to identify issues with your cluster in the OpenShift Container Platform documentation.
4.3.5. Machine pools tab
The Machine pools tab allows the cluster owner to create new machine pools, if there is enough available quota, or edit an existing machine pool.
Selecting the More options > Scale opens the "Edit node count" dialog. In this dialog, you can change the node count per availability zone. If autoscaling is enabled, you can also set the range for autoscaling.
4.3.6. Support tab
In the Support tab, you can add notification contacts for individuals that should receive cluster notifications. The username or email address that you provide must relate to a user account in the Red Hat organization where the cluster is deployed.
Also from this tab, you can open a support case to request technical support for your cluster.
4.3.7. Settings tab
The Settings tab provides a few options for the cluster owner:
- Monitoring, which is enabled by default, allows for reporting done on user-defined actions. See Understanding the monitoring stack.
- Update strategy allows you to determine if the cluster automatically updates on a certain day of the week at a specified time or if all updates are scheduled manually.
- Node draining sets the duration that protected workloads are respected during updates. When this duration has passed, the node is forcibly removed.
- Update status shows the current version and if there are any updates available.
4.4. Additional resources
- For the complete documentation for OpenShift Cluster Manager, see OpenShift Cluster Manager documentation.
Chapter 5. About the multicluster engine for Kubernetes Operator
One of the challenges of scaling Kubernetes environments is managing the lifecycle of a growing fleet. To meet that challenge, you can use the multicluster engine Operator. The operator delivers full lifecycle capabilities for managed OpenShift Container Platform clusters and partial lifecycle management for other Kubernetes distributions. It is available in two ways:
- As a standalone operator that you install as part of your OpenShift Container Platform or OpenShift Kubernetes Engine subscription
- As part of Red Hat Advanced Cluster Management for Kubernetes
5.1. Cluster management with multicluster engine on OpenShift Container Platform
When you enable multicluster engine on OpenShift Container Platform, you gain the following capabilities:
- Hosted control planes, which is a feature that is based on the HyperShift project. With a centralized hosted control plane, you can operate OpenShift Container Platform clusters in a hyperscale manner.
- Hive, which provisions self-managed OpenShift Container Platform clusters to the hub and completes the initial configurations for those clusters.
- klusterlet agent, which registers managed clusters to the hub.
- Infrastructure Operator, which manages the deployment of the Assisted Service to orchestrate on-premise bare metal and vSphere installations of OpenShift Container Platform, such as SNO on bare metal. The Infrastructure Operator includes GitOps Zero Touch Provisioning (ZTP), which fully automates cluster creation on bare metal and vSphere provisioning with GitOps workflows to manage deployments and configuration changes.
- Open cluster management, which provides resources to manage Kubernetes clusters.
The multicluster engine is included with your OpenShift Container Platform support subscription and is delivered separately from the core payload. To start to use multicluster engine, you deploy the OpenShift Container Platform cluster and then install the operator. For more information, see Installing and upgrading multicluster engine operator.
5.2. Cluster management with Red Hat Advanced Cluster Management
If you need cluster management capabilities beyond what OpenShift Container Platform with multicluster engine can provide, consider Red Hat Advanced Cluster Management. The multicluster engine is an integral part of Red Hat Advanced Cluster Management and is enabled by default.
5.3. Additional resources
For the complete documentation for multicluster engine, see Cluster lifecycle with multicluster engine documentation, which is part of the product documentation for Red Hat Advanced Cluster Management.
Chapter 6. Control plane architecture
The control plane, which is composed of control plane machines, manages the OpenShift Container Platform cluster. The control plane machines manage workloads on the compute machines, which are also known as worker machines. The cluster itself manages all upgrades to the machines by the actions of the Cluster Version Operator (CVO), the Machine Config Operator, and a set of individual Operators.
6.1. Node configuration management with machine config pools
Machines that run control plane components or user workloads are divided into groups based on the types of resources they handle. These groups of machines are called machine config pools (MCP). Each MCP manages a set of nodes and its corresponding machine configs. The role of the node determines which MCP it belongs to; the MCP governs nodes based on its assigned node role label. Nodes in an MCP have the same configuration; this means nodes can be scaled up and torn down in response to increased or decreased workloads.
By default, there are two MCPs created by the cluster when it is installed: master
and worker
. Each default MCP has a defined configuration applied by the Machine Config Operator (MCO), which is responsible for managing MCPs and facilitating MCP upgrades. You can create additional MCPs, or custom pools, to manage nodes that have custom use cases that extend outside of the default node types.
Custom pools are pools that inherit their configurations from the worker pool. They use any machine config targeted for the worker pool, but add the ability to deploy changes only targeted at the custom pool. Since a custom pool inherits its configuration from the worker pool, any change to the worker pool is applied to the custom pool as well. Custom pools that do not inherit their configurations from the worker pool are not supported by the MCO.
A node can only be included in one MCP. If a node has multiple labels that correspond to several MCPs, like worker,infra
, it is managed by the infra custom pool, not the worker pool. Custom pools take priority on selecting nodes to manage based on node labels; nodes that do not belong to a custom pool are managed by the worker pool.
It is recommended to have a custom pool for every node role you want to manage in your cluster. For example, if you create infra nodes to handle infra workloads, it is recommended to create a custom infra MCP to group those nodes together. If you apply an infra
role label to a worker node so it has the worker,infra
dual label, but do not have a custom infra MCP, the MCO considers it a worker node. If you remove the worker
label from a node and apply the infra
label without grouping it in a custom pool, the node is not recognized by the MCO and is unmanaged by the cluster.
Any node labeled with the infra
role that is only running infra workloads is not counted toward the total number of subscriptions. The MCP managing an infra node is mutually exclusive from how the cluster determines subscription charges; tagging a node with the appropriate infra
role and using taints to prevent user workloads from being scheduled on that node are the only requirements for avoiding subscription charges for infra workloads.
The MCO applies updates for pools independently; for example, if there is an update that affects all pools, nodes from each pool update in parallel with each other. If you add a custom pool, nodes from that pool also attempt to update concurrently with the master and worker nodes.
There might be situations where the configuration on a node does not fully match what the currently-applied machine config specifies. This state is called configuration drift. The Machine Config Daemon (MCD) regularly checks the nodes for configuration drift. If the MCD detects configuration drift, the MCO marks the node degraded
until an administrator corrects the node configuration. A degraded node is online and operational, but, it cannot be updated.
Additional resources
6.2. Machine roles in OpenShift Container Platform
OpenShift Container Platform assigns hosts different roles. These roles define the function of the machine within the cluster. The cluster contains definitions for the standard master
and worker
role types.
The cluster also contains the definition for the bootstrap
role. Because the bootstrap machine is used only during cluster installation, its function is explained in the cluster installation documentation.
6.2.1. Control plane and node host compatibility
The OpenShift Container Platform version must match between control plane host and node host. For example, in a 4.14 cluster, all control plane hosts must be 4.14 and all nodes must be 4.14.
Temporary mismatches during cluster upgrades are acceptable. For example, when upgrading from the previous OpenShift Container Platform version to 4.14, some nodes will upgrade to 4.14 before others. Prolonged skewing of control plane hosts and node hosts might expose older compute machines to bugs and missing features. Users should resolve skewed control plane hosts and node hosts as soon as possible.
The kubelet
service must not be newer than kube-apiserver
, and can be up to two minor versions older depending on whether your OpenShift Container Platform version is odd or even. The table below shows the appropriate version compatibility:
OpenShift Container Platform version | Supported kubelet skew |
---|---|
Odd OpenShift Container Platform minor versions [1] | Up to one version older |
Even OpenShift Container Platform minor versions [2] | Up to two versions older |
- For example, OpenShift Container Platform 4.11, 4.13.
- For example, OpenShift Container Platform 4.10, 4.12.
6.2.2. Cluster workers
In a Kubernetes cluster, the worker nodes are where the actual workloads requested by Kubernetes users run and are managed. The worker nodes advertise their capacity and the scheduler, which a control plane service, determines on which nodes to start pods and containers. Important services run on each worker node, including CRI-O, which is the container engine; Kubelet, which is the service that accepts and fulfills requests for running and stopping container workloads; a service proxy, which manages communication for pods across workers; and the runC or crun low-level container runtime, which creates and runs containers.
For information about how to enable crun instead of the default runC, see the documentation for creating a ContainerRuntimeConfig
CR.
In OpenShift Container Platform, compute machine sets control the compute machines, which are assigned the worker
machine role. Machines with the worker
role drive compute workloads that are governed by a specific machine pool that autoscales them. Because OpenShift Container Platform has the capacity to support multiple machine types, the machines with the worker
role are classed as compute machines. In this release, the terms worker machine and compute machine are used interchangeably because the only default type of compute machine is the worker machine. In future versions of OpenShift Container Platform, different types of compute machines, such as infrastructure machines, might be used by default.
Compute machine sets are groupings of compute machine resources under the machine-api
namespace. Compute machine sets are configurations that are designed to start new compute machines on a specific cloud provider. Conversely, machine config pools (MCPs) are part of the Machine Config Operator (MCO) namespace. An MCP is used to group machines together so the MCO can manage their configurations and facilitate their upgrades.
6.2.3. Cluster control planes
In a Kubernetes cluster, the master nodes run services that are required to control the Kubernetes cluster. In OpenShift Container Platform, the control plane is comprised of control plane machines that have a master
machine role. They contain more than just the Kubernetes services for managing the OpenShift Container Platform cluster.
For most OpenShift Container Platform clusters, control plane machines are defined by a series of standalone machine API resources. For supported cloud provider and OpenShift Container Platform version combinations, control planes can be managed with control plane machine sets. Extra controls apply to control plane machines to prevent you from deleting all control plane machines and breaking your cluster.
Exactly three control plane nodes must be used for all production deployments.
Services that fall under the Kubernetes category on the control plane include the Kubernetes API server, etcd, the Kubernetes controller manager, and the Kubernetes scheduler.
Component | Description |
---|---|
Kubernetes API server | The Kubernetes API server validates and configures the data for pods, services, and replication controllers. It also provides a focal point for the shared state of the cluster. |
etcd | etcd stores the persistent control plane state while other components watch etcd for changes to bring themselves into the specified state. |
Kubernetes controller manager | The Kubernetes controller manager watches etcd for changes to objects such as replication, namespace, and service account controller objects, and then uses the API to enforce the specified state. Several such processes create a cluster with one active leader at a time. |
Kubernetes scheduler | The Kubernetes scheduler watches for newly created pods without an assigned node and selects the best node to host the pod. |
There are also OpenShift services that run on the control plane, which include the OpenShift API server, OpenShift controller manager, OpenShift OAuth API server, and OpenShift OAuth server.
Component | Description |
---|---|
OpenShift API server | The OpenShift API server validates and configures the data for OpenShift resources, such as projects, routes, and templates. The OpenShift API server is managed by the OpenShift API Server Operator. |
OpenShift controller manager | The OpenShift controller manager watches etcd for changes to OpenShift objects, such as project, route, and template controller objects, and then uses the API to enforce the specified state. The OpenShift controller manager is managed by the OpenShift Controller Manager Operator. |
OpenShift OAuth API server | The OpenShift OAuth API server validates and configures the data to authenticate to OpenShift Container Platform, such as users, groups, and OAuth tokens. The OpenShift OAuth API server is managed by the Cluster Authentication Operator. |
OpenShift OAuth server | Users request tokens from the OpenShift OAuth server to authenticate themselves to the API. The OpenShift OAuth server is managed by the Cluster Authentication Operator. |
Some of these services on the control plane machines run as systemd services, while others run as static pods.
Systemd services are appropriate for services that you need to always come up on that particular system shortly after it starts. For control plane machines, those include sshd, which allows remote login. It also includes services such as:
- The CRI-O container engine (crio), which runs and manages the containers. OpenShift Container Platform 4.14 uses CRI-O instead of the Docker Container Engine.
- Kubelet (kubelet), which accepts requests for managing containers on the machine from control plane services.
CRI-O and Kubelet must run directly on the host as systemd services because they need to be running before you can run other containers.
The installer-*
and revision-pruner-*
control plane pods must run with root permissions because they write to the /etc/kubernetes
directory, which is owned by the root user. These pods are in the following namespaces:
-
openshift-etcd
-
openshift-kube-apiserver
-
openshift-kube-controller-manager
-
openshift-kube-scheduler
6.3. Operators in OpenShift Container Platform
Operators are among the most important components of OpenShift Container Platform. Operators are the preferred method of packaging, deploying, and managing services on the control plane. They can also provide advantages to applications that users run.
Operators integrate with Kubernetes APIs and CLI tools such as kubectl
and oc
commands. They provide the means of monitoring applications, performing health checks, managing over-the-air (OTA) updates, and ensuring that applications remain in your specified state.
Operators also offer a more granular configuration experience. You configure each component by modifying the API that the Operator exposes instead of modifying a global configuration file.
Because CRI-O and the Kubelet run on every node, almost every other cluster function can be managed on the control plane by using Operators. Components that are added to the control plane by using Operators include critical networking and credential services.
While both follow similar Operator concepts and goals, Operators in OpenShift Container Platform are managed by two different systems, depending on their purpose:
- Cluster Operators, which are managed by the Cluster Version Operator (CVO), are installed by default to perform cluster functions.
- Optional add-on Operators, which are managed by Operator Lifecycle Manager (OLM), can be made accessible for users to run in their applications.
6.3.1. Cluster Operators
In OpenShift Container Platform, all cluster functions are divided into a series of default cluster Operators. Cluster Operators manage a particular area of cluster functionality, such as cluster-wide application logging, management of the Kubernetes control plane, or the machine provisioning system.
Cluster Operators are represented by a ClusterOperator
object, which cluster administrators can view in the OpenShift Container Platform web console from the Administration → Cluster Settings page. Each cluster Operator provides a simple API for determining cluster functionality. The Operator hides the details of managing the lifecycle of that component. Operators can manage a single component or tens of components, but the end goal is always to reduce operational burden by automating common actions.
Additional resources
6.3.2. Add-on Operators
Operator Lifecycle Manager (OLM) and OperatorHub are default components in OpenShift Container Platform that help manage Kubernetes-native applications as Operators. Together they provide the system for discovering, installing, and managing the optional add-on Operators available on the cluster.
Using OperatorHub in the OpenShift Container Platform web console, cluster administrators and authorized users can select Operators to install from catalogs of Operators. After installing an Operator from OperatorHub, it can be made available globally or in specific namespaces to run in user applications.
Default catalog sources are available that include Red Hat Operators, certified Operators, and community Operators. Cluster administrators can also add their own custom catalog sources, which can contain a custom set of Operators.
Developers can use the Operator SDK to help author custom Operators that take advantage of OLM features, as well. Their Operator can then be bundled and added to a custom catalog source, which can be added to a cluster and made available to users.
OLM does not manage the cluster Operators that comprise the OpenShift Container Platform architecture.
Additional resources
- For more details on running add-on Operators in OpenShift Container Platform, see the Operators guide sections on Operator Lifecycle Manager (OLM) and OperatorHub.
- For more details on the Operator SDK, see Developing Operators.
6.3.3. Platform Operators (Technology Preview)
The platform Operator type is a Technology Preview feature only. Technology Preview features are not supported with Red Hat production service level agreements (SLAs) and might not be functionally complete. Red Hat does not recommend using them in production. These features provide early access to upcoming product features, enabling customers to test functionality and provide feedback during the development process.
For more information about the support scope of Red Hat Technology Preview features, see Technology Preview Features Support Scope.
Operator Lifecycle Manager (OLM) introduces a new type of Operator called platform Operators. A platform Operator is an OLM-based Operator that can be installed during or after an OpenShift Container Platform cluster’s Day 0 operations and participates in the cluster’s lifecycle. As a cluster administrator, you can use platform Operators to further customize your OpenShift Container Platform installation to meet your requirements and use cases.
Using the existing cluster capabilities feature in OpenShift Container Platform, cluster administrators can already disable a subset of Cluster Version Operator-based (CVO) components considered non-essential to the initial payload prior to cluster installation. Platform Operators iterate on this model by providing additional customization options. Through the platform Operator mechanism, which relies on resources from the RukPak component, OLM-based Operators can now be installed at cluster installation time and can block cluster rollout if the Operator fails to install successfully.
In OpenShift Container Platform 4.12, this Technology Preview release focuses on the basic platform Operator mechanism and builds a foundation for expanding the concept in upcoming releases. You can use the cluster-wide PlatformOperator
API to configure Operators before or after cluster creation on clusters that have enabled the TechPreviewNoUpgrade
feature set.
6.4. About the Machine Config Operator
OpenShift Container Platform 4.14 integrates both operating system and cluster management. Because the cluster manages its own updates, including updates to Red Hat Enterprise Linux CoreOS (RHCOS) on cluster nodes, OpenShift Container Platform provides an opinionated lifecycle management experience that simplifies the orchestration of node upgrades.
OpenShift Container Platform employs three daemon sets and controllers to simplify node management. These daemon sets orchestrate operating system updates and configuration changes to the hosts by using standard Kubernetes-style constructs. They include:
-
The
machine-config-controller
, which coordinates machine upgrades from the control plane. It monitors all of the cluster nodes and orchestrates their configuration updates. -
The
machine-config-daemon
daemon set, which runs on each node in the cluster and updates a machine to configuration as defined by machine config and as instructed by the MachineConfigController. When the node detects a change, it drains off its pods, applies the update, and reboots. These changes come in the form of Ignition configuration files that apply the specified machine configuration and control kubelet configuration. The update itself is delivered in a container. This process is key to the success of managing OpenShift Container Platform and RHCOS updates together. -
The
machine-config-server
daemon set, which provides the Ignition config files to control plane nodes as they join the cluster.
The machine configuration is a subset of the Ignition configuration. The machine-config-daemon
reads the machine configuration to see if it needs to do an OSTree update or if it must apply a series of systemd kubelet file changes, configuration changes, or other changes to the operating system or OpenShift Container Platform configuration.
When you perform node management operations, you create or modify a KubeletConfig
custom resource (CR).
When changes are made to a machine configuration, the Machine Config Operator (MCO) automatically reboots all corresponding nodes in order for the changes to take effect.
To prevent the nodes from automatically rebooting after machine configuration changes, before making the changes, you must pause the autoreboot process by setting the spec.paused
field to true
in the corresponding machine config pool. When paused, machine configuration changes are not applied until you set the spec.paused
field to false
and the nodes have rebooted into the new configuration.
The following modifications do not trigger a node reboot:
When the MCO detects any of the following changes, it applies the update without draining or rebooting the node:
-
Changes to the SSH key in the
spec.config.passwd.users.sshAuthorizedKeys
parameter of a machine config. -
Changes to the global pull secret or pull secret in the
openshift-config
namespace. -
Automatic rotation of the
/etc/kubernetes/kubelet-ca.crt
certificate authority (CA) by the Kubernetes API Server Operator.
-
Changes to the SSH key in the
When the MCO detects changes to the
/etc/containers/registries.conf
file, such as adding or editing anImageDigestMirrorSet
,ImageTagMirrorSet
, orImageContentSourcePolicy
object, it drains the corresponding nodes, applies the changes, and uncordons the nodes. The node drain does not happen for the following changes:-
The addition of a registry with the
pull-from-mirror = "digest-only"
parameter set for each mirror. -
The addition of a mirror with the
pull-from-mirror = "digest-only"
parameter set in a registry. -
The addition of items to the
unqualified-search-registries
list.
-
The addition of a registry with the
There might be situations where the configuration on a node does not fully match what the currently-applied machine config specifies. This state is called configuration drift. The Machine Config Daemon (MCD) regularly checks the nodes for configuration drift. If the MCD detects configuration drift, the MCO marks the node degraded
until an administrator corrects the node configuration. A degraded node is online and operational, but, it cannot be updated.
Additional resources
- For more information about detecting configuration drift, see Understanding configuration drift detection.
- For information about preventing the control plane machines from rebooting after the Machine Config Operator makes changes to the machine configuration, see Disabling Machine Config Operator from automatically rebooting.
6.5. Overview of etcd
etcd is a consistent, distributed key-value store that holds small amounts of data that can fit entirely in memory. Although etcd is a core component of many projects, it is the primary data store for Kubernetes, which is the standard system for container orchestration.
6.5.1. Benefits of using etcd
By using etcd, you can benefit in several ways:
- Maintain consistent uptime for your cloud-native applications, and keep them working even if individual servers fail
- Store and replicate all cluster states for Kubernetes
- Distribute configuration data to provide redundancy and resiliency for the configuration of nodes
6.5.2. How etcd works
To ensure a reliable approach to cluster configuration and management, etcd uses the etcd Operator. The Operator simplifies the use of etcd on a Kubernetes container platform like OpenShift Container Platform. With the etcd Operator, you can create or delete etcd members, resize clusters, perform backups, and upgrade etcd.
The etcd Operator observes, analyzes, and acts:
- It observes the cluster state by using the Kubernetes API.
- It analyzes differences between the current state and the state that you want.
- It fixes the differences through the etcd cluster management APIs, the Kubernetes API, or both.
etcd holds the cluster state, which is constantly updated. This state is continuously persisted, which leads to a high number of small changes at high frequency. As a result, it is critical to back the etcd cluster member with fast, low-latency I/O. For more information about best practices for etcd, see "Recommended etcd practices".
Additional resources
6.6. Introduction to hosted control planes
You can use hosted control planes for Red Hat OpenShift Container Platform to reduce management costs, optimize cluster deployment time, and separate management and workload concerns so that you can focus on your applications.
Hosted control planes is available by using the multicluster engine for Kubernetes Operator version 2.0 or later on the following platforms:
- Bare metal by using the Agent provider
- OpenShift Virtualization
- Amazon Web Services (AWS), as a Technology Preview feature
- IBM Z, as a Technology Preview feature
- IBM Power, as a Technology Preview feature
6.6.1. Architecture of hosted control planes
OpenShift Container Platform is often deployed in a coupled, or standalone, model, where a cluster consists of a control plane and a data plane. The control plane includes an API endpoint, a storage endpoint, a workload scheduler, and an actuator that ensures state. The data plane includes compute, storage, and networking where workloads and applications run.
The standalone control plane is hosted by a dedicated group of nodes, which can be physical or virtual, with a minimum number to ensure quorum. The network stack is shared. Administrator access to a cluster offers visibility into the cluster’s control plane, machine management APIs, and other components that contribute to the state of a cluster.
Although the standalone model works well, some situations require an architecture where the control plane and data plane are decoupled. In those cases, the data plane is on a separate network domain with a dedicated physical hosting environment. The control plane is hosted by using high-level primitives such as deployments and stateful sets that are native to Kubernetes. The control plane is treated as any other workload.
![Diagram that compares the hosted control plane model against OpenShift with a coupled control plane and workers](https://access.redhat.com/webassets/avalon/d/OpenShift_Container_Platform-4.14-Architecture-en-US/images/01a511f42d82a6519a600b5c8e91724f/hosted-control-planes-diagram.png)
6.6.2. Benefits of hosted control planes
With hosted control planes for OpenShift Container Platform, you can pave the way for a true hybrid-cloud approach and enjoy several other benefits.
- The security boundaries between management and workloads are stronger because the control plane is decoupled and hosted on a dedicated hosting service cluster. As a result, you are less likely to leak credentials for clusters to other users. Because infrastructure secret account management is also decoupled, cluster infrastructure administrators cannot accidentally delete control plane infrastructure.
- With hosted control planes, you can run many control planes on fewer nodes. As a result, clusters are more affordable.
- Because the control planes consist of pods that are launched on OpenShift Container Platform, control planes start quickly. The same principles apply to control planes and workloads, such as monitoring, logging, and auto-scaling.
- From an infrastructure perspective, you can push registries, HAProxy, cluster monitoring, storage nodes, and other infrastructure components to the tenant’s cloud provider account, isolating usage to the tenant.
- From an operational perspective, multicluster management is more centralized, which results in fewer external factors that affect the cluster status and consistency. Site reliability engineers have a central place to debug issues and navigate to the cluster data plane, which can lead to shorter Time to Resolution (TTR) and greater productivity.
Additional resources
6.6.3. Glossary of common concepts and personas for hosted control planes
When you use hosted control planes for OpenShift Container Platform, it is important to understand its key concepts and the personas that are involved.
6.6.3.1. Concepts
- hosted cluster
- An OpenShift Container Platform cluster with its control plane and API endpoint hosted on a management cluster. The hosted cluster includes the control plane and its corresponding data plane.
- hosted cluster infrastructure
- Network, compute, and storage resources that exist in the tenant or end-user cloud account.
- hosted control plane
- An OpenShift Container Platform control plane that runs on the management cluster, which is exposed by the API endpoint of a hosted cluster. The components of a control plane include etcd, the Kubernetes API server, the Kubernetes controller manager, and a VPN.
- hosting cluster
- See management cluster.
- managed cluster
- A cluster that the hub cluster manages. This term is specific to the cluster lifecycle that the multicluster engine for Kubernetes Operator manages in Red Hat Advanced Cluster Management. A managed cluster is not the same thing as a management cluster. For more information, see Managed cluster.
- management cluster
- An OpenShift Container Platform cluster where the HyperShift Operator is deployed and where the control planes for hosted clusters are hosted. The management cluster is synonymous with the hosting cluster.
- management cluster infrastructure
- Network, compute, and storage resources of the management cluster.
- node pool
- A resource that contains the compute nodes. The control plane contains node pools. The compute nodes run applications and workloads.
6.6.3.2. Personas
- cluster instance administrator
-
Users who assume this role are the equivalent of administrators in standalone OpenShift Container Platform. This user has the
cluster-admin
role in the provisioned cluster, but might not have power over when or how the cluster is updated or configured. This user might have read-only access to see some configuration projected into the cluster. - cluster instance user
- Users who assume this role are the equivalent of developers in standalone OpenShift Container Platform. This user does not have a view into OperatorHub or machines.
- cluster service consumer
- Users who assume this role can request control planes and worker nodes, drive updates, or modify externalized configurations. Typically, this user does not manage or access cloud credentials or infrastructure encryption keys. The cluster service consumer persona can request hosted clusters and interact with node pools. Users who assume this role have RBAC to create, read, update, or delete hosted clusters and node pools within a logical boundary.
- cluster service provider
Users who assume this role typically have the
cluster-admin
role on the management cluster and have RBAC to monitor and own the availability of the HyperShift Operator as well as the control planes for the tenant’s hosted clusters. The cluster service provider persona is responsible for several activities, including the following examples:- Owning service-level objects for control plane availability, uptime, and stability
- Configuring the cloud account for the management cluster to host control planes
- Configuring the user-provisioned infrastructure, which includes the host awareness of available compute resources
6.6.4. Versioning for hosted control planes
With each major, minor, or patch version release of OpenShift Container Platform, two components of hosted control planes are released:
- The HyperShift Operator
-
The
hcp
command-line interface (CLI)
The HyperShift Operator manages the lifecycle of hosted clusters that are represented by the HostedCluster
API resources. The HyperShift Operator is released with each OpenShift Container Platform release. The HyperShift Operator creates the supported-versions
config map in the hypershift
namespace. The config map contains the supported hosted cluster versions.
You can host different versions of control planes on the same management cluster.
Example supported-versions
config map object
apiVersion: v1 data: supported-versions: '{"versions":["4.14"]}' kind: ConfigMap metadata: labels: hypershift.openshift.io/supported-versions: "true" name: supported-versions namespace: hypershift
You can use the hcp
CLI to create hosted clusters.
You can use the hypershift.openshift.io
API resources, such as, HostedCluster
and NodePool
, to create and manage OpenShift Container Platform clusters at scale. A HostedCluster
resource contains the control plane and common data plane configuration. When you create a HostedCluster
resource, you have a fully functional control plane with no attached nodes. A NodePool
resource is a scalable set of worker nodes that is attached to a HostedCluster
resource.
The API version policy generally aligns with the policy for Kubernetes API versioning.
Chapter 7. NVIDIA GPU architecture overview
NVIDIA supports the use of graphics processing unit (GPU) resources on OpenShift Container Platform. OpenShift Container Platform is a security-focused and hardened Kubernetes platform developed and supported by Red Hat for deploying and managing Kubernetes clusters at scale. OpenShift Container Platform includes enhancements to Kubernetes so that users can easily configure and use NVIDIA GPU resources to accelerate workloads.
The NVIDIA GPU Operator leverages the Operator framework within OpenShift Container Platform to manage the full lifecycle of NVIDIA software components required to run GPU-accelerated workloads.
These components include the NVIDIA drivers (to enable CUDA), the Kubernetes device plugin for GPUs, the NVIDIA Container Toolkit, automatic node tagging using GPU feature discovery (GFD), DCGM-based monitoring, and others.
The NVIDIA GPU Operator is only supported by NVIDIA. For more information about obtaining support from NVIDIA, see Obtaining Support from NVIDIA.
7.1. NVIDIA GPU prerequisites
- A working OpenShift cluster with at least one GPU worker node.
-
Access to the OpenShift cluster as a
cluster-admin
to perform the required steps. -
OpenShift CLI (
oc
) is installed. -
The node feature discovery (NFD) Operator is installed and a
nodefeaturediscovery
instance is created.
7.2. NVIDIA GPU enablement
The following diagram shows how the GPU architecture is enabled for OpenShift:
Figure 7.1. NVIDIA GPU enablement
![NVIDIA GPU enablement](https://access.redhat.com/webassets/avalon/d/OpenShift_Container_Platform-4.14-Architecture-en-US/images/ab8a6807e4b1b8561dd9cf7d895315fc/512_OpenShift_NVIDIA_GPU_enablement_1223.png)
MIG is only supported with A30, A100, A100X, A800, AX800, H100, and H800.
7.2.1. GPUs and bare metal
You can deploy OpenShift Container Platform on an NVIDIA-certified bare metal server but with some limitations:
- Control plane nodes can be CPU nodes.
Worker nodes must be GPU nodes, provided that AI/ML workloads are executed on these worker nodes.
In addition, the worker nodes can host one or more GPUs, but they must be of the same type. For example, a node can have two NVIDIA A100 GPUs, but a node with one A100 GPU and one T4 GPU is not supported. The NVIDIA Device Plugin for Kubernetes does not support mixing different GPU models on the same node.
- When using OpenShift, note that one or three or more servers are required. Clusters with two servers are not supported. The single server deployment is called single node openShift (SNO) and using this configuration results in a non-high availability OpenShift environment.
You can choose one of the following methods to access the containerized GPUs:
- GPU passthrough
- Multi-Instance GPU (MIG)
Additional resources
7.2.2. GPUs and virtualization
Many developers and enterprises are moving to containerized applications and serverless infrastructures, but there is still a lot of interest in developing and maintaining applications that run on virtual machines (VMs). Red Hat OpenShift Virtualization provides this capability, enabling enterprises to incorporate VMs into containerized workflows within clusters.
You can choose one of the following methods to connect the worker nodes to the GPUs:
- GPU passthrough to access and use GPU hardware within a virtual machine (VM).
- GPU (vGPU) time-slicing, when GPU compute capacity is not saturated by workloads.
Additional resources
7.2.3. GPUs and vSphere
You can deploy OpenShift Container Platform on an NVIDIA-certified VMware vSphere server that can host different GPU types.
An NVIDIA GPU driver must be installed in the hypervisor in case vGPU instances are used by the VMs. For VMware vSphere, this host driver is provided in the form of a VIB file.
The maximum number of vGPUS that can be allocated to worker node VMs depends on the version of vSphere:
- vSphere 7.0: maximum 4 vGPU per VM
vSphere 8.0: maximum 8 vGPU per VM
NotevSphere 8.0 introduced support for multiple full or fractional heterogenous profiles associated with a VM.
You can choose one of the following methods to attach the worker nodes to the GPUs:
- GPU passthrough for accessing and using GPU hardware within a virtual machine (VM)
- GPU (vGPU) time-slicing, when not all of the GPU is needed
Similar to bare metal deployments, one or three or more servers are required. Clusters with two servers are not supported.
Additional resources
7.2.4. GPUs and Red Hat KVM
You can use OpenShift Container Platform on an NVIDIA-certified kernel-based virtual machine (KVM) server.
Similar to bare-metal deployments, one or three or more servers are required. Clusters with two servers are not supported.
However, unlike bare-metal deployments, you can use different types of GPUs in the server. This is because you can assign these GPUs to different VMs that act as Kubernetes nodes. The only limitation is that a Kubernetes node must have the same set of GPU types at its own level.
You can choose one of the following methods to access the containerized GPUs:
- GPU passthrough for accessing and using GPU hardware within a virtual machine (VM)
- GPU (vGPU) time-slicing when not all of the GPU is needed
To enable the vGPU capability, a special driver must be installed at the host level. This driver is delivered as a RPM package. This host driver is not required at all for GPU passthrough allocation.
Additional resources
7.2.5. GPUs and CSPs
You can deploy OpenShift Container Platform to one of the major cloud service providers (CSPs): Amazon Web Services (AWS), Google Cloud Platform (GCP), or Microsoft Azure.
Two modes of operation are available: a fully managed deployment and a self-managed deployment.
- In a fully managed deployment, everything is automated by Red Hat in collaboration with CSP. You can request an OpenShift instance through the CSP web console, and the cluster is automatically created and fully managed by Red Hat. You do not have to worry about node failures or errors in the environment. Red Hat is fully responsible for maintaining the uptime of the cluster. The fully managed services are available on AWS and Azure. For AWS, the OpenShift service is called ROSA (Red Hat OpenShift Service on AWS). For Azure, the service is called Azure Red Hat OpenShift.
- In a self-managed deployment, you are responsible for instantiating and maintaining the OpenShift cluster. Red Hat provides the OpenShift-install utility to support the deployment of the OpenShift cluster in this case. The self-managed services are available globally to all CSPs.
It is important that this compute instance is a GPU-accelerated compute instance and that the GPU type matches the list of supported GPUs from NVIDIA AI Enterprise. For example, T4, V100, and A100 are part of this list.
You can choose one of the following methods to access the containerized GPUs:
- GPU passthrough to access and use GPU hardware within a virtual machine (VM).
- GPU (vGPU) time slicing when the entire GPU is not required.
Additional resources
7.2.6. GPUs and Red Hat Device Edge
Red Hat Device Edge provides access to MicroShift. MicroShift provides the simplicity of a single-node deployment with the functionality and services you need for resource-constrained (edge) computing. Red Hat Device Edge meets the needs of bare-metal, virtual, containerized, or Kubernetes workloads deployed in resource-constrained environments.
You can enable NVIDIA GPUs on containers in a Red Hat Device Edge environment.
You use GPU passthrough to access the containerized GPUs.
Additional resources
7.3. GPU sharing methods
Red Hat and NVIDIA have developed GPU concurrency and sharing mechanisms to simplify GPU-accelerated computing on an enterprise-level OpenShift Container Platform cluster.
Applications typically have different compute requirements that can leave GPUs underutilized. Providing the right amount of compute resources for each workload is critical to reduce deployment cost and maximize GPU utilization.
Concurrency mechanisms for improving GPU utilization exist that range from programming model APIs to system software and hardware partitioning, including virtualization. The following list shows the GPU concurrency mechanisms:
- Compute Unified Device Architecture (CUDA) streams
- Time-slicing
- CUDA Multi-Process Service (MPS)
- Multi-instance GPU (MIG)
- Virtualization with vGPU
Consider the following GPU sharing suggestions when using the GPU concurrency mechanisms for different OpenShift Container Platform scenarios:
- Bare metal
- vGPU is not available. Consider using MIG-enabled cards.
- VMs
- vGPU is the best choice.
- Older NVIDIA cards with no MIG on bare metal
- Consider using time-slicing.
- VMs with multiple GPUs and you want passthrough and vGPU
- Consider using separate VMs.
- Bare metal with OpenShift Virtualization and multiple GPUs
- Consider using pass-through for hosted VMs and time-slicing for containers.
Additional resources
7.3.1. CUDA streams
Compute Unified Device Architecture (CUDA) is a parallel computing platform and programming model developed by NVIDIA for general computing on GPUs.
A stream is a sequence of operations that executes in issue-order on the GPU. CUDA commands are typically executed sequentially in a default stream and a task does not start until a preceding task has completed.
Asynchronous processing of operations across different streams allows for parallel execution of tasks. A task issued in one stream runs before, during, or after another task is issued into another stream. This allows the GPU to run multiple tasks simultaneously in no prescribed order, leading to improved performance.
Additional resources
7.3.2. Time-slicing
GPU time-slicing interleaves workloads scheduled on overloaded GPUs when you are running multiple CUDA applications.
You can enable time-slicing of GPUs on Kubernetes by defining a set of replicas for a GPU, each of which can be independently distributed to a pod to run workloads on. Unlike multi-instance GPU (MIG), there is no memory or fault isolation between replicas, but for some workloads this is better than not sharing at all. Internally, GPU time-slicing is used to multiplex workloads from replicas of the same underlying GPU.
You can apply a cluster-wide default configuration for time-slicing. You can also apply node-specific configurations. For example, you can apply a time-slicing configuration only to nodes with Tesla T4 GPUs and not modify nodes with other GPU models.
You can combine these two approaches by applying a cluster-wide default configuration and then labeling nodes to give those nodes a node-specific configuration.
7.3.3. CUDA Multi-Process Service
CUDA Multi-Process Service (MPS) allows a single GPU to use multiple CUDA processes. The processes run in parallel on the GPU, eliminating saturation of the GPU compute resources. MPS also enables concurrent execution, or overlapping, of kernel operations and memory copying from different processes to enhance utilization.
Additional resources
7.3.4. Multi-instance GPU
Using Multi-instance GPU (MIG), you can split GPU compute units and memory into multiple MIG instances. Each of these instances represents a standalone GPU device from a system perspective and can be connected to any application, container, or virtual machine running on the node. The software that uses the GPU treats each of these MIG instances as an individual GPU.
MIG is useful when you have an application that does not require the full power of an entire GPU. The MIG feature of the new NVIDIA Ampere architecture enables you to split your hardware resources into multiple GPU instances, each of which is available to the operating system as an independent CUDA-enabled GPU.
NVIDIA GPU Operator version 1.7.0 and higher provides MIG support for the A100 and A30 Ampere cards. These GPU instances are designed to support up to seven multiple independent CUDA applications so that they operate completely isolated with dedicated hardware resources.
Additional resources
7.3.5. Virtualization with vGPU
Virtual machines (VMs) can directly access a single physical GPU using NVIDIA vGPU. You can create virtual GPUs that can be shared by VMs across the enterprise and accessed by other devices.
This capability combines the power of GPU performance with the management and security benefits provided by vGPU. Additional benefits provided by vGPU includes proactive management and monitoring for your VM environment, workload balancing for mixed VDI and compute workloads, and resource sharing across multiple VMs.
Additional resources
7.4. NVIDIA GPU features for OpenShift Container Platform
- NVIDIA Container Toolkit
- NVIDIA Container Toolkit enables you to create and run GPU-accelerated containers. The toolkit includes a container runtime library and utilities to automatically configure containers to use NVIDIA GPUs.
- NVIDIA AI Enterprise
NVIDIA AI Enterprise is an end-to-end, cloud-native suite of AI and data analytics software optimized, certified, and supported with NVIDIA-Certified systems.
NVIDIA AI Enterprise includes support for Red Hat OpenShift Container Platform. The following installation methods are supported:
- OpenShift Container Platform on bare metal or VMware vSphere with GPU Passthrough.
- OpenShift Container Platform on VMware vSphere with NVIDIA vGPU.
- GPU Feature Discovery
NVIDIA GPU Feature Discovery for Kubernetes is a software component that enables you to automatically generate labels for the GPUs available on a node. GPU Feature Discovery uses node feature discovery (NFD) to perform this labeling.
The Node Feature Discovery Operator (NFD) manages the discovery of hardware features and configurations in an OpenShift Container Platform cluster by labeling nodes with hardware-specific information. NFD labels the host with node-specific attributes, such as PCI cards, kernel, OS version, and so on.
You can find the NFD Operator in the Operator Hub by searching for “Node Feature Discovery”.
- NVIDIA GPU Operator with OpenShift Virtualization
Up until this point, the GPU Operator only provisioned worker nodes to run GPU-accelerated containers. Now, the GPU Operator can also be used to provision worker nodes for running GPU-accelerated virtual machines (VMs).
You can configure the GPU Operator to deploy different software components to worker nodes depending on which GPU workload is configured to run on those nodes.
- GPU Monitoring dashboard
- You can install a monitoring dashboard to display GPU usage information on the cluster Observe page in the OpenShift Container Platform web console. GPU utilization information includes the number of available GPUs, power consumption (in watts), temperature (in degrees Celsius), utilization (in percent), and other metrics for each GPU.
Additional resources
Chapter 8. Understanding OpenShift Container Platform development
To fully leverage the capability of containers when developing and running enterprise-quality applications, ensure your environment is supported by tools that allow containers to be:
- Created as discrete microservices that can be connected to other containerized, and non-containerized, services. For example, you might want to join your application with a database or attach a monitoring application to it.
- Resilient, so if a server crashes or needs to go down for maintenance or to be decommissioned, containers can start on another machine.
- Automated to pick up code changes automatically and then start and deploy new versions of themselves.
- Scaled up, or replicated, to have more instances serving clients as demand increases and then spun down to fewer instances as demand declines.
- Run in different ways, depending on the type of application. For example, one application might run once a month to produce a report and then exit. Another application might need to run constantly and be highly available to clients.
- Managed so you can watch the state of your application and react when something goes wrong.
Containers’ widespread acceptance, and the resulting requirements for tools and methods to make them enterprise-ready, resulted in many options for them.
The rest of this section explains options for assets you can create when you build and deploy containerized Kubernetes applications in OpenShift Container Platform. It also describes which approaches you might use for different kinds of applications and development requirements.
8.1. About developing containerized applications
You can approach application development with containers in many ways, and different approaches might be more appropriate for different situations. To illustrate some of this variety, the series of approaches that is presented starts with developing a single container and ultimately deploys that container as a mission-critical application for a large enterprise. These approaches show different tools, formats, and methods that you can employ with containerized application development. This topic describes:
- Building a simple container and storing it in a registry
- Creating a Kubernetes manifest and saving it to a Git repository
- Making an Operator to share your application with others
8.2. Building a simple container
You have an idea for an application and you want to containerize it.
First you require a tool for building a container, like buildah or docker, and a file that describes what goes in your container, which is typically a Dockerfile.
Next, you require a location to push the resulting container image so you can pull it to run anywhere you want it to run. This location is a container registry.
Some examples of each of these components are installed by default on most Linux operating systems, except for the Dockerfile, which you provide yourself.
The following diagram displays the process of building and pushing an image:
Figure 8.1. Create a simple containerized application and push it to a registry
![Creating and pushing a containerized application](https://access.redhat.com/webassets/avalon/d/OpenShift_Container_Platform-4.14-Architecture-en-US/images/7cb0013c7080c715e106f482eab98065/create-push-app.png)
If you use a computer that runs Red Hat Enterprise Linux (RHEL) as the operating system, the process of creating a containerized application requires the following steps:
- Install container build tools: RHEL contains a set of tools that includes podman, buildah, and skopeo that you use to build and manage containers.
-
Create a Dockerfile to combine base image and software: Information about building your container goes into a file that is named
Dockerfile
. In that file, you identify the base image you build from, the software packages you install, and the software you copy into the container. You also identify parameter values like network ports that you expose outside the container and volumes that you mount inside the container. Put your Dockerfile and the software you want to containerize in a directory on your RHEL system. -
Run buildah or docker build: Run the
buildah build-using-dockerfile
or thedocker build
command to pull your chosen base image to the local system and create a container image that is stored locally. You can also build container images without a Dockerfile by using buildah. -
Tag and push to a registry: Add a tag to your new container image that identifies the location of the registry in which you want to store and share your container. Then push that image to the registry by running the
podman push
ordocker push
command. -
Pull and run the image: From any system that has a container client tool, such as podman or docker, run a command that identifies your new image. For example, run the
podman run <image_name>
ordocker run <image_name>
command. Here<image_name>
is the name of your new container image, which resemblesquay.io/myrepo/myapp:latest
. The registry might require credentials to push and pull images.
For more details on the process of building container images, pushing them to registries, and running them, see Custom image builds with Buildah.
8.2.1. Container build tool options
Building and managing containers with buildah, podman, and skopeo results in industry standard container images that include features specifically tuned for deploying containers in OpenShift Container Platform or other Kubernetes environments. These tools are daemonless and can run without root privileges, requiring less overhead to run them.
Support for Docker Container Engine as a container runtime is deprecated in Kubernetes 1.20 and will be removed in a future release. However, Docker-produced images will continue to work in your cluster with all runtimes, including CRI-O. For more information, see the Kubernetes blog announcement.
When you ultimately run your containers in OpenShift Container Platform, you use the CRI-O container engine. CRI-O runs on every worker and control plane machine in an OpenShift Container Platform cluster, but CRI-O is not yet supported as a standalone runtime outside of OpenShift Container Platform.
8.2.2. Base image options
The base image you choose to build your application on contains a set of software that resembles a Linux system to your application. When you build your own image, your software is placed into that file system and sees that file system as though it were looking at its operating system. Choosing this base image has major impact on how secure, efficient and upgradeable your container is in the future.
Red Hat provides a new set of base images referred to as Red Hat Universal Base Images (UBI). These images are based on Red Hat Enterprise Linux and are similar to base images that Red Hat has offered in the past, with one major difference: they are freely redistributable without a Red Hat subscription. As a result, you can build your application on UBI images without having to worry about how they are shared or the need to create different images for different environments.
These UBI images have standard, init, and minimal versions. You can also use the Red Hat Software Collections images as a foundation for applications that rely on specific runtime environments such as Node.js, Perl, or Python. Special versions of some of these runtime base images are referred to as Source-to-Image (S2I) images. With S2I images, you can insert your code into a base image environment that is ready to run that code.
S2I images are available for you to use directly from the OpenShift Container Platform web UI by selecting Catalog → Developer Catalog, as shown in the following figure:
Figure 8.2. Choose S2I base images for apps that need specific runtimes
![OpenShift Container Platform Developer Catalog](https://access.redhat.com/webassets/avalon/d/OpenShift_Container_Platform-4.14-Architecture-en-US/images/00242b6bd7400233a557430439035bc1/developer-catalog.png)
8.2.3. Registry options
Container registries are where you store container images so you can share them with others and make them available to the platform where they ultimately run. You can select large, public container registries that offer free accounts or a premium version that offer more storage and special features. You can also install your own registry that can be exclusive to your organization or selectively shared with others.
To get Red Hat images and certified partner images, you can draw from the Red Hat Registry. The Red Hat Registry is represented by two locations: registry.access.redhat.com
, which is unauthenticated and deprecated, and registry.redhat.io
, which requires authentication. You can learn about the Red Hat and partner images in the Red Hat Registry from the Container images section of the Red Hat Ecosystem Catalog. Besides listing Red Hat container images, it also shows extensive information about the contents and quality of those images, including health scores that are based on applied security updates.
Large, public registries include Docker Hub and Quay.io. The Quay.io registry is owned and managed by Red Hat. Many of the components used in OpenShift Container Platform are stored in Quay.io, including container images and the Operators that are used to deploy OpenShift Container Platform itself. Quay.io also offers the means of storing other types of content, including Helm charts.
If you want your own, private container registry, OpenShift Container Platform itself includes a private container registry that is installed with OpenShift Container Platform and runs on its cluster. Red Hat also offers a private version of the Quay.io registry called Red Hat Quay. Red Hat Quay includes geo replication, Git build triggers, Clair image scanning, and many other features.
All of the registries mentioned here can require credentials to download images from those registries. Some of those credentials are presented on a cluster-wide basis from OpenShift Container Platform, while other credentials can be assigned to individuals.
8.3. Creating a Kubernetes manifest for OpenShift Container Platform
While the container image is the basic building block for a containerized application, more information is required to manage and deploy that application in a Kubernetes environment such as OpenShift Container Platform. The typical next steps after you create an image are to:
- Understand the different resources you work with in Kubernetes manifests
- Make some decisions about what kind of an application you are running
- Gather supporting components
- Create a manifest and store that manifest in a Git repository so you can store it in a source versioning system, audit it, track it, promote and deploy it to the next environment, roll it back to earlier versions, if necessary, and share it with others
8.3.1. About Kubernetes pods and services
While the container image is the basic unit with docker, the basic units that Kubernetes works with are called pods. Pods represent the next step in building out an application. A pod can contain one or more than one container. The key is that the pod is the single unit that you deploy, scale, and manage.
Scalability and namespaces are probably the main items to consider when determining what goes in a pod. For ease of deployment, you might want to deploy a container in a pod and include its own logging and monitoring container in the pod. Later, when you run the pod and need to scale up an additional instance, those other containers are scaled up with it. For namespaces, containers in a pod share the same network interfaces, shared storage volumes, and resource limitations, such as memory and CPU, which makes it easier to manage the contents of the pod as a single unit. Containers in a pod can also communicate with each other by using standard inter-process communications, such as System V semaphores or POSIX shared memory.
While individual pods represent a scalable unit in Kubernetes, a service provides a means of grouping together a set of pods to create a complete, stable application that can complete tasks such as load balancing. A service is also more permanent than a pod because the service remains available from the same IP address until you delete it. When the service is in use, it is requested by name and the OpenShift Container Platform cluster resolves that name into the IP addresses and ports where you can reach the pods that compose the service.
By their nature, containerized applications are separated from the operating systems where they run and, by extension, their users. Part of your Kubernetes manifest describes how to expose the application to internal and external networks by defining network policies that allow fine-grained control over communication with your containerized applications. To connect incoming requests for HTTP, HTTPS, and other services from outside your cluster to services inside your cluster, you can use an Ingress
resource.
If your container requires on-disk storage instead of database storage, which might be provided through a service, you can add volumes to your manifests to make that storage available to your pods. You can configure the manifests to create persistent volumes (PVs) or dynamically create volumes that are added to your Pod
definitions.
After you define a group of pods that compose your application, you can define those pods in Deployment
and DeploymentConfig
objects.
8.3.2. Application types
Next, consider how your application type influences how to run it.
Kubernetes defines different types of workloads that are appropriate for different kinds of applications. To determine the appropriate workload for your application, consider if the application is:
-
Meant to run to completion and be done. An example is an application that starts up to produce a report and exits when the report is complete. The application might not run again then for a month. Suitable OpenShift Container Platform objects for these types of applications include
Job
andCronJob
objects. - Expected to run continuously. For long-running applications, you can write a deployment.
-
Required to be highly available. If your application requires high availability, then you want to size your deployment to have more than one instance. A
Deployment
orDeploymentConfig
object can incorporate a replica set for that type of application. With replica sets, pods run across multiple nodes to make sure the application is always available, even if a worker goes down. - Need to run on every node. Some types of Kubernetes applications are intended to run in the cluster itself on every master or worker node. DNS and monitoring applications are examples of applications that need to run continuously on every node. You can run this type of application as a daemon set. You can also run a daemon set on a subset of nodes, based on node labels.
- Require life-cycle management. When you want to hand off your application so that others can use it, consider creating an Operator. Operators let you build in intelligence, so it can handle things like backups and upgrades automatically. Coupled with the Operator Lifecycle Manager (OLM), cluster managers can expose Operators to selected namespaces so that users in the cluster can run them.
-
Have identity or numbering requirements. An application might have identity requirements or numbering requirements. For example, you might be required to run exactly three instances of the application and to name the instances
0
,1
, and2
. A stateful set is suitable for this application. Stateful sets are most useful for applications that require independent storage, such as databases and zookeeper clusters.
8.3.3. Available supporting components
The application you write might need supporting components, like a database or a logging component. To fulfill that need, you might be able to obtain the required component from the following Catalogs that are available in the OpenShift Container Platform web console:
- OperatorHub, which is available in each OpenShift Container Platform 4.14 cluster. The OperatorHub makes Operators available from Red Hat, certified Red Hat partners, and community members to the cluster operator. The cluster operator can make those Operators available in all or selected namespaces in the cluster, so developers can launch them and configure them with their applications.
-
Templates, which are useful for a one-off type of application, where the lifecycle of a component is not important after it is installed. A template provides an easy way to get started developing a Kubernetes application with minimal overhead. A template can be a list of resource definitions, which could be
Deployment
,Service
,Route
, or other objects. If you want to change names or resources, you can set these values as parameters in the template.
You can configure the supporting Operators and templates to the specific needs of your development team and then make them available in the namespaces in which your developers work. Many people add shared templates to the openshift
namespace because it is accessible from all other namespaces.
8.3.4. Applying the manifest
Kubernetes manifests let you create a more complete picture of the components that make up your Kubernetes applications. You write these manifests as YAML files and deploy them by applying them to the cluster, for example, by running the oc apply
command.
8.3.5. Next steps
At this point, consider ways to automate your container development process. Ideally, you have some sort of CI pipeline that builds the images and pushes them to a registry. In particular, a GitOps pipeline integrates your container development with the Git repositories that you use to store the software that is required to build your applications.
The workflow to this point might look like:
-
Day 1: You write some YAML. You then run the
oc apply
command to apply that YAML to the cluster and test that it works. - Day 2: You put your YAML container configuration file into your own Git repository. From there, people who want to install that app, or help you improve it, can pull down the YAML and apply it to their cluster to run the app.
- Day 3: Consider writing an Operator for your application.
8.4. Develop for Operators
Packaging and deploying your application as an Operator might be preferred if you make your application available for others to run. As noted earlier, Operators add a lifecycle component to your application that acknowledges that the job of running an application is not complete as soon as it is installed.
When you create an application as an Operator, you can build in your own knowledge of how to run and maintain the application. You can build in features for upgrading the application, backing it up, scaling it, or keeping track of its state. If you configure the application correctly, maintenance tasks, like updating the Operator, can happen automatically and invisibly to the Operator’s users.
An example of a useful Operator is one that is set up to automatically back up data at particular times. Having an Operator manage an application’s backup at set times can save a system administrator from remembering to do it.
Any application maintenance that has traditionally been completed manually, like backing up data or rotating certificates, can be completed automatically with an Operator.
Chapter 9. Red Hat Enterprise Linux CoreOS (RHCOS)
9.1. About RHCOS
Red Hat Enterprise Linux CoreOS (RHCOS) represents the next generation of single-purpose container operating system technology by providing the quality standards of Red Hat Enterprise Linux (RHEL) with automated, remote upgrade features.
RHCOS is supported only as a component of OpenShift Container Platform 4.14 for all OpenShift Container Platform machines. RHCOS is the only supported operating system for OpenShift Container Platform control plane, or master, machines. While RHCOS is the default operating system for all cluster machines, you can create compute machines, which are also known as worker machines, that use RHEL as their operating system. There are two general ways RHCOS is deployed in OpenShift Container Platform 4.14:
- If you install your cluster on infrastructure that the installation program provisions, RHCOS images are downloaded to the target platform during installation. Suitable Ignition config files, which control the RHCOS configuration, are also downloaded and used to deploy the machines.
- If you install your cluster on infrastructure that you manage, you must follow the installation documentation to obtain the RHCOS images, generate Ignition config files, and use the Ignition config files to provision your machines.
9.1.1. Key RHCOS features
The following list describes key features of the RHCOS operating system:
- Based on RHEL: The underlying operating system consists primarily of RHEL components. The same quality, security, and control measures that support RHEL also support RHCOS. For example, RHCOS software is in RPM packages, and each RHCOS system starts up with a RHEL kernel and a set of services that are managed by the systemd init system.
- Controlled immutability: Although it contains RHEL components, RHCOS is designed to be managed more tightly than a default RHEL installation. Management is performed remotely from the OpenShift Container Platform cluster. When you set up your RHCOS machines, you can modify only a few system settings. This controlled immutability allows OpenShift Container Platform to store the latest state of RHCOS systems in the cluster so it is always able to create additional machines and perform updates based on the latest RHCOS configurations.
CRI-O container runtime: Although RHCOS contains features for running the OCI- and libcontainer-formatted containers that Docker requires, it incorporates the CRI-O container engine instead of the Docker container engine. By focusing on features needed by Kubernetes platforms, such as OpenShift Container Platform, CRI-O can offer specific compatibility with different Kubernetes versions. CRI-O also offers a smaller footprint and reduced attack surface than is possible with container engines that offer a larger feature set. At the moment, CRI-O is the only engine available within OpenShift Container Platform clusters.
CRI-O can use either the runC or crun container runtime to start and manage containers. For information about how to enable crun, see the documentation for creating a
ContainerRuntimeConfig
CR.-
Set of container tools: For tasks such as building, copying, and otherwise managing containers, RHCOS replaces the Docker CLI tool with a compatible set of container tools. The podman CLI tool supports many container runtime features, such as running, starting, stopping, listing, and removing containers and container images. The skopeo CLI tool can copy, authenticate, and sign images. You can use the
crictl
CLI tool to work with containers and pods from the CRI-O container engine. While direct use of these tools in RHCOS is discouraged, you can use them for debugging purposes. -
rpm-ostree upgrades: RHCOS features transactional upgrades using the
rpm-ostree
system. Updates are delivered by means of container images and are part of the OpenShift Container Platform update process. When deployed, the container image is pulled, extracted, and written to disk, then the bootloader is modified to boot into the new version. The machine will reboot into the update in a rolling manner to ensure cluster capacity is minimally impacted. bootupd firmware and bootloader updater: Package managers and hybrid systems such as
rpm-ostree
do not update the firmware or the bootloader. Withbootupd
, RHCOS users have access to a cross-distribution, system-agnostic update tool that manages firmware and boot updates in UEFI and legacy BIOS boot modes that run on modern architectures, such as x86_64, ppc64le, and aarch64.For information about how to install
bootupd
, see the documentation for Updating the bootloader using bootupd.-
Updated through the Machine Config Operator: In OpenShift Container Platform, the Machine Config Operator handles operating system upgrades. Instead of upgrading individual packages, as is done with
yum
upgrades,rpm-ostree
delivers upgrades of the OS as an atomic unit. The new OS deployment is staged during upgrades and goes into effect on the next reboot. If something goes wrong with the upgrade, a single rollback and reboot returns the system to the previous state. RHCOS upgrades in OpenShift Container Platform are performed during cluster updates.
For RHCOS systems, the layout of the rpm-ostree
file system has the following characteristics:
-
/usr
is where the operating system binaries and libraries are stored and is read-only. We do not support altering this. -
/etc
,/boot
,/var
are writable on the system but only intended to be altered by the Machine Config Operator. -
/var/lib/containers
is the graph storage location for storing container images.
9.1.2. Choosing how to configure RHCOS
RHCOS is designed to deploy on an OpenShift Container Platform cluster with a minimal amount of user configuration. In its most basic form, this consists of:
- Starting with a provisioned infrastructure, such as on AWS, or provisioning the infrastructure yourself.
-
Supplying a few pieces of information, such as credentials and cluster name, in an
install-config.yaml
file when runningopenshift-install
.
Because RHCOS systems in OpenShift Container Platform are designed to be fully managed from the OpenShift Container Platform cluster after that, directly changing an RHCOS machine is discouraged. Although limited direct access to RHCOS machines cluster can be accomplished for debugging purposes, you should not directly configure RHCOS systems. Instead, if you need to add or change features on your OpenShift Container Platform nodes, consider making changes in the following ways:
- Kubernetes workload objects, such as DaemonSet and Deployment: If you need to add services or other user-level features to your cluster, consider adding them as Kubernetes workload objects. Keeping those features outside of specific node configurations is the best way to reduce the risk of breaking the cluster on subsequent upgrades.
- Day-2 customizations: If possible, bring up a cluster without making any customizations to cluster nodes and make necessary node changes after the cluster is up. Those changes are easier to track later and less likely to break updates. Creating machine configs or modifying Operator custom resources are ways of making these customizations.
-
Day-1 customizations: For customizations that you must implement when the cluster first comes up, there are ways of modifying your cluster so changes are implemented on first boot. Day-1 customizations can be done through Ignition configs and manifest files during
openshift-install
or by adding boot options during ISO installs provisioned by the user.
Here are examples of customizations you could do on day 1:
- Kernel arguments: If particular kernel features or tuning is needed on nodes when the cluster first boots.
- Disk encryption: If your security needs require that the root file system on the nodes are encrypted, such as with FIPS support.
- Kernel modules: If a particular hardware device, such as a network card or video card, does not have a usable module available by default in the Linux kernel.
- Chronyd: If you want to provide specific clock settings to your nodes, such as the location of time servers.
To accomplish these tasks, you can augment the openshift-install
process to include additional objects such as MachineConfig
objects. Those procedures that result in creating machine configs can be passed to the Machine Config Operator after the cluster is up.
-
The Ignition config files that the installation program generates contain certificates that expire after 24 hours, which are then renewed at that time. If the cluster is shut down before renewing the certificates and the cluster is later restarted after the 24 hours have elapsed, the cluster automatically recovers the expired certificates. The exception is that you must manually approve the pending
node-bootstrapper
certificate signing requests (CSRs) to recover kubelet certificates. See the documentation for Recovering from expired control plane certificates for more information. - It is recommended that you use Ignition config files within 12 hours after they are generated because the 24-hour certificate rotates from 16 to 22 hours after the cluster is installed. By using the Ignition config files within 12 hours, you can avoid installation failure if the certificate update runs during installation.
9.1.3. Choosing how to deploy RHCOS
Differences between RHCOS installations for OpenShift Container Platform are based on whether you are deploying on an infrastructure provisioned by the installer or by the user:
- Installer-provisioned: Some cloud environments offer preconfigured infrastructures that allow you to bring up an OpenShift Container Platform cluster with minimal configuration. For these types of installations, you can supply Ignition configs that place content on each node so it is there when the cluster first boots.
- User-provisioned: If you are provisioning your own infrastructure, you have more flexibility in how you add content to a RHCOS node. For example, you could add kernel arguments when you boot the RHCOS ISO installer to install each system. However, in most cases where configuration is required on the operating system itself, it is best to provide that configuration through an Ignition config.
The Ignition facility runs only when the RHCOS system is first set up. After that, Ignition configs can be supplied later using the machine config.
9.1.4. About Ignition
Ignition is the utility that is used by RHCOS to manipulate disks during initial configuration. It completes common disk tasks, including partitioning disks, formatting partitions, writing files, and configuring users. On first boot, Ignition reads its configuration from the installation media or the location that you specify and applies the configuration to the machines.
Whether you are installing your cluster or adding machines to it, Ignition always performs the initial configuration of the OpenShift Container Platform cluster machines. Most of the actual system setup happens on each machine itself. For each machine, Ignition takes the RHCOS image and boots the RHCOS kernel. Options on the kernel command line identify the type of deployment and the location of the Ignition-enabled initial RAM disk (initramfs).
9.1.4.1. How Ignition works
To create machines by using Ignition, you need Ignition config files. The OpenShift Container Platform installation program creates the Ignition config files that you need to deploy your cluster. These files are based on the information that you provide to the installation program directly or through an install-config.yaml
file.
The way that Ignition configures machines is similar to how tools like cloud-init or Linux Anaconda kickstart configure systems, but with some important differences:
- Ignition runs from an initial RAM disk that is separate from the system you are installing to. Because of that, Ignition can repartition disks, set up file systems, and perform other changes to the machine’s permanent file system. In contrast, cloud-init runs as part of a machine init system when the system boots, so making foundational changes to things like disk partitions cannot be done as easily. With cloud-init, it is also difficult to reconfigure the boot process while you are in the middle of the node boot process.
- Ignition is meant to initialize systems, not change existing systems. After a machine initializes and the kernel is running from the installed system, the Machine Config Operator from the OpenShift Container Platform cluster completes all future machine configuration.
- Instead of completing a defined set of actions, Ignition implements a declarative configuration. It checks that all partitions, files, services, and other items are in place before the new machine starts. It then makes the changes, like copying files to disk that are necessary for the new machine to meet the specified configuration.
- After Ignition finishes configuring a machine, the kernel keeps running but discards the initial RAM disk and pivots to the installed system on disk. All of the new system services and other features start without requiring a system reboot.
- Because Ignition confirms that all new machines meet the declared configuration, you cannot have a partially configured machine. If a machine setup fails, the initialization process does not finish, and Ignition does not start the new machine. Your cluster will never contain partially configured machines. If Ignition cannot complete, the machine is not added to the cluster. You must add a new machine instead. This behavior prevents the difficult case of debugging a machine when the results of a failed configuration task are not known until something that depended on it fails at a later date.
- If there is a problem with an Ignition config that causes the setup of a machine to fail, Ignition will not try to use the same config to set up another machine. For example, a failure could result from an Ignition config made up of a parent and child config that both want to create the same file. A failure in such a case would prevent that Ignition config from being used again to set up an other machines until the problem is resolved.
- If you have multiple Ignition config files, you get a union of that set of configs. Because Ignition is declarative, conflicts between the configs could cause Ignition to fail to set up the machine. The order of information in those files does not matter. Ignition will sort and implement each setting in ways that make the most sense. For example, if a file needs a directory several levels deep, if another file needs a directory along that path, the later file is created first. Ignition sorts and creates all files, directories, and links by depth.
- Because Ignition can start with a completely empty hard disk, it can do something cloud-init cannot do: set up systems on bare metal from scratch using features such as PXE boot. In the bare metal case, the Ignition config is injected into the boot partition so that Ignition can find it and configure the system correctly.
9.1.4.2. The Ignition sequence
The Ignition process for an RHCOS machine in an OpenShift Container Platform cluster involves the following steps:
- The machine gets its Ignition config file. Control plane machines get their Ignition config files from the bootstrap machine, and worker machines get Ignition config files from a control plane machine.
- Ignition creates disk partitions, file systems, directories, and links on the machine. It supports RAID arrays but does not support LVM volumes.
-
Ignition mounts the root of the permanent file system to the
/sysroot
directory in the initramfs and starts working in that/sysroot
directory. - Ignition configures all defined file systems and sets them up to mount appropriately at runtime.
-
Ignition runs
systemd
temporary files to populate required files in the/var
directory. - Ignition runs the Ignition config files to set up users, systemd unit files, and other configuration files.
- Ignition unmounts all components in the permanent system that were mounted in the initramfs.
- Ignition starts up the init process of the new machine, which in turn starts up all other services on the machine that run during system boot.
At the end of this process, the machine is ready to join the cluster and does not require a reboot.
9.2. Viewing Ignition configuration files
To see the Ignition config file used to deploy the bootstrap machine, run the following command:
$ openshift-install create ignition-configs --dir $HOME/testconfig
After you answer a few questions, the bootstrap.ign
, master.ign
, and worker.ign
files appear in the directory you entered.
To see the contents of the bootstrap.ign
file, pipe it through the jq
filter. Here’s a snippet from that file:
$ cat $HOME/testconfig/bootstrap.ign | jq { "ignition": { "version": "3.2.0" }, "passwd": { "users": [ { "name": "core", "sshAuthorizedKeys": [ "ssh-rsa AAAAB3NzaC1yc...." ] } ] }, "storage": { "files": [ { "overwrite": false, "path": "/etc/motd", "user": { "name": "root" }, "append": [ { "source": "data:text/plain;charset=utf-8;base64,VGhpcyBpcyB0aGUgYm9vdHN0cmFwIG5vZGU7IGl0IHdpbGwgYmUgZGVzdHJveWVkIHdoZW4gdGhlIG1hc3RlciBpcyBmdWxseSB1cC4KClRoZSBwcmltYXJ5IHNlcnZpY2VzIGFyZSByZWxlYXNlLWltYWdlLnNlcnZpY2UgZm9sbG93ZWQgYnkgYm9vdGt1YmUuc2VydmljZS4gVG8gd2F0Y2ggdGhlaXIgc3RhdHVzLCBydW4gZS5nLgoKICBqb3VybmFsY3RsIC1iIC1mIC11IHJlbGVhc2UtaW1hZ2Uuc2VydmljZSAtdSBib290a3ViZS5zZXJ2aWNlCg==" } ], "mode": 420 }, ...
To decode the contents of a file listed in the bootstrap.ign
file, pipe the base64-encoded data string representing the contents of that file to the base64 -d
command. Here’s an example using the contents of the /etc/motd
file added to the bootstrap machine from the output shown above:
$ echo VGhpcyBpcyB0aGUgYm9vdHN0cmFwIG5vZGU7IGl0IHdpbGwgYmUgZGVzdHJveWVkIHdoZW4gdGhlIG1hc3RlciBpcyBmdWxseSB1cC4KClRoZSBwcmltYXJ5IHNlcnZpY2VzIGFyZSByZWxlYXNlLWltYWdlLnNlcnZpY2UgZm9sbG93ZWQgYnkgYm9vdGt1YmUuc2VydmljZS4gVG8gd2F0Y2ggdGhlaXIgc3RhdHVzLCBydW4gZS5nLgoKICBqb3VybmFsY3RsIC1iIC1mIC11IHJlbGVhc2UtaW1hZ2Uuc2VydmljZSAtdSBib290a3ViZS5zZXJ2aWNlCg== | base64 --decode
Example output
This is the bootstrap node; it will be destroyed when the master is fully up. The primary services are release-image.service followed by bootkube.service. To watch their status, run e.g. journalctl -b -f -u release-image.service -u bootkube.service
Repeat those commands on the master.ign
and worker.ign
files to see the source of Ignition config files for each of those machine types. You should see a line like the following for the worker.ign
, identifying how it gets its Ignition config from the bootstrap machine:
"source": "https://api.myign.develcluster.example.com:22623/config/worker",
Here are a few things you can learn from the bootstrap.ign
file:
- Format: The format of the file is defined in the Ignition config spec. Files of the same format are used later by the MCO to merge changes into a machine’s configuration.
-
Contents: Because the bootstrap machine serves the Ignition configs for other machines, both master and worker machine Ignition config information is stored in the
bootstrap.ign
, along with the bootstrap machine’s configuration. - Size: The file is more than 1300 lines long, with path to various types of resources.
-
The content of each file that will be copied to the machine is actually encoded into data URLs, which tends to make the content a bit clumsy to read. (Use the
jq
andbase64
commands shown previously to make the content more readable.) - Configuration: The different sections of the Ignition config file are generally meant to contain files that are just dropped into a machine’s file system, rather than commands to modify existing files. For example, instead of having a section on NFS that configures that service, you would just add an NFS configuration file, which would then be started by the init process when the system comes up.
-
users: A user named
core
is created, with your SSH key assigned to that user. This allows you to log in to the cluster with that user name and your credentials. -
storage: The storage section identifies files that are added to each machine. A few notable files include
/root/.docker/config.json
(which provides credentials your cluster needs to pull from container image registries) and a bunch of manifest files in/opt/openshift/manifests
that are used to configure your cluster. -
systemd: The
systemd
section holds content used to createsystemd
unit files. Those files are used to start up services at boot time, as well as manage those services on running systems. - Primitives: Ignition also exposes low-level primitives that other tools can build on.
9.3. Changing Ignition configs after installation
Machine config pools manage a cluster of nodes and their corresponding machine configs. Machine configs contain configuration information for a cluster. To list all machine config pools that are known:
$ oc get machineconfigpools
Example output
NAME CONFIG UPDATED UPDATING DEGRADED master master-1638c1aea398413bb918e76632f20799 False False False worker worker-2feef4f8288936489a5a832ca8efe953 False False False
To list all machine configs:
$ oc get machineconfig
Example output
NAME GENERATEDBYCONTROLLER IGNITIONVERSION CREATED OSIMAGEURL 00-master 4.0.0-0.150.0.0-dirty 3.2.0 16m 00-master-ssh 4.0.0-0.150.0.0-dirty 16m 00-worker 4.0.0-0.150.0.0-dirty 3.2.0 16m 00-worker-ssh 4.0.0-0.150.0.0-dirty 16m 01-master-kubelet 4.0.0-0.150.0.0-dirty 3.2.0 16m 01-worker-kubelet 4.0.0-0.150.0.0-dirty 3.2.0 16m master-1638c1aea398413bb918e76632f20799 4.0.0-0.150.0.0-dirty 3.2.0 16m worker-2feef4f8288936489a5a832ca8efe953 4.0.0-0.150.0.0-dirty 3.2.0 16m
The Machine Config Operator acts somewhat differently than Ignition when it comes to applying these machine configs. The machine configs are read in order (from 00* to 99*). Labels inside the machine configs identify the type of node each is for (master or worker). If the same file appears in multiple machine config files, the last one wins. So, for example, any file that appears in a 99* file would replace the same file that appeared in a 00* file. The input MachineConfig
objects are unioned into a "rendered" MachineConfig
object, which will be used as a target by the operator and is the value you can see in the machine config pool.
To see what files are being managed from a machine config, look for "Path:" inside a particular MachineConfig
object. For example:
$ oc describe machineconfigs 01-worker-container-runtime | grep Path:
Example output
Path: /etc/containers/registries.conf Path: /etc/containers/storage.conf Path: /etc/crio/crio.conf
Be sure to give the machine config file a later name (such as 10-worker-container-runtime). Keep in mind that the content of each file is in URL-style data. Then apply the new machine config to the cluster.
Chapter 10. Admission plugins
Admission plugins are used to help regulate how OpenShift Container Platform functions.
10.1. About admission plugins
Admission plugins intercept requests to the master API to validate resource requests. After a request is authenticated and authorized, the admission plugins ensure that any associated policies are followed. For example, they are commonly used to enforce security policy, resource limitations or configuration requirements.
Admission plugins run in sequence as an admission chain. If any admission plugin in the sequence rejects a request, the whole chain is aborted and an error is returned.
OpenShift Container Platform has a default set of admission plugins enabled for each resource type. These are required for proper functioning of the cluster. Admission plugins ignore resources that they are not responsible for.
In addition to the defaults, the admission chain can be extended dynamically through webhook admission plugins that call out to custom webhook servers. There are two types of webhook admission plugins: a mutating admission plugin and a validating admission plugin. The mutating admission plugin runs first and can both modify resources and validate requests. The validating admission plugin validates requests and runs after the mutating admission plugin so that modifications triggered by the mutating admission plugin can also be validated.
Calling webhook servers through a mutating admission plugin can produce side effects on resources related to the target object. In such situations, you must take steps to validate that the end result is as expected.
Dynamic admission should be used cautiously because it impacts cluster control plane operations. When calling webhook servers through webhook admission plugins in OpenShift Container Platform 4.14, ensure that you have read the documentation fully and tested for side effects of mutations. Include steps to restore resources back to their original state prior to mutation, in the event that a request does not pass through the entire admission chain.
10.2. Default admission plugins
Default validating and admission plugins are enabled in OpenShift Container Platform 4.14. These default plugins contribute to fundamental control plane functionality, such as ingress policy, cluster resource limit override and quota policy.
Do not run workloads in or share access to default projects. Default projects are reserved for running core cluster components.
The following default projects are considered highly privileged: default
, kube-public
, kube-system
, openshift
, openshift-infra
, openshift-node
, and other system-created projects that have the openshift.io/run-level
label set to 0
or 1
. Functionality that relies on admission plugins, such as pod security admission, security context constraints, cluster resource quotas, and image reference resolution, does not work in highly privileged projects.
The following lists contain the default admission plugins:
Example 10.1. Validating admission plugins
-
LimitRanger
-
ServiceAccount
-
PodNodeSelector
-
Priority
-
PodTolerationRestriction
-
OwnerReferencesPermissionEnforcement
-
PersistentVolumeClaimResize
-
RuntimeClass
-
CertificateApproval
-
CertificateSigning
-
CertificateSubjectRestriction
-
autoscaling.openshift.io/ManagementCPUsOverride
-
authorization.openshift.io/RestrictSubjectBindings
-
scheduling.openshift.io/OriginPodNodeEnvironment
-
network.openshift.io/ExternalIPRanger
-
network.openshift.io/RestrictedEndpointsAdmission
-
image.openshift.io/ImagePolicy
-
security.openshift.io/SecurityContextConstraint
-
security.openshift.io/SCCExecRestrictions
-
route.openshift.io/IngressAdmission
-
config.openshift.io/ValidateAPIServer
-
config.openshift.io/ValidateAuthentication
-
config.openshift.io/ValidateFeatureGate
-
config.openshift.io/ValidateConsole
-
operator.openshift.io/ValidateDNS
-
config.openshift.io/ValidateImage
-
config.openshift.io/ValidateOAuth
-
config.openshift.io/ValidateProject
-
config.openshift.io/DenyDeleteClusterConfiguration
-
config.openshift.io/ValidateScheduler
-
quota.openshift.io/ValidateClusterResourceQuota
-
security.openshift.io/ValidateSecurityContextConstraints
-
authorization.openshift.io/ValidateRoleBindingRestriction
-
config.openshift.io/ValidateNetwork
-
operator.openshift.io/ValidateKubeControllerManager
-
ValidatingAdmissionWebhook
-
ResourceQuota
-
quota.openshift.io/ClusterResourceQuota
Example 10.2. Mutating admission plugins
-
NamespaceLifecycle
-
LimitRanger
-
ServiceAccount
-
NodeRestriction
-
TaintNodesByCondition
-
PodNodeSelector
-
Priority
-
DefaultTolerationSeconds
-
PodTolerationRestriction
-
DefaultStorageClass
-
StorageObjectInUseProtection
-
RuntimeClass
-
DefaultIngressClass
-
autoscaling.openshift.io/ManagementCPUsOverride
-
scheduling.openshift.io/OriginPodNodeEnvironment
-
image.openshift.io/ImagePolicy
-
security.openshift.io/SecurityContextConstraint
-
security.openshift.io/DefaultSecurityContextConstraints
-
MutatingAdmissionWebhook
10.3. Webhook admission plugins
In addition to OpenShift Container Platform default admission plugins, dynamic admission can be implemented through webhook admission plugins that call webhook servers, to extend the functionality of the admission chain. Webhook servers are called over HTTP at defined endpoints.
There are two types of webhook admission plugins in OpenShift Container Platform:
- During the admission process, the mutating admission plugin can perform tasks, such as injecting affinity labels.
- At the end of the admission process, the validating admission plugin can be used to make sure an object is configured properly, for example ensuring affinity labels are as expected. If the validation passes, OpenShift Container Platform schedules the object as configured.
When an API request comes in, mutating or validating admission plugins use the list of external webhooks in the configuration and call them in parallel:
- If all of the webhooks approve the request, the admission chain continues.
- If any of the webhooks deny the request, the admission request is denied and the reason for doing so is based on the first denial.
- If more than one webhook denies the admission request, only the first denial reason is returned to the user.
-
If an error is encountered when calling a webhook, the request is either denied or the webhook is ignored depending on the error policy set. If the error policy is set to
Ignore
, the request is unconditionally accepted in the event of a failure. If the policy is set toFail
, failed requests are denied. UsingIgnore
can result in unpredictable behavior for all clients.
Communication between the webhook admission plugin and the webhook server must use TLS. Generate a CA certificate and use the certificate to sign the server certificate that is used by your webhook admission server. The PEM-encoded CA certificate is supplied to the webhook admission plugin using a mechanism, such as service serving certificate secrets.
The following diagram illustrates the sequential admission chain process within which multiple webhook servers are called.
Figure 10.1. API admission chain with mutating and validating admission plugins
![API admission stage](https://access.redhat.com/webassets/avalon/d/OpenShift_Container_Platform-4.14-Architecture-en-US/images/e2115419a4f5ded9dcc282b79e84a8b2/api-admission-chain.png)
An example webhook admission plugin use case is where all pods must have a common set of labels. In this example, the mutating admission plugin can inject labels and the validating admission plugin can check that labels are as expected. OpenShift Container Platform would subsequently schedule pods that include required labels and reject those that do not.
Some common webhook admission plugin use cases include:
- Namespace reservation.
- Limiting custom network resources managed by the SR-IOV network device plugin.
- Defining tolerations that enable taints to qualify which pods should be scheduled on a node.
- Pod priority class validation.
The maximum default webhook timeout value in OpenShift Container Platform is 13 seconds, and it cannot be changed.
10.4. Types of webhook admission plugins
Cluster administrators can call out to webhook servers through the mutating admission plugin or the validating admission plugin in the API server admission chain.
10.4.1. Mutating admission plugin
The mutating admission plugin is invoked during the mutation phase of the admission process, which allows modification of resource content before it is persisted. One example webhook that can be called through the mutating admission plugin is the Pod Node Selector feature, which uses an annotation on a namespace to find a label selector and add it to the pod specification.
Sample mutating admission plugin configuration
apiVersion: admissionregistration.k8s.io/v1beta1 kind: MutatingWebhookConfiguration 1 metadata: name: <webhook_name> 2 webhooks: - name: <webhook_name> 3 clientConfig: 4 service: namespace: default 5 name: kubernetes 6 path: <webhook_url> 7 caBundle: <ca_signing_certificate> 8 rules: 9 - operations: 10 - <operation> apiGroups: - "" apiVersions: - "*" resources: - <resource> failurePolicy: <policy> 11 sideEffects: None
- 1
- Specifies a mutating admission plugin configuration.
- 2
- The name for the
MutatingWebhookConfiguration
object. Replace<webhook_name>
with the appropriate value. - 3
- The name of the webhook to call. Replace
<webhook_name>
with the appropriate value. - 4
- Information about how to connect to, trust, and send data to the webhook server.
- 5
- The namespace where the front-end service is created.
- 6
- The name of the front-end service.
- 7
- The webhook URL used for admission requests. Replace
<webhook_url>
with the appropriate value. - 8
- A PEM-encoded CA certificate that signs the server certificate that is used by the webhook server. Replace
<ca_signing_certificate>
with the appropriate certificate in base64 format. - 9
- Rules that define when the API server should use this webhook admission plugin.
- 10
- One or more operations that trigger the API server to call this webhook admission plugin. Possible values are
create
,update
,delete
orconnect
. Replace<operation>
and<resource>
with the appropriate values. - 11
- Specifies how the policy should proceed if the webhook server is unavailable. Replace
<policy>
with eitherIgnore
(to unconditionally accept the request in the event of a failure) orFail
(to deny the failed request). UsingIgnore
can result in unpredictable behavior for all clients.
In OpenShift Container Platform 4.14, objects created by users or control loops through a mutating admission plugin might return unexpected results, especially if values set in an initial request are overwritten, which is not recommended.
10.4.2. Validating admission plugin
A validating admission plugin is invoked during the validation phase of the admission process. This phase allows the enforcement of invariants on particular API resources to ensure that the resource does not change again. The Pod Node Selector is also an example of a webhook which is called by the validating admission plugin, to ensure that all nodeSelector
fields are constrained by the node selector restrictions on the namespace.
Sample validating admission plugin configuration
apiVersion: admissionregistration.k8s.io/v1beta1 kind: ValidatingWebhookConfiguration 1 metadata: name: <webhook_name> 2 webhooks: - name: <webhook_name> 3 clientConfig: 4 service: namespace: default 5 name: kubernetes 6 path: <webhook_url> 7 caBundle: <ca_signing_certificate> 8 rules: 9 - operations: 10 - <operation> apiGroups: - "" apiVersions: - "*" resources: - <resource> failurePolicy: <policy> 11 sideEffects: Unknown
- 1
- Specifies a validating admission plugin configuration.
- 2
- The name for the
ValidatingWebhookConfiguration
object. Replace<webhook_name>
with the appropriate value. - 3
- The name of the webhook to call. Replace
<webhook_name>
with the appropriate value. - 4
- Information about how to connect to, trust, and send data to the webhook server.
- 5
- The namespace where the front-end service is created.
- 6
- The name of the front-end service.
- 7
- The webhook URL used for admission requests. Replace
<webhook_url>
with the appropriate value. - 8
- A PEM-encoded CA certificate that signs the server certificate that is used by the webhook server. Replace
<ca_signing_certificate>
with the appropriate certificate in base64 format. - 9
- Rules that define when the API server should use this webhook admission plugin.
- 10
- One or more operations that trigger the API server to call this webhook admission plugin. Possible values are
create
,update
,delete
orconnect
. Replace<operation>
and<resource>
with the appropriate values. - 11
- Specifies how the policy should proceed if the webhook server is unavailable. Replace
<policy>
with eitherIgnore
(to unconditionally accept the request in the event of a failure) orFail
(to deny the failed request). UsingIgnore
can result in unpredictable behavior for all clients.
10.5. Configuring dynamic admission
This procedure outlines high-level steps to configure dynamic admission. The functionality of the admission chain is extended by configuring a webhook admission plugin to call out to a webhook server.
The webhook server is also configured as an aggregated API server. This allows other OpenShift Container Platform components to communicate with the webhook using internal credentials and facilitates testing using the oc
command. Additionally, this enables role based access control (RBAC) into the webhook and prevents token information from other API servers from being disclosed to the webhook.
Prerequisites
- An OpenShift Container Platform account with cluster administrator access.
-
The OpenShift Container Platform CLI (
oc
) installed. - A published webhook server container image.
Procedure
- Build a webhook server container image and make it available to the cluster using an image registry.
- Create a local CA key and certificate and use them to sign the webhook server’s certificate signing request (CSR).
Create a new project for webhook resources:
$ oc new-project my-webhook-namespace 1
- 1
- Note that the webhook server might expect a specific name.
Define RBAC rules for the aggregated API service in a file called
rbac.yaml
:apiVersion: v1 kind: List items: - apiVersion: rbac.authorization.k8s.io/v1 1 kind: ClusterRoleBinding metadata: name: auth-delegator-my-webhook-namespace roleRef: kind: ClusterRole apiGroup: rbac.authorization.k8s.io name: system:auth-delegator subjects: - kind: ServiceAccount namespace: my-webhook-namespace name: server - apiVersion: rbac.authorization.k8s.io/v1 2 kind: ClusterRole metadata: annotations: name: system:openshift:online:my-webhook-server rules: - apiGroups: - online.openshift.io resources: - namespacereservations 3 verbs: - get - list - watch - apiVersion: rbac.authorization.k8s.io/v1 4 kind: ClusterRole metadata: name: system:openshift:online:my-webhook-requester rules: - apiGroups: - admission.online.openshift.io resources: - namespacereservations 5 verbs: - create - apiVersion: rbac.authorization.k8s.io/v1 6 kind: ClusterRoleBinding metadata: name: my-webhook-server-my-webhook-namespace roleRef: kind: ClusterRole apiGroup: rbac.authorization.k8s.io name: system:openshift:online:my-webhook-server subjects: - kind: ServiceAccount namespace: my-webhook-namespace name: server - apiVersion: rbac.authorization.k8s.io/v1 7 kind: RoleBinding metadata: namespace: kube-system name: extension-server-authentication-reader-my-webhook-namespace roleRef: kind: Role apiGroup: rbac.authorization.k8s.io name: extension-apiserver-authentication-reader subjects: - kind: ServiceAccount namespace: my-webhook-namespace name: server - apiVersion: rbac.authorization.k8s.io/v1 8 kind: ClusterRole metadata: name: my-cluster-role rules: - apiGroups: - admissionregistration.k8s.io resources: - validatingwebhookconfigurations - mutatingwebhookconfigurations verbs: - get - list - watch - apiGroups: - "" resources: - namespaces verbs: - get - list - watch - apiVersion: rbac.authorization.k8s.io/v1 kind: ClusterRoleBinding metadata: name: my-cluster-role roleRef: kind: ClusterRole apiGroup: rbac.authorization.k8s.io name: my-cluster-role subjects: - kind: ServiceAccount namespace: my-webhook-namespace name: server
- 1
- Delegates authentication and authorization to the webhook server API.
- 2
- Allows the webhook server to access cluster resources.
- 3
- Points to resources. This example points to the
namespacereservations
resource. - 4
- Enables the aggregated API server to create admission reviews.
- 5
- Points to resources. This example points to the
namespacereservations
resource. - 6
- Enables the webhook server to access cluster resources.
- 7
- Role binding to read the configuration for terminating authentication.
- 8
- Default cluster role and cluster role bindings for an aggregated API server.
Apply those RBAC rules to the cluster:
$ oc auth reconcile -f rbac.yaml
Create a YAML file called
webhook-daemonset.yaml
that is used to deploy a webhook as a daemon set server in a namespace:apiVersion: apps/v1 kind: DaemonSet metadata: namespace: my-webhook-namespace name: server labels: server: "true" spec: selector: matchLabels: server: "true" template: metadata: name: server labels: server: "true" spec: serviceAccountName: server containers: - name: my-webhook-container 1 image: <image_registry_username>/<image_path>:<tag> 2 imagePullPolicy: IfNotPresent command: - <container_commands> 3 ports: - containerPort: 8443 4 volumeMounts: - mountPath: /var/serving-cert name: serving-cert readinessProbe: httpGet: path: /healthz port: 8443 5 scheme: HTTPS volumes: - name: serving-cert secret: defaultMode: 420 secretName: server-serving-cert
- 1
- Note that the webhook server might expect a specific container name.
- 2
- Points to a webhook server container image. Replace
<image_registry_username>/<image_path>:<tag>
with the appropriate value. - 3
- Specifies webhook container run commands. Replace
<container_commands>
with the appropriate value. - 4
- Defines the target port within pods. This example uses port 8443.
- 5
- Specifies the port used by the readiness probe. This example uses port 8443.
Deploy the daemon set:
$ oc apply -f webhook-daemonset.yaml
Define a secret for the service serving certificate signer, within a YAML file called
webhook-secret.yaml
:apiVersion: v1 kind: Secret metadata: namespace: my-webhook-namespace name: server-serving-cert type: kubernetes.io/tls data: tls.crt: <server_certificate> 1 tls.key: <server_key> 2
Create the secret:
$ oc apply -f webhook-secret.yaml
Define a service account and service, within a YAML file called
webhook-service.yaml
:apiVersion: v1 kind: List items: - apiVersion: v1 kind: ServiceAccount metadata: namespace: my-webhook-namespace name: server - apiVersion: v1 kind: Service metadata: namespace: my-webhook-namespace name: server annotations: service.beta.openshift.io/serving-cert-secret-name: server-serving-cert spec: selector: server: "true" ports: - port: 443 1 targetPort: 8443 2
Expose the webhook server within the cluster:
$ oc apply -f webhook-service.yaml
Define a custom resource definition for the webhook server, in a file called
webhook-crd.yaml
:apiVersion: apiextensions.k8s.io/v1beta1 kind: CustomResourceDefinition metadata: name: namespacereservations.online.openshift.io 1 spec: group: online.openshift.io 2 version: v1alpha1 3 scope: Cluster 4 names: plural: namespacereservations 5 singular: namespacereservation 6 kind: NamespaceReservation 7
- 1
- Reflects
CustomResourceDefinition
spec
values and is in the format<plural>.<group>
. This example uses thenamespacereservations
resource. - 2
- REST API group name.
- 3
- REST API version name.
- 4
- Accepted values are
Namespaced
orCluster
. - 5
- Plural name to be included in URL.
- 6
- Alias seen in
oc
output. - 7
- The reference for resource manifests.
Apply the custom resource definition:
$ oc apply -f webhook-crd.yaml
Configure the webhook server also as an aggregated API server, within a file called
webhook-api-service.yaml
:apiVersion: apiregistration.k8s.io/v1beta1 kind: APIService metadata: name: v1beta1.admission.online.openshift.io spec: caBundle: <ca_signing_certificate> 1 group: admission.online.openshift.io groupPriorityMinimum: 1000 versionPriority: 15 service: name: server namespace: my-webhook-namespace version: v1beta1
- 1
- A PEM-encoded CA certificate that signs the server certificate that is used by the webhook server. Replace
<ca_signing_certificate>
with the appropriate certificate in base64 format.
Deploy the aggregated API service:
$ oc apply -f webhook-api-service.yaml
Define the webhook admission plugin configuration within a file called
webhook-config.yaml
. This example uses the validating admission plugin:apiVersion: admissionregistration.k8s.io/v1beta1 kind: ValidatingWebhookConfiguration metadata: name: namespacereservations.admission.online.openshift.io 1 webhooks: - name: namespacereservations.admission.online.openshift.io 2 clientConfig: service: 3 namespace: default name: kubernetes path: /apis/admission.online.openshift.io/v1beta1/namespacereservations 4 caBundle: <ca_signing_certificate> 5 rules: - operations: - CREATE apiGroups: - project.openshift.io apiVersions: - "*" resources: - projectrequests - operations: - CREATE apiGroups: - "" apiVersions: - "*" resources: - namespaces failurePolicy: Fail
- 1
- Name for the
ValidatingWebhookConfiguration
object. This example uses thenamespacereservations
resource. - 2
- Name of the webhook to call. This example uses the
namespacereservations
resource. - 3
- Enables access to the webhook server through the aggregated API.
- 4
- The webhook URL used for admission requests. This example uses the
namespacereservation
resource. - 5
- A PEM-encoded CA certificate that signs the server certificate that is used by the webhook server. Replace
<ca_signing_certificate>
with the appropriate certificate in base64 format.
Deploy the webhook:
$ oc apply -f webhook-config.yaml
- Verify that the webhook is functioning as expected. For example, if you have configured dynamic admission to reserve specific namespaces, confirm that requests to create those namespaces are rejected and that requests to create non-reserved namespaces succeed.