Architecture

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:

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.

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.

OpenShift Container Platform provides enterprise-ready enhancements to Kubernetes, including the following enhancements:

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 4.13 offers. The following sections describe some unique features and benefits of OpenShift Container Platform.

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

In OpenShift Container Platform 4.13, you require access to the internet to install your cluster.

You must have internet access to:

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

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 4.13 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.

In OpenShift Container Platform 4.13, you can install a cluster that uses installer-provisioned infrastructure on the following platforms:

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.

In OpenShift Container Platform 4.13, you can install a cluster that uses user-provisioned infrastructure on the following platforms:

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.

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:

In OpenShift Container Platform 4.13, 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:

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.

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.

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:

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

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.

Bootstrapping a cluster involves the following steps:

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.

The Overview tab provides information about how your cluster was configured:

The Access control tab allows the cluster owner to set up an identity provider, grant elevated permissions, and grant roles to other users.

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.

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.

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.

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.

The Settings tab provides a few options for the cluster owner:

The OpenShift Container Platform version must match between control plane host and node host. For example, in a 4.13 cluster, all control plane hosts must be 4.13 and all nodes must be 4.13.

Temporary mismatches during cluster upgrades are acceptable. For example, when upgrading from OpenShift Container Platform 4.12 to 4.13, some nodes will upgrade to 4.13 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:

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.

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.

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.

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.

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.

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:

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:

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.

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.

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 4.13, 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.

By using etcd, you can benefit in several ways:

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:

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".

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.

With hosted control planes for OpenShift Container Platform, you can pave the way for a true hybrid-cloud approach and enjoy several other benefits.

With each major, minor, or patch version release of OpenShift Container Platform, two components of hosted control planes are released:

The HyperShift Operator manages the lifecycle of hosted clusters that are represented by HostedCluster API resources. The HyperShift Operator is released with each OpenShift Container Platform release. After the HyperShift Operator is installed, it creates a config map called supported-versions in the HyperShift namespace, as shown in the following example. The config map describes the HostedCluster versions that can be deployed.

    apiVersion: v1
    data:
      supported-versions: '{"versions":["4.13","4.12","4.11"]}'
    kind: ConfigMap
    metadata:
      labels:
        hypershift.openshift.io/supported-versions: "true"
      name: supported-versions
      namespace: hypershift

The CLI is a helper utility for development purposes. The CLI is released as part of any HyperShift Operator release. No compatibility policies are guaranteed.

The API, hypershift.openshift.io, provides a way to create and manage lightweight, flexible, heterogeneous OpenShift Container Platform clusters at scale. The API exposes two user-facing resources: HostedCluster and NodePool. A HostedCluster resource encapsulates 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.

You can deploy OpenShift Container Platform on an NVIDIA-certified bare metal server but with some limitations:

You can choose one of the following methods to access the containerized GPUs:

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:

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:

You can choose one of the following methods to attach the worker nodes to the GPUs:

Similar to bare metal deployments, one or three or more servers are required. Clusters with two servers are not supported.

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:

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.

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.

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:

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.

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.

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.

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.

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.

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.

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.

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.

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

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.

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.

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:

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:

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.

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.

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:

The following list describes key features of the RHCOS operating system:

For RHCOS systems, the layout of the rpm-ostree file system has the following characteristics:

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:

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:

Here are examples of customizations you could do on day 1:

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.

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:

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.

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).

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.

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

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.

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