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Chapter 6. Cluster logging with OpenShift Serverless
6.1. About cluster logging
OpenShift Container Platform cluster administrators can deploy cluster logging using a few CLI commands and the OpenShift Container Platform web console to install the Elasticsearch Operator and Cluster Logging Operator. When the operators are installed, create a Cluster Logging Custom Resource (CR) to schedule cluster logging pods and other resources necessary to support cluster logging. The operators are responsible for deploying, upgrading, and maintaining cluster logging.
You can configure cluster logging by modifying the Cluster Logging Custom Resource (CR), named instance
. The CR defines a complete cluster logging deployment that includes all the components of the logging stack to collect, store and visualize logs. The Cluster Logging Operator watches the ClusterLogging
Custom Resource and adjusts the logging deployment accordingly.
Administrators and application developers can view the logs of the projects for which they have view access.
6.2. About deploying and configuring cluster logging
OpenShift Container Platform cluster logging is designed to be used with the default configuration, which is tuned for small to medium sized OpenShift Container Platform clusters.
The installation instructions that follow include a sample Cluster Logging Custom Resource (CR), which you can use to create a cluster logging instance and configure your cluster logging deployment.
If you want to use the default cluster logging install, you can use the sample CR directly.
If you want to customize your deployment, make changes to the sample CR as needed. The following describes the configurations you can make when installing your cluster logging instance or modify after installtion. See the Configuring sections for more information on working with each component, including modifications you can make outside of the Cluster Logging Custom Resource.
6.2.1. Configuring and Tuning Cluster Logging
You can configure your cluster logging environment by modifying the Cluster Logging Custom Resource deployed in the openshift-logging
project.
You can modify any of the following components upon install or after install:
- Memory and CPU
-
You can adjust both the CPU and memory limits for each component by modifying the
resources
block with valid memory and CPU values:
spec: logStore: elasticsearch: resources: limits: cpu: memory: requests: cpu: 1 memory: 16Gi type: "elasticsearch" collection: logs: fluentd: resources: limits: cpu: memory: requests: cpu: memory: type: "fluentd" visualization: kibana: resources: limits: cpu: memory: requests: cpu: memory: type: kibana curation: curator: resources: limits: memory: 200Mi requests: cpu: 200m memory: 200Mi type: "curator"
- Elasticsearch storage
-
You can configure a persistent storage class and size for the Elasticsearch cluster using the
storageClass
name
andsize
parameters. The Cluster Logging Operator creates aPersistentVolumeClaim
for each data node in the Elasticsearch cluster based on these parameters.
spec: logStore: type: "elasticsearch" elasticsearch: storage: storageClassName: "gp2" size: "200G"
This example specifies each data node in the cluster will be bound to a PersistentVolumeClaim
that requests "200G" of "gp2" storage. Each primary shard will be backed by a single replica.
Omitting the storage
block results in a deployment that includes ephemeral storage only.
spec: logStore: type: "elasticsearch" elasticsearch: storage: {}
- Elasticsearch replication policy
You can set the policy that defines how Elasticsearch shards are replicated across data nodes in the cluster:
-
FullRedundancy
. The shards for each index are fully replicated to every data node. -
MultipleRedundancy
. The shards for each index are spread over half of the data nodes. -
SingleRedundancy
. A single copy of each shard. Logs are always available and recoverable as long as at least two data nodes exist. -
ZeroRedundancy
. No copies of any shards. Logs may be unavailable (or lost) in the event a node is down or fails.
-
- Curator schedule
- You specify the schedule for Curator in the [cron format](https://en.wikipedia.org/wiki/Cron).
spec: curation: type: "curator" resources: curator: schedule: "30 3 * * *"
6.2.2. Sample modified Cluster Logging Custom Resource
The following is an example of a Cluster Logging Custom Resource modified using the options previously described.
Sample modified Cluster Logging Custom Resource
apiVersion: "logging.openshift.io/v1" kind: "ClusterLogging" metadata: name: "instance" namespace: "openshift-logging" spec: managementState: "Managed" logStore: type: "elasticsearch" elasticsearch: nodeCount: 2 resources: limits: memory: 2Gi requests: cpu: 200m memory: 2Gi storage: {} redundancyPolicy: "SingleRedundancy" visualization: type: "kibana" kibana: resources: limits: memory: 1Gi requests: cpu: 500m memory: 1Gi replicas: 1 curation: type: "curator" curator: resources: limits: memory: 200Mi requests: cpu: 200m memory: 200Mi schedule: "*/5 * * * *" collection: logs: type: "fluentd" fluentd: resources: limits: memory: 1Gi requests: cpu: 200m memory: 1Gi
6.3. Using cluster logging to find logs for Knative Serving components
Procedure
To open the Kibana UI, the visualization tool for Elasticsearch, use the following command to get the Kibana route:
$ oc -n openshift-logging get route kibana
- Use the route’s URL to navigate to the Kibana dashboard and log in.
- Ensure the index is set to .all. If the index is not set to .all, only the OpenShift system logs will be listed.
You can filter the logs by using the
knative-serving
namespace. Enterkubernetes.namespace_name:knative-serving
in the search box to filter results.NoteKnative Serving uses structured logging by default. You can enable the parsing of these logs by customizing the cluster logging Fluentd settings. This makes the logs more searchable and enables filtering on the log level to quickly identify issues.
6.4. Using cluster logging to find logs for services deployed with Knative Serving
With OpenShift Cluster Logging, the logs that your applications write to the console are collected in Elasticsearch. The following procedure outlines how to apply these capabilities to applications deployed by using Knative Serving.
Procedure
Use the following command to find the URL to Kibana:
$ oc -n cluster-logging get route kibana`
- Enter the URL in your browser to open the Kibana UI.
- Ensure the index is set to .all. If the index is not set to .all, only the OpenShift system logs will be listed.
Filter the logs by using the Kubernetes namespace your service is deployed in. Add a filter to identify the service itself:
kubernetes.namespace_name:default AND kubernetes.labels.serving_knative_dev\/service:{SERVICE_NAME}
.NoteYou can also filter by using
/configuration
or/revision
.You can narrow your search by using
kubernetes.container_name:<user-container>
to only display the logs generated by your application. Otherwise, you will see logs from the queue-proxy.NoteUse JSON-based structured logging in your application to allow for the quick filtering of these logs in production environments.