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Installing the logging subsystem for Red Hat OpenShift

You can install the logging subsystem for Red Hat OpenShift by deploying the OpenShift Elasticsearch and Red Hat OpenShift Logging Operators. The OpenShift Elasticsearch Operator creates and manages the Elasticsearch cluster used by OpenShift Logging. The logging subsystem Operator creates and manages the components of the logging stack.

The process for deploying the logging subsystem to OKD involves:

Installing the logging subsystem for Red Hat OpenShift using the web console

You can use the OKD web console to install the OpenShift Elasticsearch and Red Hat OpenShift Logging Operators.

If you do not want to use the default Elasticsearch log store, you can remove the internal Elasticsearch logStore and Kibana visualization components from the ClusterLogging custom resource (CR). Removing these components is optional but saves resources. For more information, see Removing unused components if you do not use the default Elasticsearch log store.
Prerequisites

  • Ensure that you have the necessary persistent storage for Elasticsearch. Note that each Elasticsearch node requires its own storage volume.

    If you use a local volume for persistent storage, do not use a raw block volume, which is described with volumeMode: block in the LocalVolume object. Elasticsearch cannot use raw block volumes.

    Elasticsearch is a memory-intensive application. By default, OKD installs three Elasticsearch nodes with memory requests and limits of 16 GB. This initial set of three OKD nodes might not have enough memory to run Elasticsearch within your cluster. If you experience memory issues that are related to Elasticsearch, add more Elasticsearch nodes to your cluster rather than increasing the memory on existing nodes.

  • Ensure that you have downloaded the pull secret from the Red Hat OpenShift Cluster Manager as shown in Obtaining the installation program in the installation documentation for your platform.

    If you have the pull secret, add the redhat-operators catalog to the OperatorHub custom resource (CR) as shown in Configuring OKD to use Red Hat Operators.

Procedure

To install the OpenShift Elasticsearch Operator and Red Hat OpenShift Logging Operator using the OKD web console:

  1. Install the OpenShift Elasticsearch Operator:

    1. In the OKD web console, click Operators → OperatorHub.

    2. Choose OpenShift Elasticsearch Operator from the list of available Operators, and click Install.

    3. Ensure that the All namespaces on the cluster is selected under Installation Mode.

    4. Ensure that openshift-operators-redhat is selected under Installed Namespace.

      You must specify the openshift-operators-redhat namespace. The openshift-operators namespace might contain Community Operators, which are untrusted and could publish a metric with the same name as an OKD metric, which would cause conflicts.

    5. Select Enable operator recommended cluster monitoring on this namespace.

      This option sets the openshift.io/cluster-monitoring: "true" label in the Namespace object. You must select this option to ensure that cluster monitoring scrapes the openshift-operators-redhat namespace.

    6. Select stable-5.x as the Update Channel.

    7. Select an Approval Strategy.

      • The Automatic strategy allows Operator Lifecycle Manager (OLM) to automatically update the Operator when a new version is available.

      • The Manual strategy requires a user with appropriate credentials to approve the Operator update.

    8. Click Install.

    9. Verify that the OpenShift Elasticsearch Operator installed by switching to the Operators → Installed Operators page.

    10. Ensure that OpenShift Elasticsearch Operator is listed in all projects with a Status of Succeeded.

  2. Install the Red Hat OpenShift Logging Operator:

    1. In the OKD web console, click Operators → OperatorHub.

    2. Choose Red Hat OpenShift Logging from the list of available Operators, and click Install.

    3. Ensure that the A specific namespace on the cluster is selected under Installation Mode.

    4. Ensure that Operator recommended namespace is openshift-logging under Installed Namespace.

    5. Select Enable operator recommended cluster monitoring on this namespace.

      This option sets the openshift.io/cluster-monitoring: "true" label in the Namespace object. You must select this option to ensure that cluster monitoring scrapes the openshift-logging namespace.

    6. Select stable-5.x as the Update Channel.

    7. Select an Approval Strategy.

      • The Automatic strategy allows Operator Lifecycle Manager (OLM) to automatically update the Operator when a new version is available.

      • The Manual strategy requires a user with appropriate credentials to approve the Operator update.

    8. Click Install.

    9. Verify that the Red Hat OpenShift Logging Operator installed by switching to the Operators → Installed Operators page.

    10. Ensure that Red Hat OpenShift Logging is listed in the openshift-logging project with a Status of Succeeded.

      If the Operator does not appear as installed, to troubleshoot further:

      • Switch to the Operators → Installed Operators page and inspect the Status column for any errors or failures.

      • Switch to the Workloads → Pods page and check the logs in any pods in the openshift-logging project that are reporting issues.

  3. Create an OpenShift Logging instance:

    1. Switch to the Administration → Custom Resource Definitions page.

    2. On the Custom Resource Definitions page, click ClusterLogging.

    3. On the Custom Resource Definition details page, select View Instances from the Actions menu.

    4. On the ClusterLoggings page, click Create ClusterLogging.

      You might have to refresh the page to load the data.

    5. In the YAML field, replace the code with the following:

      This default OpenShift Logging configuration should support a wide array of environments. Review the topics on tuning and configuring logging subsystem components for information on modifications you can make to your OpenShift Logging cluster.

      		 
      apiVersion: "logging.openshift.io/v1"
kind: "ClusterLogging"
metadata:
  name: "instance" (1)
  namespace: "openshift-logging"
spec:
  managementState: "Managed"  (2)
  logStore:
    type: "elasticsearch"  (3)
    retentionPolicy: (4)
      application:
        maxAge: 1d
      infra:
        maxAge: 7d
      audit:
        maxAge: 7d
    elasticsearch:
      nodeCount: 3 (5)
      storage:
        storageClassName: "<storage_class_name>" (6)
        size: 200G
      resources: (7)
          limits:
            memory: "16Gi"
          requests:
            memory: "16Gi"
      proxy: (8)
        resources:
          limits:
            memory: 256Mi
          requests:
            memory: 256Mi
      redundancyPolicy: "SingleRedundancy"
  visualization:
    type: "kibana"  (9)
    kibana:
      replicas: 1
  collection:
    logs:
      type: "fluentd"  (10)
      fluentd: {}
      1 The name must be instance.
      2 The OpenShift Logging management state. In some cases, if you change the OpenShift Logging defaults, you must set this to Unmanaged. However, an unmanaged deployment does not receive updates until OpenShift Logging is placed back into a managed state.
      3 Settings for configuring Elasticsearch. Using the CR, you can configure shard replication policy and persistent storage.
      4 Specify the length of time that Elasticsearch should retain each log source. Enter an integer and a time designation: weeks(w), hours(h/H), minutes(m) and seconds(s). For example, 7d for seven days. Logs older than the maxAge are deleted. You must specify a retention policy for each log source or the Elasticsearch indices will not be created for that source.
      5 Specify the number of Elasticsearch nodes. See the note that follows this list.
      6 Enter the name of an existing storage class for Elasticsearch storage. For best performance, specify a storage class that allocates block storage. If you do not specify a storage class, OpenShift Logging uses ephemeral storage.
      7 Specify the CPU and memory requests for Elasticsearch as needed. If you leave these values blank, the OpenShift Elasticsearch Operator sets default values that should be sufficient for most deployments. The default values are 16Gi for the memory request and 1 for the CPU request.
      8 Specify the CPU and memory requests for the Elasticsearch proxy as needed. If you leave these values blank, the OpenShift Elasticsearch Operator sets default values that should be sufficient for most deployments. The default values are 256Mi for the memory request and 100m for the CPU request.
      9 Settings for configuring Kibana. Using the CR, you can scale Kibana for redundancy and configure the CPU and memory for your Kibana nodes. For more information, see Configuring the log visualizer.
      10 Settings for configuring Fluentd. Using the CR, you can configure Fluentd CPU and memory limits. For more information, see Configuring Fluentd.

      The maximum number of Elasticsearch control plane nodes is three. If you specify a nodeCount greater than 3, OKD creates three Elasticsearch nodes that are Master-eligible nodes, with the master, client, and data roles. The additional Elasticsearch nodes are created as Data-only nodes, using client and data roles. Control plane nodes perform cluster-wide actions such as creating or deleting an index, shard allocation, and tracking nodes. Data nodes hold the shards and perform data-related operations such as CRUD, search, and aggregations. Data-related operations are I/O-, memory-, and CPU-intensive. It is important to monitor these resources and to add more Data nodes if the current nodes are overloaded.

      For example, if nodeCount=4, the following nodes are created:

      $ oc get deployment
      Example output
      cluster-logging-operator       1/1     1            1           18h
elasticsearch-cd-x6kdekli-1    0/1     1            0           6m54s
elasticsearch-cdm-x6kdekli-1   1/1     1            1           18h
elasticsearch-cdm-x6kdekli-2   0/1     1            0           6m49s
elasticsearch-cdm-x6kdekli-3   0/1     1            0           6m44s

      The number of primary shards for the index templates is equal to the number of Elasticsearch data nodes.

    6. Click Create. This creates the logging subsystem components, the Elasticsearch custom resource and components, and the Kibana interface.

  4. Verify the install:

    1. Switch to the Workloads → Pods page.

    2. Select the openshift-logging project.

      You should see several pods for OpenShift Logging, Elasticsearch, Fluentd, and Kibana similar to the following list:

      • cluster-logging-operator-cb795f8dc-xkckc

      • elasticsearch-cdm-b3nqzchd-1-5c6797-67kfz

      • elasticsearch-cdm-b3nqzchd-2-6657f4-wtprv

      • elasticsearch-cdm-b3nqzchd-3-588c65-clg7g

      • fluentd-2c7dg

      • fluentd-9z7kk

      • fluentd-br7r2

      • fluentd-fn2sb

      • fluentd-pb2f8

      • fluentd-zqgqx

      • kibana-7fb4fd4cc9-bvt4p

Additional resources

Post-installation tasks

If you plan to use Kibana, you must manually create your Kibana index patterns and visualizations to explore and visualize data in Kibana.

If your cluster network provider enforces network isolation, allow network traffic between the projects that contain the logging subsystem Operators.

Installing the logging subsystem for Red Hat OpenShift using the CLI

You can use the OKD CLI to install the OpenShift Elasticsearch and Red Hat OpenShift Logging Operators.

Prerequisites

  • Ensure that you have the necessary persistent storage for Elasticsearch. Note that each Elasticsearch node requires its own storage volume.

    If you use a local volume for persistent storage, do not use a raw block volume, which is described with volumeMode: block in the LocalVolume object. Elasticsearch cannot use raw block volumes.

    Elasticsearch is a memory-intensive application. By default, OKD installs three Elasticsearch nodes with memory requests and limits of 16 GB. This initial set of three OKD nodes might not have enough memory to run Elasticsearch within your cluster. If you experience memory issues that are related to Elasticsearch, add more Elasticsearch nodes to your cluster rather than increasing the memory on existing nodes.

  • Ensure that you have downloaded the pull secret from the Red Hat OpenShift Cluster Manager as shown in Obtaining the installation program in the installation documentation for your platform.

    If you have the pull secret, add the redhat-operators catalog to the OperatorHub custom resource (CR) as shown in Configuring OKD to use Red Hat Operators.

Procedure

To install the OpenShift Elasticsearch Operator and Red Hat OpenShift Logging Operator using the CLI:

  1. Create a namespace for the OpenShift Elasticsearch Operator.

    1. Create a namespace object YAML file (for example, eo-namespace.yaml) for the OpenShift Elasticsearch Operator:

      apiVersion: v1
kind: Namespace
metadata:
  name: openshift-operators-redhat (1)
  annotations:
    openshift.io/node-selector: ""
  labels:
    openshift.io/cluster-monitoring: "true" (2)
      1 You must specify the openshift-operators-redhat namespace. To prevent possible conflicts with metrics, you should configure the Prometheus Cluster Monitoring stack to scrape metrics from the openshift-operators-redhat namespace and not the openshift-operators namespace. The openshift-operators namespace might contain community Operators, which are untrusted and could publish a metric with the same name as an OKD metric, which would cause conflicts.
      2 String. You must specify this label as shown to ensure that cluster monitoring scrapes the openshift-operators-redhat namespace.

    2. Create the namespace:

      $ oc create -f <file-name>.yaml

      For example:

      $ oc create -f eo-namespace.yaml

  2. Create a namespace for the Red Hat OpenShift Logging Operator:

    1. Create a namespace object YAML file (for example, olo-namespace.yaml) for the Red Hat OpenShift Logging Operator:

      apiVersion: v1
kind: Namespace
metadata:
  name: openshift-logging
  annotations:
    openshift.io/node-selector: ""
  labels:
    openshift.io/cluster-monitoring: "true"

    2. Create the namespace:

      $ oc create -f <file-name>.yaml

      For example:

      $ oc create -f olo-namespace.yaml

  3. Install the OpenShift Elasticsearch Operator by creating the following objects:

    1. Create an Operator Group object YAML file (for example, eo-og.yaml) for the OpenShift Elasticsearch Operator:

      apiVersion: operators.coreos.com/v1
kind: OperatorGroup
metadata:
  name: openshift-operators-redhat
  namespace: openshift-operators-redhat (1)
spec: {}
      1 You must specify the openshift-operators-redhat namespace.

    2. Create an Operator Group object:

      $ oc create -f <file-name>.yaml

      For example:

      $ oc create -f eo-og.yaml

    3. Create a Subscription object YAML file (for example, eo-sub.yaml) to subscribe a namespace to the OpenShift Elasticsearch Operator.

      Example Subscription
      apiVersion: operators.coreos.com/v1alpha1
kind: Subscription
metadata:
  name: "elasticsearch-operator"
  namespace: "openshift-operators-redhat" (1)
spec:
  channel: "stable-5.1" (2)
  installPlanApproval: "Automatic" (3)
  source: "redhat-operators" (4)
  sourceNamespace: "openshift-marketplace"
  name: "elasticsearch-operator"
      1 You must specify the openshift-operators-redhat namespace.
      2 Specify stable, or stable-5.<x> as the channel. See the following note.
      3 Automatic allows the Operator Lifecycle Manager (OLM) to automatically update the Operator when a new version is available. Manual requires a user with appropriate credentials to approve the Operator update.
      4 Specify redhat-operators. If your OKD cluster is installed on a restricted network, also known as a disconnected cluster, specify the name of the CatalogSource object created when you configured the Operator Lifecycle Manager (OLM).

      Specifying stable installs the current version of the latest stable release. Using stable with installPlanApproval: "Automatic", will automatically upgrade your operators to the latest stable major and minor release.

      Specifying stable-5.<x> installs the current minor version of a specific major release. Using stable-5.<x> with installPlanApproval: "Automatic", will automatically upgrade your operators to the latest stable minor release within the major release you specify with x.

    4. Create the Subscription object:

      $ oc create -f <file-name>.yaml

      For example:

      $ oc create -f eo-sub.yaml

      The OpenShift Elasticsearch Operator is installed to the openshift-operators-redhat namespace and copied to each project in the cluster.

    5. Verify the Operator installation:

      $ oc get csv --all-namespaces
      Example output
      NAMESPACE                                               NAME                                            DISPLAY                  VERSION               REPLACES   PHASE
default                                                 elasticsearch-operator.5.1.0-202007012112.p0    OpenShift Elasticsearch Operator   5.1.0-202007012112.p0               Succeeded
kube-node-lease                                         elasticsearch-operator.5.1.0-202007012112.p0    OpenShift Elasticsearch Operator   5.1.0-202007012112.p0               Succeeded
kube-public                                             elasticsearch-operator.5.1.0-202007012112.p0    OpenShift Elasticsearch Operator   5.1.0-202007012112.p0               Succeeded
kube-system                                             elasticsearch-operator.5.1.0-202007012112.p0    OpenShift Elasticsearch Operator   5.1.0-202007012112.p0               Succeeded
openshift-apiserver-operator                            elasticsearch-operator.5.1.0-202007012112.p0    OpenShift Elasticsearch Operator   5.1.0-202007012112.p0               Succeeded
openshift-apiserver                                     elasticsearch-operator.5.1.0-202007012112.p0    OpenShift Elasticsearch Operator   5.1.0-202007012112.p0               Succeeded
openshift-authentication-operator                       elasticsearch-operator.5.1.0-202007012112.p0    OpenShift Elasticsearch Operator   5.1.0-202007012112.p0               Succeeded
openshift-authentication                                elasticsearch-operator.5.1.0-202007012112.p0    OpenShift Elasticsearch Operator   5.1.0-202007012112.p0               Succeeded
...

      There should be an OpenShift Elasticsearch Operator in each namespace. The version number might be different than shown.

  4. Install the Red Hat OpenShift Logging Operator by creating the following objects:

    1. Create an Operator Group object YAML file (for example, olo-og.yaml) for the Red Hat OpenShift Logging Operator:

      apiVersion: operators.coreos.com/v1
kind: OperatorGroup
metadata:
  name: cluster-logging
  namespace: openshift-logging (1)
spec:
  targetNamespaces:
  - openshift-logging (1)
      1 You must specify the openshift-logging namespace.

    2. Create the OperatorGroup object:

      $ oc create -f <file-name>.yaml

      For example:

      $ oc create -f olo-og.yaml

    3. Create a Subscription object YAML file (for example, olo-sub.yaml) to subscribe a namespace to the Red Hat OpenShift Logging Operator.

      apiVersion: operators.coreos.com/v1alpha1
kind: Subscription
metadata:
  name: cluster-logging
  namespace: openshift-logging (1)
spec:
  channel: "stable" (2)
  name: cluster-logging
  source: redhat-operators (3)
  sourceNamespace: openshift-marketplace
      1 You must specify the openshift-logging namespace.
      2 Specify stable, or stable-5.<x> as the channel.
      3 Specify redhat-operators. If your OKD cluster is installed on a restricted network, also known as a disconnected cluster, specify the name of the CatalogSource object you created when you configured the Operator Lifecycle Manager (OLM). 
      $ oc create -f <file-name>.yaml

      For example:

      $ oc create -f olo-sub.yaml

      The Red Hat OpenShift Logging Operator is installed to the openshift-logging namespace.

    4. Verify the Operator installation.

      There should be a Red Hat OpenShift Logging Operator in the openshift-logging namespace. The Version number might be different than shown.

      $ oc get csv -n openshift-logging
      Example output
      NAMESPACE                                               NAME                                         DISPLAY                  VERSION               REPLACES   PHASE
...
openshift-logging                                       clusterlogging.5.1.0-202007012112.p0         OpenShift Logging          5.1.0-202007012112.p0              Succeeded
...

  5. Create an OpenShift Logging instance:

    1. Create an instance object YAML file (for example, olo-instance.yaml) for the Red Hat OpenShift Logging Operator:

      This default OpenShift Logging configuration should support a wide array of environments. Review the topics on tuning and configuring logging subsystem components for information on modifications you can make to your OpenShift Logging cluster.

      		 
      apiVersion: "logging.openshift.io/v1"
kind: "ClusterLogging"
metadata:
  name: "instance" (1)
  namespace: "openshift-logging"
spec:
  managementState: "Managed"  (2)
  logStore:
    type: "elasticsearch"  (3)
    retentionPolicy: (4)
      application:
        maxAge: 1d
      infra:
        maxAge: 7d
      audit:
        maxAge: 7d
    elasticsearch:
      nodeCount: 3 (5)
      storage:
        storageClassName: "<storage-class-name>" (6)
        size: 200G
      resources: (7)
        limits:
          memory: "16Gi"
        requests:
          memory: "16Gi"
      proxy: (8)
        resources:
          limits:
            memory: 256Mi
          requests:
             memory: 256Mi
      redundancyPolicy: "SingleRedundancy"
  visualization:
    type: "kibana"  (9)
    kibana:
      replicas: 1
  collection:
    logs:
      type: "fluentd"  (10)
      fluentd: {}
      1 The name must be instance.
      2 The OpenShift Logging management state. In some cases, if you change the OpenShift Logging defaults, you must set this to Unmanaged. However, an unmanaged deployment does not receive updates until OpenShift Logging is placed back into a managed state. Placing a deployment back into a managed state might revert any modifications you made.
      3 Settings for configuring Elasticsearch. Using the custom resource (CR), you can configure shard replication policy and persistent storage.
      4 Specify the length of time that Elasticsearch should retain each log source. Enter an integer and a time designation: weeks(w), hours(h/H), minutes(m) and seconds(s). For example, 7d for seven days. Logs older than the maxAge are deleted. You must specify a retention policy for each log source or the Elasticsearch indices will not be created for that source.
      5 Specify the number of Elasticsearch nodes. See the note that follows this list.
      6 Enter the name of an existing storage class for Elasticsearch storage. For best performance, specify a storage class that allocates block storage. If you do not specify a storage class, OKD deploys OpenShift Logging with ephemeral storage only.
      7 Specify the CPU and memory requests for Elasticsearch as needed. If you leave these values blank, the OpenShift Elasticsearch Operator sets default values that are sufficient for most deployments. The default values are 16Gi for the memory request and 1 for the CPU request.
      8 Specify the CPU and memory requests for the Elasticsearch proxy as needed. If you leave these values blank, the OpenShift Elasticsearch Operator sets default values that should be sufficient for most deployments. The default values are 256Mi for the memory request and 100m for the CPU request.
      9 Settings for configuring Kibana. Using the CR, you can scale Kibana for redundancy and configure the CPU and memory for your Kibana pods. For more information, see Configuring the log visualizer.
      10 Settings for configuring Fluentd. Using the CR, you can configure Fluentd CPU and memory limits. For more information, see Configuring Fluentd.

      The maximum number of Elasticsearch control plane nodes is three. If you specify a nodeCount greater than 3, OKD creates three Elasticsearch nodes that are Master-eligible nodes, with the master, client, and data roles. The additional Elasticsearch nodes are created as Data-only nodes, using client and data roles. Control plane nodes perform cluster-wide actions such as creating or deleting an index, shard allocation, and tracking nodes. Data nodes hold the shards and perform data-related operations such as CRUD, search, and aggregations. Data-related operations are I/O-, memory-, and CPU-intensive. It is important to monitor these resources and to add more Data nodes if the current nodes are overloaded.

      For example, if nodeCount=4, the following nodes are created:

      $ oc get deployment
      Example output
      cluster-logging-operator       1/1     1            1           18h
elasticsearch-cd-x6kdekli-1    1/1     1            0           6m54s
elasticsearch-cdm-x6kdekli-1   1/1     1            1           18h
elasticsearch-cdm-x6kdekli-2   1/1     1            0           6m49s
elasticsearch-cdm-x6kdekli-3   1/1     1            0           6m44s

      The number of primary shards for the index templates is equal to the number of Elasticsearch data nodes.

    2. Create the instance:

      $ oc create -f <file-name>.yaml

      For example:

      $ oc create -f olo-instance.yaml

      This creates the logging subsystem components, the Elasticsearch custom resource and components, and the Kibana interface.

  6. Verify the installation by listing the pods in the openshift-logging project.

    You should see several pods for components of the Logging subsystem, similar to the following list:

    $ oc get pods -n openshift-logging
    Example output
    NAME                                            READY   STATUS    RESTARTS   AGE
cluster-logging-operator-66f77ffccb-ppzbg       1/1     Running   0          7m
elasticsearch-cdm-ftuhduuw-1-ffc4b9566-q6bhp    2/2     Running   0          2m40s
elasticsearch-cdm-ftuhduuw-2-7b4994dbfc-rd2gc   2/2     Running   0          2m36s
elasticsearch-cdm-ftuhduuw-3-84b5ff7ff8-gqnm2   2/2     Running   0          2m4s
collector-587vb                                   1/1     Running   0          2m26s
collector-7mpb9                                   1/1     Running   0          2m30s
collector-flm6j                                   1/1     Running   0          2m33s
collector-gn4rn                                   1/1     Running   0          2m26s
collector-nlgb6                                   1/1     Running   0          2m30s
collector-snpkt                                   1/1     Running   0          2m28s
kibana-d6d5668c5-rppqm                          2/2     Running   0          2m39s

Post-installation tasks

If you plan to use Kibana, you must manually create your Kibana index patterns and visualizations to explore and visualize data in Kibana.

If your cluster network provider enforces network isolation, allow network traffic between the projects that contain the logging subsystem Operators.

Defining Kibana index patterns

An index pattern defines the Elasticsearch indices that you want to visualize. To explore and visualize data in Kibana, you must create an index pattern.

Prerequisites

  • A user must have the cluster-admin role, the cluster-reader role, or both roles to view the infra and audit indices in Kibana. The default kubeadmin user has proper permissions to view these indices.

    If you can view the pods and logs in the default, kube- and openshift- projects, you should be able to access these indices. You can use the following command to check if the current user has appropriate permissions:

    $ oc auth can-i get pods/log -n <project>
    Example output
    yes

    The audit logs are not stored in the internal OKD Elasticsearch instance by default. To view the audit logs in Kibana, you must use the Log Forwarding API to configure a pipeline that uses the default output for audit logs.

  • Elasticsearch documents must be indexed before you can create index patterns. This is done automatically, but it might take a few minutes in a new or updated cluster.

Procedure

To define index patterns and create visualizations in Kibana:

  1. In the OKD console, click the Application Launcher app launcher and select Logging.

  2. Create your Kibana index patterns by clicking Management → Index Patterns → Create index pattern:

    • Each user must manually create index patterns when logging into Kibana the first time to see logs for their projects. Users must create an index pattern named app and use the @timestamp time field to view their container logs.

    • Each admin user must create index patterns when logged into Kibana the first time for the app, infra, and audit indices using the @timestamp time field.

  3. Create Kibana Visualizations from the new index patterns.

Allowing traffic between projects when network isolation is enabled

Your cluster network provider might enforce network isolation. If so, you must allow network traffic between the projects that contain the operators deployed by OpenShift Logging.

Network isolation blocks network traffic between pods or services that are in different projects. The logging subsystem installs the OpenShift Elasticsearch Operator in the openshift-operators-redhat project and the Red Hat OpenShift Logging Operator in the openshift-logging project. Therefore, you must allow traffic between these two projects.

OKD offers two supported choices for the default Container Network Interface (CNI) network provider, OpenShift SDN and OVN-Kubernetes. These two providers implement various network isolation policies.

OpenShift SDN has three modes:

network policy

This is the default mode. If no policy is defined, it allows all traffic. However, if a user defines a policy, they typically start by denying all traffic and then adding exceptions. This process might break applications that are running in different projects. Therefore, explicitly configure the policy to allow traffic to egress from one logging-related project to the other.

multitenant

This mode enforces network isolation. You must join the two logging-related projects to allow traffic between them.

subnet

This mode allows all traffic. It does not enforce network isolation. No action is needed.

OVN-Kubernetes always uses a network policy. Therefore, as with OpenShift SDN, you must configure the policy to allow traffic to egress from one logging-related project to the other.

Procedure

  • If you are using OpenShift SDN in multitenant mode, join the two projects. For example:

    $ oc adm pod-network join-projects --to=openshift-operators-redhat openshift-logging

  • Otherwise, for OpenShift SDN in network policy mode and OVN-Kubernetes, perform the following actions:

    1. Set a label on the openshift-operators-redhat namespace. For example:

      $ oc label namespace openshift-operators-redhat project=openshift-operators-redhat

    2. Create a network policy object in the openshift-logging namespace that allows ingress from the openshift-operators-redhat, openshift-monitoring and openshift-ingress projects to the openshift-logging project. For example:

      apiVersion: networking.k8s.io/v1
kind: NetworkPolicy
metadata:
  name: allow-from-openshift-monitoring-ingress-operators-redhat
spec:
  ingress:
  - from:
    - podSelector: {}
  - from:
    - namespaceSelector:
        matchLabels:
          project: "openshift-operators-redhat"
  - from:
    - namespaceSelector:
        matchLabels:
          name: "openshift-monitoring"
  - from:
    - namespaceSelector:
        matchLabels:
          network.openshift.io/policy-group: ingress
  podSelector: {}
  policyTypes:
  - Ingress
Additional resources