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Chapter 2. Logging 6.0

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2.1. Release notes

2.1.1. Logging 6.0.1

This release includes OpenShift Logging Bug Fix Release 6.0.1.

2.1.1.1. Bug fixes

With this update, the default memory limit for the collector has been increased from 1024 Mi to 2024 Mi. However, users should always adjust their resource limits according to their cluster specifications and needs. (LOG-6180)
Before this update, the Loki Operator failed to add the default namespace label to all AlertingRule resources, which caused the User-Workload-Monitoring Alertmanager to skip routing these alerts. This update adds the rule namespace as a label to all alerting and recording rules, resolving the issue and restoring proper alert routing in Alertmanager. (LOG-6151)
Before this update, the LokiStack ruler component view did not initialize properly, causing an invalid field error when the ruler component was disabled. This update ensures that the component view initializes with an empty value, resolving the issue. (LOG-6129)
Before this update, it was possible to set log_source in the prune filter, which could lead to inconsistent log data. With this update, the configuration is validated before being applied, and any configuration that includes log_source in the prune filter is rejected. (LOG-6202)

2.1.1.2. CVEs

2.1.2. Logging 6.0.0

This release includes Logging for Red Hat OpenShift Bug Fix Release 6.0.0

Note

Logging is provided as an installable component, with a distinct release cycle from the core OpenShift Container Platform. The Red Hat OpenShift Container Platform Life Cycle Policy outlines release compatibility.

Table 2.1. Upstream component versions
logging Version	Component Version
Operator	`eventrouter`	`logfilemetricexporter`	`loki`	`lokistack-gateway`	`opa-openshift`	`vector`
6.0	0.4	1.1	3.1.0	0.1	0.1	0.37.1

2.1.3. Removal notice

With this release, logging no longer supports the ClusterLogging.logging.openshift.io and ClusterLogForwarder.logging.openshift.io custom resources. Refer to the product documentation for details on the replacement features. (LOG-5803)
With this release, logging no longer manages or deploys log storage (such as Elasticsearch), visualization (such as Kibana), or Fluentd-based log collectors. (LOG-5368)

Note

In order to continue to use Elasticsearch and Kibana managed by the elasticsearch-operator, the administrator must modify those object’s ownerRefs before deleting the ClusterLogging resource.

2.1.4. New features and enhancements

This feature introduces a new architecture for logging for Red Hat OpenShift by shifting component responsibilities to their relevant Operators, such as for storage, visualization, and collection. It introduces the ClusterLogForwarder.observability.openshift.io API for log collection and forwarding. Support for the ClusterLogging.logging.openshift.io and ClusterLogForwarder.logging.openshift.io APIs, along with the Red Hat managed Elastic stack (Elasticsearch and Kibana), is removed. Users are encouraged to migrate to the Red Hat LokiStack for log storage. Existing managed Elasticsearch deployments can be used for a limited time. Automated migration for log collection is not provided, so administrators need to create a new ClusterLogForwarder.observability.openshift.io specification to replace their previous custom resources. Refer to the official product documentation for more details. (LOG-3493)
With this release, the responsibility for deploying the logging view plugin shifts from the Red Hat OpenShift Logging Operator to the Cluster Observability Operator (COO). For new log storage installations that need visualization, the Cluster Observability Operator and the associated UIPlugin resource must be deployed. Refer to the Cluster Observability Operator Overview product documentation for more details. (LOG-5461)
This enhancement sets default requests and limits for Vector collector deployments' memory and CPU usage based on Vector documentation recommendations. (LOG-4745)
This enhancement updates Vector to align with the upstream version v0.37.1. (LOG-5296)
This enhancement introduces an alert that triggers when log collectors buffer logs to a node’s file system and use over 15% of the available space, indicating potential back pressure issues. (LOG-5381)
This enhancement updates the selectors for all components to use common Kubernetes labels. (LOG-5906)
This enhancement changes the collector configuration to deploy as a ConfigMap instead of a secret, allowing users to view and edit the configuration when the ClusterLogForwarder is set to Unmanaged. (LOG-5599)
This enhancement adds the ability to configure the Vector collector log level using an annotation on the ClusterLogForwarder, with options including trace, debug, info, warn, error, or off. (LOG-5372)
This enhancement adds validation to reject configurations where Amazon CloudWatch outputs use multiple AWS roles, preventing incorrect log routing. (LOG-5640)
This enhancement removes the Log Bytes Collected and Log Bytes Sent graphs from the metrics dashboard. (LOG-5964)
This enhancement updates the must-gather functionality to only capture information for inspecting Logging 6.0 components, including Vector deployments from ClusterLogForwarder.observability.openshift.io resources and the Red Hat managed LokiStack. (LOG-5949)
This enhancement improves Azure storage secret validation by providing early warnings for specific error conditions. (LOG-4571)

2.1.5. Technology Preview features

This release introduces a Technology Preview feature for log forwarding using OpenTelemetry. A new output type,` OTLP`, allows sending JSON-encoded log records using the OpenTelemetry data model and resource semantic conventions. (LOG-4225)

2.1.6. Bug fixes

Before this update, the CollectorHighErrorRate and CollectorVeryHighErrorRate alerts were still present. With this update, both alerts are removed in the logging 6.0 release but might return in a future release. (LOG-3432)

2.1.7. CVEs

CVE-2024-34397

2.2. Logging 6.0

The ClusterLogForwarder custom resource (CR) is the central configuration point for log collection and forwarding.

2.2.1. Inputs and Outputs

Inputs specify the sources of logs to be forwarded. Logging provides built-in input types: application, infrastructure, and audit, which select logs from different parts of your cluster. You can also define custom inputs based on namespaces or pod labels to fine-tune log selection.

Outputs define the destinations where logs are sent. Each output type has its own set of configuration options, allowing you to customize the behavior and authentication settings.

2.2.2. Receiver Input Type

The receiver input type enables the Logging system to accept logs from external sources. It supports two formats for receiving logs: http and syslog.

The ReceiverSpec defines the configuration for a receiver input.

2.2.3. Pipelines and Filters

Pipelines determine the flow of logs from inputs to outputs. A pipeline consists of one or more input refs, output refs, and optional filter refs. Filters can be used to transform or drop log messages within a pipeline. The order of filters matters, as they are applied sequentially, and earlier filters can prevent log messages from reaching later stages.

2.2.4. Operator Behavior

The Cluster Logging Operator manages the deployment and configuration of the collector based on the managementState field:

When set to Managed (default), the operator actively manages the logging resources to match the configuration defined in the spec.
When set to Unmanaged, the operator does not take any action, allowing you to manually manage the logging components.

2.2.5. Validation

Logging includes extensive validation rules and default values to ensure a smooth and error-free configuration experience. The ClusterLogForwarder resource enforces validation checks on required fields, dependencies between fields, and the format of input values. Default values are provided for certain fields, reducing the need for explicit configuration in common scenarios.

2.2.5.1. Quick Start

Prerequisites

Cluster administrator permissions

Procedure

Install the OpenShift Logging and Loki Operators from OperatorHub.

Create a LokiStack custom resource (CR) in the openshift-logging namespace:

apiVersion: loki.grafana.com/v1
kind: LokiStack
metadata:
  name: logging-loki
  namespace: openshift-logging
spec:
  managementState: Managed
  size: 1x.extra-small
  storage:
    schemas:
    - effectiveDate: '2022-06-01'
      version: v13
    secret:
      name: logging-loki-s3
      type: s3
    storageClassName: gp3-csi
  tenants:
    mode: openshift-logging

Create a service account for the collector:

$ oc create sa collector -n openshift-logging

Create a ClusterRole for the collector:

apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRole
metadata:
  name: logging-collector-logs-writer
rules:
- apiGroups:
  - loki.grafana.com
  resourceNames:
  - logs
  resources:
  - application
  - audit
  - infrastructure
  verbs:
  - create

Bind the ClusterRole to the service account:

$ oc adm policy add-cluster-role-to-user logging-collector-logs-writer -z collector

Install the Cluster Observability Operator.

Create a UIPlugin to enable the Log section in the Observe tab:

apiVersion: observability.openshift.io/v1alpha1
kind: UIPlugin
metadata:
  name: logging
spec:
  type: Logging
  logging:
    lokiStack:
      name: logging-loki

Add additional roles to the collector service account:

$ oc project openshift-logging
$ oc adm policy add-cluster-role-to-user collect-application-logs -z collector
$ oc adm policy add-cluster-role-to-user collect-audit-logs -z collector
$ oc adm policy add-cluster-role-to-user collect-infrastructure-logs -z collector

Create a ClusterLogForwarder CR to configure log forwarding:

apiVersion: observability.openshift.io/v1
kind: ClusterLogForwarder
metadata:
  name: collector
  namespace: openshift-logging
spec:
  serviceAccount:
    name: collector
  outputs:
  - name: default-lokistack
    type: lokiStack
    lokiStack:
      target:
        name: logging-loki
        namespace: openshift-logging
    authentication:
      token:
        from: serviceAccount
    tls:
      ca:
        key: service-ca.crt
        configMapName: openshift-service-ca.crt
  pipelines:
  - name: default-logstore
    inputRefs:
    - application
    - infrastructure
    outputRefs:
    - default-lokistack

Verify that logs are visible in the Log section of the Observe tab in the OpenShift web console.

2.3. Upgrading to Logging 6.0

Logging v6.0 is a significant upgrade from previous releases, achieving several longstanding goals of Cluster Logging:

Introduction of distinct operators to manage logging components (e.g., collectors, storage, visualization).
Removal of support for managed log storage and visualization based on Elastic products (i.e., Elasticsearch, Kibana).
Deprecation of the Fluentd log collector implementation.
Removal of support for ClusterLogging.logging.openshift.io and ClusterLogForwarder.logging.openshift.io resources.

Note

The cluster-logging-operator does not provide an automated upgrade process.

Given the various configurations for log collection, forwarding, and storage, no automated upgrade is provided by the cluster-logging-operator. This documentation assists administrators in converting existing ClusterLogging.logging.openshift.io and ClusterLogForwarder.logging.openshift.io specifications to the new API. Examples of migrated ClusterLogForwarder.observability.openshift.io resources for common use cases are included.

2.3.1. Using the `oc explain` command

The oc explain command is an essential tool in the OpenShift CLI oc that provides detailed descriptions of the fields within Custom Resources (CRs). This command is invaluable for administrators and developers who are configuring or troubleshooting resources in an OpenShift cluster.

2.3.1.1. Resource Descriptions

oc explain offers in-depth explanations of all fields associated with a specific object. This includes standard resources like pods and services, as well as more complex entities like statefulsets and custom resources defined by Operators.

To view the documentation for the outputs field of the ClusterLogForwarder custom resource, you can use:

$ oc explain clusterlogforwarders.observability.openshift.io.spec.outputs

Note

In place of clusterlogforwarder the short form obsclf can be used.

This will display detailed information about these fields, including their types, default values, and any associated sub-fields.

2.3.1.2. Hierarchical Structure

The command displays the structure of resource fields in a hierarchical format, clarifying the relationships between different configuration options.

For instance, here’s how you can drill down into the storage configuration for a LokiStack custom resource:

$ oc explain lokistacks.loki.grafana.com
$ oc explain lokistacks.loki.grafana.com.spec
$ oc explain lokistacks.loki.grafana.com.spec.storage
$ oc explain lokistacks.loki.grafana.com.spec.storage.schemas

Each command reveals a deeper level of the resource specification, making the structure clear.

2.3.1.3. Type Information

oc explain also indicates the type of each field (such as string, integer, or boolean), allowing you to verify that resource definitions use the correct data types.

For example:

$ oc explain lokistacks.loki.grafana.com.spec.size

This will show that size should be defined using an integer value.

2.3.1.4. Default Values

When applicable, the command shows the default values for fields, providing insights into what values will be used if none are explicitly specified.

Again using lokistacks.loki.grafana.com as an example:

$ oc explain lokistacks.spec.template.distributor.replicas

Example output

GROUP:      loki.grafana.com
KIND:       LokiStack
VERSION:    v1

FIELD: replicas <integer>

DESCRIPTION:
    Replicas defines the number of replica pods of the component.

2.3.2. Log Storage

The only managed log storage solution available in this release is a Lokistack, managed by the loki-operator. This solution, previously available as the preferred alternative to the managed Elasticsearch offering, remains unchanged in its deployment process.

Important

To continue using an existing Red Hat managed Elasticsearch or Kibana deployment provided by the elasticsearch-operator, remove the owner references from the Elasticsearch resource named elasticsearch, and the Kibana resource named kibana in the openshift-logging namespace before removing the ClusterLogging resource named instance in the same namespace.

Temporarily set ClusterLogging to state Unmanaged

$ oc -n openshift-logging patch clusterlogging/instance -p '{"spec":{"managementState": "Unmanaged"}}' --type=merge

Remove ClusterLogging ownerReferences from the Elasticsearch resource
The following command ensures that ClusterLogging no longer owns the Elasticsearch resource. Updates to the ClusterLogging resource’s logStore field will no longer affect the Elasticsearch resource.
```
$ oc -n openshift-logging patch elasticsearch/elasticsearch -p '{"metadata":{"ownerReferences": []}}' --type=merge
```
Remove ClusterLogging ownerReferences from the Kibana resource
The following command ensures that ClusterLogging no longer owns the Kibana resource. Updates to the ClusterLogging resource’s visualization field will no longer affect the Kibana resource.
```
$ oc -n openshift-logging patch kibana/kibana -p '{"metadata":{"ownerReferences": []}}' --type=merge
```
Set ClusterLogging to state Managed

$ oc -n openshift-logging patch clusterlogging/instance -p '{"spec":{"managementState": "Managed"}}' --type=merge

2.3.3. Log Visualization

The OpenShift console UI plugin for log visualization has been moved to the cluster-observability-operator from the cluster-logging-operator.

2.3.4. Log Collection and Forwarding

Log collection and forwarding configurations are now specified under the new API, part of the observability.openshift.io API group. The following sections highlight the differences from the old API resources.

Note

Vector is the only supported collector implementation.

2.3.5. Management, Resource Allocation, and Workload Scheduling

Configuration for management state (e.g., Managed, Unmanaged), resource requests and limits, tolerations, and node selection is now part of the new ClusterLogForwarder API.

Previous Configuration

apiVersion: "logging.openshift.io/v1"
kind: "ClusterLogging"
spec:
  managementState: "Managed"
  collection:
    resources:
      limits: {}
      requests: {}
    nodeSelector: {}
    tolerations: {}

Current Configuration

apiVersion: "observability.openshift.io/v1"
kind: ClusterLogForwarder
spec:
  managementState: Managed
  collector:
    resources:
      limits: {}
      requests: {}
    nodeSelector: {}
    tolerations: {}

2.3.6. Input Specifications

The input specification is an optional part of the ClusterLogForwarder specification. Administrators can continue to use the predefined values of application, infrastructure, and audit to collect these sources.

2.3.6.1. Application Inputs

Namespace and container inclusions and exclusions have been consolidated into a single field.

5.9 Application Input with Namespace and Container Includes and Excludes

apiVersion: "logging.openshift.io/v1"
kind: ClusterLogForwarder
spec:
  inputs:
   - name: application-logs
     type: application
     application:
       namespaces:
       - foo
       - bar
       includes:
       - namespace: my-important
         container: main
       excludes:
       - container: too-verbose

6.0 Application Input with Namespace and Container Includes and Excludes

apiVersion: "observability.openshift.io/v1"
kind: ClusterLogForwarder
spec:
  inputs:
   - name: application-logs
     type: application
     application:
       includes:
       - namespace: foo
       - namespace: bar
       - namespace: my-important
         container: main
       excludes:
       - container: too-verbose

Note

application, infrastructure, and audit are reserved words and cannot be used as names when defining an input.

2.3.6.2. Input Receivers

Changes to input receivers include:

Explicit configuration of the type at the receiver level.
Port settings moved to the receiver level.

5.9 Input Receivers

apiVersion: "logging.openshift.io/v1"
kind: ClusterLogForwarder
spec:
  inputs:
  - name: an-http
    receiver:
      http:
        port: 8443
        format: kubeAPIAudit
  - name: a-syslog
    receiver:
      type: syslog
      syslog:
        port: 9442

6.0 Input Receivers

apiVersion: "observability.openshift.io/v1"
kind: ClusterLogForwarder
spec:
  inputs:
  - name: an-http
    type: receiver
    receiver:
      type: http
      port: 8443
      http:
        format: kubeAPIAudit
  - name: a-syslog
    type: receiver
    receiver:
      type: syslog
      port: 9442

2.3.7. Output Specifications

High-level changes to output specifications include:

URL settings moved to each output type specification.
Tuning parameters moved to each output type specification.
Separation of TLS configuration from authentication.
Explicit configuration of keys and secret/configmap for TLS and authentication.

2.3.8. Secrets and TLS Configuration

Secrets and TLS configurations are now separated into authentication and TLS configuration for each output. They must be explicitly defined in the specification rather than relying on administrators to define secrets with recognized keys. Upgrading TLS and authorization configurations requires administrators to understand previously recognized keys to continue using existing secrets. Examples in the following sections provide details on how to configure ClusterLogForwarder secrets to forward to existing Red Hat managed log storage solutions.

2.3.9. Red Hat Managed Elasticsearch

v5.9 Forwarding to Red Hat Managed Elasticsearch

apiVersion: logging.openshift.io/v1
kind: ClusterLogging
metadata:
  name: instance
  namespace: openshift-logging
spec:
  logStore:
    type: elasticsearch

v6.0 Forwarding to Red Hat Managed Elasticsearch

apiVersion: observability.openshift.io/v1
kind: ClusterLogForwarder
metadata:
  name: instance
  namespace: openshift-logging
spec:
  outputs:
  - name: default-elasticsearch
    type: elasticsearch
    elasticsearch:
      url: https://elasticsearch:9200
      version: 6
      index: <log_type>-write-{+yyyy.MM.dd}
    tls:
      ca:
        key: ca-bundle.crt
        secretName: collector
      certificate:
        key: tls.crt
        secretName: collector
      key:
        key: tls.key
        secretName: collector
  pipelines:
  - outputRefs:
    - default-elasticsearch
  - inputRefs:
    - application
    - infrastructure

Note

In this example, application logs are written to the application-write alias/index instead of app-write.

2.3.10. Red Hat Managed LokiStack

v5.9 Forwarding to Red Hat Managed LokiStack

apiVersion: logging.openshift.io/v1
kind: ClusterLogging
metadata:
  name: instance
  namespace: openshift-logging
spec:
  logStore:
    type: lokistack
    lokistack:
      name: lokistack-dev

v6.0 Forwarding to Red Hat Managed LokiStack

apiVersion: observability.openshift.io/v1
kind: ClusterLogForwarder
metadata:
  name: instance
  namespace: openshift-logging
spec:
  outputs:
  - name: default-lokistack
    type: lokiStack
    lokiStack:
      target:
        name: lokistack-dev
        namespace: openshift-logging
      authentication:
        token:
          from: serviceAccount
    tls:
      ca:
        key: service-ca.crt
        configMapName: openshift-service-ca.crt
  pipelines:
  - outputRefs:
    - default-lokistack
  - inputRefs:
    - application
    - infrastructure

2.3.11. Filters and Pipeline Configuration

Pipeline configurations now define only the routing of input sources to their output destinations, with any required transformations configured separately as filters. All attributes of pipelines from previous releases have been converted to filters in this release. Individual filters are defined in the filters specification and referenced by a pipeline.

5.9 Filters

apiVersion: logging.openshift.io/v1
kind: ClusterLogForwarder
spec:
  pipelines:
   - name: application-logs
     parse: json
     labels:
       foo: bar
     detectMultilineErrors: true

6.0 Filter Configuration

apiVersion: observability.openshift.io/v1
kind: ClusterLogForwarder
spec:
  filters:
  - name: detectexception
    type: detectMultilineException
  - name: parse-json
    type: parse
  - name: labels
    type: openShiftLabels
    openShiftLabels:
      foo: bar
  pipelines:
  - name: application-logs
    filterRefs:
    - detectexception
    - labels
    - parse-json

2.3.12. Validation and Status

Most validations are enforced when a resource is created or updated, providing immediate feedback. This is a departure from previous releases, where validation occurred post-creation and required inspecting the resource status. Some validation still occurs post-creation for cases where it is not possible to validate at creation or update time.

Instances of the ClusterLogForwarder.observability.openshift.io must satisfy the following conditions before the operator will deploy the log collector: Authorized, Valid, Ready. An example of these conditions is:

6.0 Status Conditions

apiVersion: observability.openshift.io/v1
kind: ClusterLogForwarder
status:
  conditions:
  - lastTransitionTime: "2024-09-13T03:28:44Z"
    message: 'permitted to collect log types: [application]'
    reason: ClusterRolesExist
    status: "True"
    type: observability.openshift.io/Authorized
  - lastTransitionTime: "2024-09-13T12:16:45Z"
    message: ""
    reason: ValidationSuccess
    status: "True"
    type: observability.openshift.io/Valid
  - lastTransitionTime: "2024-09-13T12:16:45Z"
    message: ""
    reason: ReconciliationComplete
    status: "True"
    type: Ready
  filterConditions:
  - lastTransitionTime: "2024-09-13T13:02:59Z"
    message: filter "detectexception" is valid
    reason: ValidationSuccess
    status: "True"
    type: observability.openshift.io/ValidFilter-detectexception
  - lastTransitionTime: "2024-09-13T13:02:59Z"
    message: filter "parse-json" is valid
    reason: ValidationSuccess
    status: "True"
    type: observability.openshift.io/ValidFilter-parse-json
  inputConditions:
  - lastTransitionTime: "2024-09-13T12:23:03Z"
    message: input "application1" is valid
    reason: ValidationSuccess
    status: "True"
    type: observability.openshift.io/ValidInput-application1
  outputConditions:
  - lastTransitionTime: "2024-09-13T13:02:59Z"
    message: output "default-lokistack-application1" is valid
    reason: ValidationSuccess
    status: "True"
    type: observability.openshift.io/ValidOutput-default-lokistack-application1
  pipelineConditions:
  - lastTransitionTime: "2024-09-13T03:28:44Z"
    message: pipeline "default-before" is valid
    reason: ValidationSuccess
    status: "True"
    type: observability.openshift.io/ValidPipeline-default-before

Note

Conditions that are satisfied and applicable have a "status" value of "True". Conditions with a status other than "True" provide a reason and a message explaining the issue.

2.4. Configuring log forwarding

The ClusterLogForwarder (CLF) allows users to configure forwarding of logs to various destinations. It provides a flexible way to select log messages from different sources, send them through a pipeline that can transform or filter them, and forward them to one or more outputs.

Key Functions of the ClusterLogForwarder

Selects log messages using inputs
Forwards logs to external destinations using outputs
Filters, transforms, and drops log messages using filters
Defines log forwarding pipelines connecting inputs, filters and outputs

2.4.1. Setting up log collection

This release of Cluster Logging requires administrators to explicitly grant log collection permissions to the service account associated with ClusterLogForwarder. This was not required in previous releases for the legacy logging scenario consisting of a ClusterLogging and, optionally, a ClusterLogForwarder.logging.openshift.io resource.

The Red Hat OpenShift Logging Operator provides collect-audit-logs, collect-application-logs, and collect-infrastructure-logs cluster roles, which enable the collector to collect audit logs, application logs, and infrastructure logs respectively.

Setup log collection by binding the required cluster roles to your service account.

2.4.1.1. Legacy service accounts

To use the existing legacy service account logcollector, create the following ClusterRoleBinding:

$ oc adm policy add-cluster-role-to-user collect-application-logs system:serviceaccount:openshift-logging:logcollector
$ oc adm policy add-cluster-role-to-user collect-infrastructure-logs system:serviceaccount:openshift-logging:logcollector

Additionally, create the following ClusterRoleBinding if collecting audit logs:

$ oc adm policy add-cluster-role-to-user collect-audit-logs system:serviceaccount:openshift-logging:logcollector

2.4.1.2. Creating service accounts

Prerequisites

The Red Hat OpenShift Logging Operator is installed in the openshift-logging namespace.
You have administrator permissions.

Procedure

Create a service account for the collector. If you want to write logs to storage that requires a token for authentication, you must include a token in the service account.

Bind the appropriate cluster roles to the service account:

Example binding command

$ oc adm policy add-cluster-role-to-user <cluster_role_name> system:serviceaccount:<namespace_name>:<service_account_name>

2.4.1.2.1. Cluster Role Binding for your Service Account

The role_binding.yaml file binds the ClusterLogging operator’s ClusterRole to a specific ServiceAccount, allowing it to manage Kubernetes resources cluster-wide.

apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRoleBinding
metadata:
  name: manager-rolebinding
roleRef:                                           1
  apiGroup: rbac.authorization.k8s.io              2
  kind: ClusterRole                                3
  name: cluster-logging-operator                   4
subjects:                                          5
  - kind: ServiceAccount                           6
    name: cluster-logging-operator                 7
    namespace: openshift-logging                   8

1: roleRef: References the ClusterRole to which the binding applies.
2: apiGroup: Indicates the RBAC API group, specifying that the ClusterRole is part of Kubernetes' RBAC system.
3: kind: Specifies that the referenced role is a ClusterRole, which applies cluster-wide.
4: name: The name of the ClusterRole being bound to the ServiceAccount, here cluster-logging-operator.
5: subjects: Defines the entities (users or service accounts) that are being granted the permissions from the ClusterRole.
6: kind: Specifies that the subject is a ServiceAccount.
7: Name: The name of the ServiceAccount being granted the permissions.
8: namespace: Indicates the namespace where the ServiceAccount is located.

2.4.1.2.2. Writing application logs

The write-application-logs-clusterrole.yaml file defines a ClusterRole that grants permissions to write application logs to the Loki logging application.

apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRole
metadata:
  name: cluster-logging-write-application-logs
rules:                                              1
  - apiGroups:                                      2
      - loki.grafana.com                            3
    resources:                                      4
      - application                                 5
    resourceNames:                                  6
      - logs                                        7
    verbs:                                          8
      - create                                      9
Annotations
<1> rules: Specifies the permissions granted by this ClusterRole.
<2> apiGroups: Refers to the API group loki.grafana.com, which relates to the Loki logging system.
<3> loki.grafana.com: The API group for managing Loki-related resources.
<4> resources: The resource type that the ClusterRole grants permission to interact with.
<5> application: Refers to the application resources within the Loki logging system.
<6> resourceNames: Specifies the names of resources that this role can manage.
<7> logs: Refers to the log resources that can be created.
<8> verbs: The actions allowed on the resources.
<9> create: Grants permission to create new logs in the Loki system.

2.4.1.2.3. Writing audit logs

The write-audit-logs-clusterrole.yaml file defines a ClusterRole that grants permissions to create audit logs in the Loki logging system.

apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRole
metadata:
  name: cluster-logging-write-audit-logs
rules:                                              1
  - apiGroups:                                      2
      - loki.grafana.com                            3
    resources:                                      4
      - audit                                       5
    resourceNames:                                  6
      - logs                                        7
    verbs:                                          8
      - create                                      9

1 1: rules: Defines the permissions granted by this ClusterRole.
2 2: apiGroups: Specifies the API group loki.grafana.com.
3 3: loki.grafana.com: The API group responsible for Loki logging resources.
4 4: resources: Refers to the resource type this role manages, in this case, audit.
5 5: audit: Specifies that the role manages audit logs within Loki.
6 6: resourceNames: Defines the specific resources that the role can access.
7 7: logs: Refers to the logs that can be managed under this role.
8 8: verbs: The actions allowed on the resources.
9 9: create: Grants permission to create new audit logs.

2.4.1.2.4. Writing infrastructure logs

The write-infrastructure-logs-clusterrole.yaml file defines a ClusterRole that grants permission to create infrastructure logs in the Loki logging system.

Sample YAML

apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRole
metadata:
  name: cluster-logging-write-infrastructure-logs
rules:                                              1
  - apiGroups:                                      2
      - loki.grafana.com                            3
    resources:                                      4
      - infrastructure                              5
    resourceNames:                                  6
      - logs                                        7
    verbs:                                          8
      - create                                      9

1: rules: Specifies the permissions this ClusterRole grants.
2: apiGroups: Specifies the API group for Loki-related resources.
3: loki.grafana.com: The API group managing the Loki logging system.
4: resources: Defines the resource type that this role can interact with.
5: infrastructure: Refers to infrastructure-related resources that this role manages.
6: resourceNames: Specifies the names of resources this role can manage.
7: logs: Refers to the log resources related to infrastructure.
8: verbs: The actions permitted by this role.
9: create: Grants permission to create infrastructure logs in the Loki system.

2.4.1.2.5. ClusterLogForwarder editor role

The clusterlogforwarder-editor-role.yaml file defines a ClusterRole that allows users to manage ClusterLogForwarders in OpenShift.

apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRole
metadata:
  name: clusterlogforwarder-editor-role
rules:                                              1
  - apiGroups:                                      2
      - observability.openshift.io                  3
    resources:                                      4
      - clusterlogforwarders                        5
    verbs:                                          6
      - create                                      7
      - delete                                      8
      - get                                         9
      - list                                        10
      - patch                                       11
      - update                                      12
      - watch                                       13

1: rules: Specifies the permissions this ClusterRole grants.
2: apiGroups: Refers to the OpenShift-specific API group
3: obervability.openshift.io: The API group for managing observability resources, like logging.
4: resources: Specifies the resources this role can manage.
5: clusterlogforwarders: Refers to the log forwarding resources in OpenShift.
6: verbs: Specifies the actions allowed on the ClusterLogForwarders.
7: create: Grants permission to create new ClusterLogForwarders.
8: delete: Grants permission to delete existing ClusterLogForwarders.
9: get: Grants permission to retrieve information about specific ClusterLogForwarders.
10: list: Allows listing all ClusterLogForwarders.
11: patch: Grants permission to partially modify ClusterLogForwarders.
12: update: Grants permission to update existing ClusterLogForwarders.
13: watch: Grants permission to monitor changes to ClusterLogForwarders.

2.4.2. Modifying log level in collector

To modify the log level in the collector, you can set the observability.openshift.io/log-level annotation to trace, debug, info, warn, error, and off.

Example log level annotation

apiVersion: observability.openshift.io/v1
kind: ClusterLogForwarder
metadata:
  name: collector
  annotations:
    observability.openshift.io/log-level: debug
# ...

2.4.3. Managing the Operator

The ClusterLogForwarder resource has a managementState field that controls whether the operator actively manages its resources or leaves them Unmanaged:

Managed: (default) The operator will drive the logging resources to match the desired state in the CLF spec.
Unmanaged: The operator will not take any action related to the logging components.

This allows administrators to temporarily pause log forwarding by setting managementState to Unmanaged.

2.4.4. Structure of the ClusterLogForwarder

The CLF has a spec section that contains the following key components:

Inputs: Select log messages to be forwarded. Built-in input types application, infrastructure and audit forward logs from different parts of the cluster. You can also define custom inputs.
Outputs: Define destinations to forward logs to. Each output has a unique name and type-specific configuration.
Pipelines: Define the path logs take from inputs, through filters, to outputs. Pipelines have a unique name and consist of a list of input, output and filter names.
Filters: Transform or drop log messages in the pipeline. Users can define filters that match certain log fields and drop or modify the messages. Filters are applied in the order specified in the pipeline.

2.4.4.1. Inputs

Inputs are configured in an array under spec.inputs. There are three built-in input types:

application: Selects logs from all application containers, excluding those in infrastructure namespaces such as default, openshift, or any namespace with the kube- or openshift- prefix.
infrastructure: Selects logs from infrastructure components running in default and openshift namespaces and node logs.
audit: Selects logs from the OpenShift API server audit logs, Kubernetes API server audit logs, ovn audit logs, and node audit logs from auditd.

Users can define custom inputs of type application that select logs from specific namespaces or using pod labels.

2.4.4.2. Outputs

Outputs are configured in an array under spec.outputs. Each output must have a unique name and a type. Supported types are:

azureMonitor: Forwards logs to Azure Monitor.
cloudwatch: Forwards logs to AWS CloudWatch.
elasticsearch: Forwards logs to an external Elasticsearch instance.
googleCloudLogging: Forwards logs to Google Cloud Logging.
http: Forwards logs to a generic HTTP endpoint.
kafka: Forwards logs to a Kafka broker.
loki: Forwards logs to a Loki logging backend.
lokistack: Forwards logs to the logging supported combination of Loki and web proxy with OpenShift Container Platform authentication integration. LokiStack’s proxy uses OpenShift Container Platform authentication to enforce multi-tenancy
otlp: Forwards logs using the OpenTelemetry Protocol.
splunk: Forwards logs to Splunk.
syslog: Forwards logs to an external syslog server.

Each output type has its own configuration fields.

2.4.4.3. Pipelines

Pipelines are configured in an array under spec.pipelines. Each pipeline must have a unique name and consists of:

inputRefs: Names of inputs whose logs should be forwarded to this pipeline.
outputRefs: Names of outputs to send logs to.
filterRefs: (optional) Names of filters to apply.

The order of filterRefs matters, as they are applied sequentially. Earlier filters can drop messages that will not be processed by later filters.

2.4.4.4. Filters

Filters are configured in an array under spec.filters. They can match incoming log messages based on the value of structured fields and modify or drop them.

Administrators can configure the following types of filters:

2.4.4.5. Enabling multi-line exception detection

Enables multi-line error detection of container logs.

Warning

Enabling this feature could have performance implications and may require additional computing resources or alternate logging solutions.

Log parsers often incorrectly identify separate lines of the same exception as separate exceptions. This leads to extra log entries and an incomplete or inaccurate view of the traced information.

Example java exception

java.lang.NullPointerException: Cannot invoke "String.toString()" because "<param1>" is null
    at testjava.Main.handle(Main.java:47)
    at testjava.Main.printMe(Main.java:19)
    at testjava.Main.main(Main.java:10)

To enable logging to detect multi-line exceptions and reassemble them into a single log entry, ensure that the ClusterLogForwarder Custom Resource (CR) contains a detectMultilineErrors field under the .spec.filters.

Example ClusterLogForwarder CR

apiVersion: "observability.openshift.io/v1"
kind: ClusterLogForwarder
metadata:
  name: <log_forwarder_name>
  namespace: <log_forwarder_namespace>
spec:
  serviceAccount:
    name: <service_account_name>
  filters:
  - name: <name>
    type: detectMultilineException
  pipelines:
    - inputRefs:
        - <input-name>
      name: <pipeline-name>
      filterRefs:
        - <filter-name>
      outputRefs:
        - <output-name>

2.4.4.5.1. Details

When log messages appear as a consecutive sequence forming an exception stack trace, they are combined into a single, unified log record. The first log message’s content is replaced with the concatenated content of all the message fields in the sequence.

The collector supports the following languages:

Java
JS
Ruby
Python
Golang
PHP
Dart

2.4.4.6. Configuring content filters to drop unwanted log records

When the drop filter is configured, the log collector evaluates log streams according to the filters before forwarding. The collector drops unwanted log records that match the specified configuration.

Procedure

Add a configuration for a filter to the filters spec in the ClusterLogForwarder CR.
The following example shows how to configure the ClusterLogForwarder CR to drop log records based on regular expressions:
Example ClusterLogForwarder CR
```
apiVersion: observability.openshift.io/v1
kind: ClusterLogForwarder
metadata:
# ...
spec:
  serviceAccount:
    name: <service_account_name>
  filters:
  - name: <filter_name>
    type: drop 1
    drop: 2
    - test: 3
      - field: .kubernetes.labels."foo-bar/baz" 4
        matches: .+ 5
      - field: .kubernetes.pod_name
        notMatches: "my-pod" 6
  pipelines:
  - name: <pipeline_name> 7
    filterRefs: ["<filter_name>"]
# ...
```
1
Specifies the type of filter. The drop filter drops log records that match the filter configuration.
2
Specifies configuration options for applying the drop filter.
3
Specifies the configuration for tests that are used to evaluate whether a log record is dropped.
If all the conditions specified for a test are true, the test passes and the log record is dropped.
When multiple tests are specified for the drop filter configuration, if any of the tests pass, the record is dropped.
If there is an error evaluating a condition, for example, the field is missing from the log record being evaluated, that condition evaluates to false.
4
Specifies a dot-delimited field path, which is a path to a field in the log record. The path can contain alpha-numeric characters and underscores (a-zA-Z0-9_), for example, .kubernetes.namespace_name. If segments contain characters outside of this range, the segment must be in quotes, for example, .kubernetes.labels."foo.bar-bar/baz". You can include multiple field paths in a single test configuration, but they must all evaluate to true for the test to pass and the drop filter to be applied.
5
Specifies a regular expression. If log records match this regular expression, they are dropped. You can set either the matches or notMatches condition for a single field path, but not both.
6
Specifies a regular expression. If log records do not match this regular expression, they are dropped. You can set either the matches or notMatches condition for a single field path, but not both.
7
Specifies the pipeline that the drop filter is applied to.
Apply the ClusterLogForwarder CR by running the following command:
```
$ oc apply -f <filename>.yaml
```

Additional examples

The following additional example shows how you can configure the drop filter to only keep higher priority log records:

apiVersion: observability.openshift.io/v1
kind: ClusterLogForwarder
metadata:
# ...
spec:
  serviceAccount:
    name: <service_account_name>
  filters:
  - name: important
    type: drop
    drop:
    - test:
      - field: .message
        notMatches: "(?i)critical|error"
      - field: .level
        matches: "info|warning"
# ...

In addition to including multiple field paths in a single test configuration, you can also include additional tests that are treated as OR checks. In the following example, records are dropped if either test configuration evaluates to true. However, for the second test configuration, both field specs must be true for it to be evaluated to true:

apiVersion: observability.openshift.io/v1
kind: ClusterLogForwarder
metadata:
# ...
spec:
  serviceAccount:
    name: <service_account_name>
  filters:
  - name: important
    type: drop
    drop:
    - test:
      - field: .kubernetes.namespace_name
        matches: "^open"
    - test:
      - field: .log_type
        matches: "application"
      - field: .kubernetes.pod_name
        notMatches: "my-pod"
# ...

2.4.4.7. Overview of API audit filter

OpenShift API servers generate audit events for each API call, detailing the request, response, and the identity of the requester, leading to large volumes of data. The API Audit filter uses rules to enable the exclusion of non-essential events and the reduction of event size, facilitating a more manageable audit trail. Rules are checked in order, and checking stops at the first match. The amount of data that is included in an event is determined by the value of the level field:

None: The event is dropped.
Metadata: Audit metadata is included, request and response bodies are removed.
Request: Audit metadata and the request body are included, the response body is removed.
RequestResponse: All data is included: metadata, request body and response body. The response body can be very large. For example, oc get pods -A generates a response body containing the YAML description of every pod in the cluster.

The ClusterLogForwarder custom resource (CR) uses the same format as the standard Kubernetes audit policy, while providing the following additional functions:

Wildcards

Names of users, groups, namespaces, and resources can have a leading or trailing * asterisk character. For example, the namespace openshift-\* matches openshift-apiserver or openshift-authentication. Resource \*/status matches Pod/status or Deployment/status.

Default Rules

Events that do not match any rule in the policy are filtered as follows:

Read-only system events such as get, list, and watch are dropped.
Service account write events that occur within the same namespace as the service account are dropped.
All other events are forwarded, subject to any configured rate limits.

To disable these defaults, either end your rules list with a rule that has only a level field or add an empty rule.

Omit Response Codes: A list of integer status codes to omit. You can drop events based on the HTTP status code in the response by using the OmitResponseCodes field, which lists HTTP status codes for which no events are created. The default value is [404, 409, 422, 429]. If the value is an empty list, [], then no status codes are omitted.

The ClusterLogForwarder CR audit policy acts in addition to the OpenShift Container Platform audit policy. The ClusterLogForwarder CR audit filter changes what the log collector forwards and provides the ability to filter by verb, user, group, namespace, or resource. You can create multiple filters to send different summaries of the same audit stream to different places. For example, you can send a detailed stream to the local cluster log store and a less detailed stream to a remote site.

Note

You must have a cluster role collect-audit-logs to collect the audit logs. The following example provided is intended to illustrate the range of rules possible in an audit policy and is not a recommended configuration.

Example audit policy

apiVersion: observability.openshift.io/v1
kind: ClusterLogForwarder
metadata:
  name: <log_forwarder_name>
  namespace: <log_forwarder_namespace>
spec:
  serviceAccount:
    name: <service_account_name>
  pipelines:
    - name: my-pipeline
      inputRefs: audit 1
      filterRefs: my-policy 2
  filters:
    - name: my-policy
      type: kubeAPIAudit
      kubeAPIAudit:
        # Don't generate audit events for all requests in RequestReceived stage.
        omitStages:
          - "RequestReceived"

        rules:
          # Log pod changes at RequestResponse level
          - level: RequestResponse
            resources:
            - group: ""
              resources: ["pods"]

          # Log "pods/log", "pods/status" at Metadata level
          - level: Metadata
            resources:
            - group: ""
              resources: ["pods/log", "pods/status"]

          # Don't log requests to a configmap called "controller-leader"
          - level: None
            resources:
            - group: ""
              resources: ["configmaps"]
              resourceNames: ["controller-leader"]

          # Don't log watch requests by the "system:kube-proxy" on endpoints or services
          - level: None
            users: ["system:kube-proxy"]
            verbs: ["watch"]
            resources:
            - group: "" # core API group
              resources: ["endpoints", "services"]

          # Don't log authenticated requests to certain non-resource URL paths.
          - level: None
            userGroups: ["system:authenticated"]
            nonResourceURLs:
            - "/api*" # Wildcard matching.
            - "/version"

          # Log the request body of configmap changes in kube-system.
          - level: Request
            resources:
            - group: "" # core API group
              resources: ["configmaps"]
            # This rule only applies to resources in the "kube-system" namespace.
            # The empty string "" can be used to select non-namespaced resources.
            namespaces: ["kube-system"]

          # Log configmap and secret changes in all other namespaces at the Metadata level.
          - level: Metadata
            resources:
            - group: "" # core API group
              resources: ["secrets", "configmaps"]

          # Log all other resources in core and extensions at the Request level.
          - level: Request
            resources:
            - group: "" # core API group
            - group: "extensions" # Version of group should NOT be included.

          # A catch-all rule to log all other requests at the Metadata level.
          - level: Metadata

1: The log types that are collected. The value for this field can be audit for audit logs, application for application logs, infrastructure for infrastructure logs, or a named input that has been defined for your application.
2: The name of your audit policy.

2.4.4.8. Filtering application logs at input by including the label expressions or a matching label key and values

You can include the application logs based on the label expressions or a matching label key and its values by using the input selector.

Procedure

Add a configuration for a filter to the input spec in the ClusterLogForwarder CR.

The following example shows how to configure the ClusterLogForwarder CR to include logs based on label expressions or matched label key/values:

Example ClusterLogForwarder CR

apiVersion: observability.openshift.io/v1
kind: ClusterLogForwarder
# ...
spec:
  serviceAccount:
    name: <service_account_name>
  inputs:
    - name: mylogs
      application:
        selector:
          matchExpressions:
          - key: env 1
            operator: In 2
            values: ["prod", "qa"] 3
          - key: zone
            operator: NotIn
            values: ["east", "west"]
          matchLabels: 4
            app: one
            name: app1
      type: application
# ...

1: Specifies the label key to match.
2: Specifies the operator. Valid values include: In, NotIn, Exists, and DoesNotExist.
3: Specifies an array of string values. If the operator value is either Exists or DoesNotExist, the value array must be empty.
4: Specifies an exact key or value mapping.

Apply the ClusterLogForwarder CR by running the following command:
```
$ oc apply -f <filename>.yaml
```

2.4.4.9. Configuring content filters to prune log records

When the prune filter is configured, the log collector evaluates log streams according to the filters before forwarding. The collector prunes log records by removing low value fields such as pod annotations.

Procedure

Add a configuration for a filter to the prune spec in the ClusterLogForwarder CR.
The following example shows how to configure the ClusterLogForwarder CR to prune log records based on field paths:
Important
If both are specified, records are pruned based on the notIn array first, which takes precedence over the in array. After records have been pruned by using the notIn array, they are then pruned by using the in array.
Example ClusterLogForwarder CR
```
apiVersion: observability.openshift.io/v1
kind: ClusterLogForwarder
metadata:
# ...
spec:
  serviceAccount:
    name: <service_account_name>
  filters:
  - name: <filter_name>
    type: prune 1
    prune: 2
      in: [.kubernetes.annotations, .kubernetes.namespace_id] 3
      notIn: [.kubernetes,.log_type,.message,."@timestamp"] 4
  pipelines:
  - name: <pipeline_name> 5
    filterRefs: ["<filter_name>"]
# ...
```
1
Specify the type of filter. The prune filter prunes log records by configured fields.
2
Specify configuration options for applying the prune filter. The in and notIn fields are specified as arrays of dot-delimited field paths, which are paths to fields in log records. These paths can contain alpha-numeric characters and underscores (a-zA-Z0-9_), for example, .kubernetes.namespace_name. If segments contain characters outside of this range, the segment must be in quotes, for example, .kubernetes.labels."foo.bar-bar/baz".
3
Optional: Any fields that are specified in this array are removed from the log record.
4
Optional: Any fields that are not specified in this array are removed from the log record.
5
Specify the pipeline that the prune filter is applied to.
Note
The filters exempts the log_type, .log_source, and .message fields.
Apply the ClusterLogForwarder CR by running the following command:
```
$ oc apply -f <filename>.yaml
```

2.4.5. Filtering the audit and infrastructure log inputs by source

You can define the list of audit and infrastructure sources to collect the logs by using the input selector.

Procedure

Add a configuration to define the audit and infrastructure sources in the ClusterLogForwarder CR.
The following example shows how to configure the ClusterLogForwarder CR to define audit and infrastructure sources:
Example ClusterLogForwarder CR
```
apiVersion: observability.openshift.io/v1
kind: ClusterLogForwarder
# ...
spec:
  serviceAccount:
    name: <service_account_name>
  inputs:
    - name: mylogs1
      type: infrastructure
      infrastructure:
        sources: 1
          - node
    - name: mylogs2
      type: audit
      audit:
        sources: 2
          - kubeAPI
          - openshiftAPI
          - ovn
# ...
```
1
Specifies the list of infrastructure sources to collect. The valid sources include:
node: Journal log from the node
container: Logs from the workloads deployed in the namespaces
2
Specifies the list of audit sources to collect. The valid sources include:
kubeAPI: Logs from the Kubernetes API servers
openshiftAPI: Logs from the OpenShift API servers
auditd: Logs from a node auditd service
ovn: Logs from an open virtual network service
Apply the ClusterLogForwarder CR by running the following command:
```
$ oc apply -f <filename>.yaml
```

2.4.6. Filtering application logs at input by including or excluding the namespace or container name

You can include or exclude the application logs based on the namespace and container name by using the input selector.

Procedure

Add a configuration to include or exclude the namespace and container names in the ClusterLogForwarder CR.
The following example shows how to configure the ClusterLogForwarder CR to include or exclude namespaces and container names:
Example ClusterLogForwarder CR
```
apiVersion: observability.openshift.io/v1
kind: ClusterLogForwarder
# ...
spec:
  serviceAccount:
    name: <service_account_name>
  inputs:
    - name: mylogs
      application:
        includes:
          - namespace: "my-project" 1
            container: "my-container" 2
        excludes:
          - container: "other-container*" 3
            namespace: "other-namespace" 4
# ...
```
1
Specifies that the logs are only collected from these namespaces.
2
Specifies that the logs are only collected from these containers.
3
Specifies the pattern of namespaces to ignore when collecting the logs.
4
Specifies the set of containers to ignore when collecting the logs.
Note
The excludes field takes precedence over the includes field.
Apply the ClusterLogForwarder CR by running the following command:
```
$ oc apply -f <filename>.yaml
```

2.5. Storing logs with LokiStack

You can configure a LokiStack CR to store application, audit, and infrastructure-related logs.

2.5.1. Prerequisites

You have installed the Loki Operator by using the CLI or web console.
You have a serviceAccount in the same namespace in which you create the ClusterLogForwarder.
The serviceAccount is assigned collect-audit-logs, collect-application-logs, and collect-infrastructure-logs cluster roles.

2.5.1.1. Core Setup and Configuration

Role-based access controls, basic monitoring, and pod placement to deploy Loki.

2.5.2. Authorizing LokiStack rules RBAC permissions

Administrators can allow users to create and manage their own alerting and recording rules by binding cluster roles to usernames. Cluster roles are defined as ClusterRole objects that contain necessary role-based access control (RBAC) permissions for users.

The following cluster roles for alerting and recording rules are available for LokiStack:

Rule name	Description
`alertingrules.loki.grafana.com-v1-admin`	Users with this role have administrative-level access to manage alerting rules. This cluster role grants permissions to create, read, update, delete, list, and watch `AlertingRule` resources within the `loki.grafana.com/v1` API group.
`alertingrules.loki.grafana.com-v1-crdview`	Users with this role can view the definitions of Custom Resource Definitions (CRDs) related to `AlertingRule` resources within the `loki.grafana.com/v1` API group, but do not have permissions for modifying or managing these resources.
`alertingrules.loki.grafana.com-v1-edit`	Users with this role have permission to create, update, and delete `AlertingRule` resources.
`alertingrules.loki.grafana.com-v1-view`	Users with this role can read `AlertingRule` resources within the `loki.grafana.com/v1` API group. They can inspect configurations, labels, and annotations for existing alerting rules but cannot make any modifications to them.
`recordingrules.loki.grafana.com-v1-admin`	Users with this role have administrative-level access to manage recording rules. This cluster role grants permissions to create, read, update, delete, list, and watch `RecordingRule` resources within the `loki.grafana.com/v1` API group.
`recordingrules.loki.grafana.com-v1-crdview`	Users with this role can view the definitions of Custom Resource Definitions (CRDs) related to `RecordingRule` resources within the `loki.grafana.com/v1` API group, but do not have permissions for modifying or managing these resources.
`recordingrules.loki.grafana.com-v1-edit`	Users with this role have permission to create, update, and delete `RecordingRule` resources.
`recordingrules.loki.grafana.com-v1-view`	Users with this role can read `RecordingRule` resources within the `loki.grafana.com/v1` API group. They can inspect configurations, labels, and annotations for existing alerting rules but cannot make any modifications to them.

2.5.2.1. Examples

To apply cluster roles for a user, you must bind an existing cluster role to a specific username.

Cluster roles can be cluster or namespace scoped, depending on which type of role binding you use. When a RoleBinding object is used, as when using the oc adm policy add-role-to-user command, the cluster role only applies to the specified namespace. When a ClusterRoleBinding object is used, as when using the oc adm policy add-cluster-role-to-user command, the cluster role applies to all namespaces in the cluster.

The following example command gives the specified user create, read, update and delete (CRUD) permissions for alerting rules in a specific namespace in the cluster:

Example cluster role binding command for alerting rule CRUD permissions in a specific namespace

$ oc adm policy add-role-to-user alertingrules.loki.grafana.com-v1-admin -n <namespace> <username>

The following command gives the specified user administrator permissions for alerting rules in all namespaces:

Example cluster role binding command for administrator permissions

$ oc adm policy add-cluster-role-to-user alertingrules.loki.grafana.com-v1-admin <username>

2.5.3. Creating a log-based alerting rule with Loki

The AlertingRule CR contains a set of specifications and webhook validation definitions to declare groups of alerting rules for a single LokiStack instance. In addition, the webhook validation definition provides support for rule validation conditions:

If an AlertingRule CR includes an invalid interval period, it is an invalid alerting rule
If an AlertingRule CR includes an invalid for period, it is an invalid alerting rule.
If an AlertingRule CR includes an invalid LogQL expr, it is an invalid alerting rule.
If an AlertingRule CR includes two groups with the same name, it is an invalid alerting rule.
If none of the above applies, an alerting rule is considered valid.

Table 2.2. AlertingRule definitions
Tenant type	Valid namespaces for `AlertingRule` CRs
application	`<your_application_namespace>`
audit	`openshift-logging`
infrastructure	`openshift-/`, `kube-/\`, `default`

Procedure

Create an AlertingRule custom resource (CR):

Example infrastructure AlertingRule CR

  apiVersion: loki.grafana.com/v1
  kind: AlertingRule
  metadata:
    name: loki-operator-alerts
    namespace: openshift-operators-redhat 1
    labels: 2
      openshift.io/<label_name>: "true"
  spec:
    tenantID: "infrastructure" 3
    groups:
      - name: LokiOperatorHighReconciliationError
        rules:
          - alert: HighPercentageError
            expr: | 4
              sum(rate({kubernetes_namespace_name="openshift-operators-redhat", kubernetes_pod_name=~"loki-operator-controller-manager.*"} |= "error" [1m])) by (job)
                /
              sum(rate({kubernetes_namespace_name="openshift-operators-redhat", kubernetes_pod_name=~"loki-operator-controller-manager.*"}[1m])) by (job)
                > 0.01
            for: 10s
            labels:
              severity: critical 5
            annotations:
              summary: High Loki Operator Reconciliation Errors 6
              description: High Loki Operator Reconciliation Errors 7

1: The namespace where this AlertingRule CR is created must have a label matching the LokiStack spec.rules.namespaceSelector definition.
2: The labels block must match the LokiStack spec.rules.selector definition.
3: AlertingRule CRs for infrastructure tenants are only supported in the openshift-*, kube-\*, or default namespaces.
4: The value for kubernetes_namespace_name: must match the value for metadata.namespace.
5: The value of this mandatory field must be critical, warning, or info.
6: This field is mandatory.
7: This field is mandatory.

Example application AlertingRule CR

  apiVersion: loki.grafana.com/v1
  kind: AlertingRule
  metadata:
    name: app-user-workload
    namespace: app-ns 1
    labels: 2
      openshift.io/<label_name>: "true"
  spec:
    tenantID: "application"
    groups:
      - name: AppUserWorkloadHighError
        rules:
          - alert:
            expr: | 3
              sum(rate({kubernetes_namespace_name="app-ns", kubernetes_pod_name=~"podName.*"} |= "error" [1m])) by (job)
            for: 10s
            labels:
              severity: critical 4
            annotations:
              summary:  5
              description:  6

1: The namespace where this AlertingRule CR is created must have a label matching the LokiStack spec.rules.namespaceSelector definition.
2: The labels block must match the LokiStack spec.rules.selector definition.
3: Value for kubernetes_namespace_name: must match the value for metadata.namespace.
4: The value of this mandatory field must be critical, warning, or info.
5: The value of this mandatory field is a summary of the rule.
6: The value of this mandatory field is a detailed description of the rule.

Apply the AlertingRule CR:
```
$ oc apply -f <filename>.yaml
```

2.5.4. Configuring Loki to tolerate memberlist creation failure

In an OpenShift Container Platform cluster, administrators generally use a non-private IP network range. As a result, the LokiStack memberlist configuration fails because, by default, it only uses private IP networks.

As an administrator, you can select the pod network for the memberlist configuration. You can modify the LokiStack custom resource (CR) to use the podIP address in the hashRing spec. To configure the LokiStack CR, use the following command:

$ oc patch LokiStack logging-loki -n openshift-logging  --type=merge -p '{"spec": {"hashRing":{"memberlist":{"instanceAddrType":"podIP"},"type":"memberlist"}}}'

Example LokiStack to include podIP

apiVersion: loki.grafana.com/v1
kind: LokiStack
metadata:
  name: logging-loki
  namespace: openshift-logging
spec:
# ...
  hashRing:
    type: memberlist
    memberlist:
      instanceAddrType: podIP
# ...

2.5.5. Enabling stream-based retention with Loki

You can configure retention policies based on log streams. Rules for these may be set globally, per-tenant, or both. If you configure both, tenant rules apply before global rules.

Important

If there is no retention period defined on the s3 bucket or in the LokiStack custom resource (CR), then the logs are not pruned and they stay in the s3 bucket forever, which might fill up the s3 storage.

Note

Schema v13 is recommended.

Procedure

Create a LokiStack CR:

Enable stream-based retention globally as shown in the following example:

Example global stream-based retention for AWS

apiVersion: loki.grafana.com/v1
kind: LokiStack
metadata:
  name: logging-loki
  namespace: openshift-logging
spec:
  limits:
   global: 1
      retention: 2
        days: 20
        streams:
        - days: 4
          priority: 1
          selector: '{kubernetes_namespace_name=~"test.+"}' 3
        - days: 1
          priority: 1
          selector: '{log_type="infrastructure"}'
  managementState: Managed
  replicationFactor: 1
  size: 1x.small
  storage:
    schemas:
    - effectiveDate: "2020-10-11"
      version: v13
    secret:
      name: logging-loki-s3
      type: aws
  storageClassName: gp3-csi
  tenants:
    mode: openshift-logging

1: Sets retention policy for all log streams. Note: This field does not impact the retention period for stored logs in object storage.
2: Retention is enabled in the cluster when this block is added to the CR.
3: Contains the LogQL query used to define the log stream.spec: limits:

Enable stream-based retention per-tenant basis as shown in the following example:

Example per-tenant stream-based retention for AWS

apiVersion: loki.grafana.com/v1
kind: LokiStack
metadata:
  name: logging-loki
  namespace: openshift-logging
spec:
  limits:
    global:
      retention:
        days: 20
    tenants: 1
      application:
        retention:
          days: 1
          streams:
            - days: 4
              selector: '{kubernetes_namespace_name=~"test.+"}' 2
      infrastructure:
        retention:
          days: 5
          streams:
            - days: 1
              selector: '{kubernetes_namespace_name=~"openshift-cluster.+"}'
  managementState: Managed
  replicationFactor: 1
  size: 1x.small
  storage:
    schemas:
    - effectiveDate: "2020-10-11"
      version: v13
    secret:
      name: logging-loki-s3
      type: aws
  storageClassName: gp3-csi
  tenants:
    mode: openshift-logging

1: Sets retention policy by tenant. Valid tenant types are application, audit, and infrastructure.
2: Contains the LogQL query used to define the log stream.

Apply the LokiStack CR:
```
$ oc apply -f <filename>.yaml
```
Note
This is not for managing the retention for stored logs. Global retention periods for stored logs to a supported maximum of 30 days is configured with your object storage.

2.5.6. Loki pod placement

You can control which nodes the Loki pods run on, and prevent other workloads from using those nodes, by using tolerations or node selectors on the pods.

You can apply tolerations to the log store pods with the LokiStack custom resource (CR) and apply taints to a node with the node specification. A taint on a node is a key:value pair that instructs the node to repel all pods that do not allow the taint. Using a specific key:value pair that is not on other pods ensures that only the log store pods can run on that node.

Example LokiStack with node selectors

apiVersion: loki.grafana.com/v1
kind: LokiStack
metadata:
  name: logging-loki
  namespace: openshift-logging
spec:
# ...
  template:
    compactor: 1
      nodeSelector:
        node-role.kubernetes.io/infra: "" 2
    distributor:
      nodeSelector:
        node-role.kubernetes.io/infra: ""
    gateway:
      nodeSelector:
        node-role.kubernetes.io/infra: ""
    indexGateway:
      nodeSelector:
        node-role.kubernetes.io/infra: ""
    ingester:
      nodeSelector:
        node-role.kubernetes.io/infra: ""
    querier:
      nodeSelector:
        node-role.kubernetes.io/infra: ""
    queryFrontend:
      nodeSelector:
        node-role.kubernetes.io/infra: ""
    ruler:
      nodeSelector:
        node-role.kubernetes.io/infra: ""
# ...

1: Specifies the component pod type that applies to the node selector.
2: Specifies the pods that are moved to nodes containing the defined label.

Example LokiStack CR with node selectors and tolerations

apiVersion: loki.grafana.com/v1
kind: LokiStack
metadata:
  name: logging-loki
  namespace: openshift-logging
spec:
# ...
  template:
    compactor:
      nodeSelector:
        node-role.kubernetes.io/infra: ""
      tolerations:
      - effect: NoSchedule
        key: node-role.kubernetes.io/infra
        value: reserved
      - effect: NoExecute
        key: node-role.kubernetes.io/infra
        value: reserved
    distributor:
      nodeSelector:
        node-role.kubernetes.io/infra: ""
      tolerations:
      - effect: NoSchedule
        key: node-role.kubernetes.io/infra
        value: reserved
      - effect: NoExecute
        key: node-role.kubernetes.io/infra
        value: reserved
      nodeSelector:
        node-role.kubernetes.io/infra: ""
      tolerations:
      - effect: NoSchedule
        key: node-role.kubernetes.io/infra
        value: reserved
      - effect: NoExecute
        key: node-role.kubernetes.io/infra
        value: reserved
    indexGateway:
      nodeSelector:
        node-role.kubernetes.io/infra: ""
      tolerations:
      - effect: NoSchedule
        key: node-role.kubernetes.io/infra
        value: reserved
      - effect: NoExecute
        key: node-role.kubernetes.io/infra
        value: reserved
    ingester:
      nodeSelector:
        node-role.kubernetes.io/infra: ""
      tolerations:
      - effect: NoSchedule
        key: node-role.kubernetes.io/infra
        value: reserved
      - effect: NoExecute
        key: node-role.kubernetes.io/infra
        value: reserved
    querier:
      nodeSelector:
        node-role.kubernetes.io/infra: ""
      tolerations:
      - effect: NoSchedule
        key: node-role.kubernetes.io/infra
        value: reserved
      - effect: NoExecute
        key: node-role.kubernetes.io/infra
        value: reserved
    queryFrontend:
      nodeSelector:
        node-role.kubernetes.io/infra: ""
      tolerations:
      - effect: NoSchedule
        key: node-role.kubernetes.io/infra
        value: reserved
      - effect: NoExecute
        key: node-role.kubernetes.io/infra
        value: reserved
    ruler:
      nodeSelector:
        node-role.kubernetes.io/infra: ""
      tolerations:
      - effect: NoSchedule
        key: node-role.kubernetes.io/infra
        value: reserved
      - effect: NoExecute
        key: node-role.kubernetes.io/infra
        value: reserved
    gateway:
      nodeSelector:
        node-role.kubernetes.io/infra: ""
      tolerations:
      - effect: NoSchedule
        key: node-role.kubernetes.io/infra
        value: reserved
      - effect: NoExecute
        key: node-role.kubernetes.io/infra
        value: reserved
# ...

To configure the nodeSelector and tolerations fields of the LokiStack (CR), you can use the oc explain command to view the description and fields for a particular resource:

$ oc explain lokistack.spec.template

Example output

KIND:     LokiStack
VERSION:  loki.grafana.com/v1

RESOURCE: template <Object>

DESCRIPTION:
     Template defines the resource/limits/tolerations/nodeselectors per
     component

FIELDS:
   compactor	<Object>
     Compactor defines the compaction component spec.

   distributor	<Object>
     Distributor defines the distributor component spec.
...

For more detailed information, you can add a specific field:

$ oc explain lokistack.spec.template.compactor

Example output

KIND:     LokiStack
VERSION:  loki.grafana.com/v1

RESOURCE: compactor <Object>

DESCRIPTION:
     Compactor defines the compaction component spec.

FIELDS:
   nodeSelector	<map[string]string>
     NodeSelector defines the labels required by a node to schedule the
     component onto it.
...

2.5.6.1. Enhanced Reliability and Performance

Configurations to ensure Loki’s reliability and efficiency in production.

2.5.7. Enabling authentication to cloud-based log stores using short-lived tokens

Workload identity federation enables authentication to cloud-based log stores using short-lived tokens.

Procedure

Use one of the following options to enable authentication:

If you use the OpenShift Container Platform web console to install the Loki Operator, clusters that use short-lived tokens are automatically detected. You are prompted to create roles and supply the data required for the Loki Operator to create a CredentialsRequest object, which populates a secret.

If you use the OpenShift CLI (oc) to install the Loki Operator, you must manually create a Subscription object using the appropriate template for your storage provider, as shown in the following examples. This authentication strategy is only supported for the storage providers indicated.

Example Azure sample subscription

apiVersion: operators.coreos.com/v1alpha1
kind: Subscription
metadata:
  name: loki-operator
  namespace: openshift-operators-redhat
spec:
  channel: "stable-6.0"
  installPlanApproval: Manual
  name: loki-operator
  source: redhat-operators
  sourceNamespace: openshift-marketplace
  config:
    env:
      - name: CLIENTID
        value: <your_client_id>
      - name: TENANTID
        value: <your_tenant_id>
      - name: SUBSCRIPTIONID
        value: <your_subscription_id>
      - name: REGION
        value: <your_region>

Example AWS sample subscription

apiVersion: operators.coreos.com/v1alpha1
kind: Subscription
metadata:
  name: loki-operator
  namespace: openshift-operators-redhat
spec:
  channel: "stable-6.0"
  installPlanApproval: Manual
  name: loki-operator
  source: redhat-operators
  sourceNamespace: openshift-marketplace
  config:
    env:
    - name: ROLEARN
      value: <role_ARN>

2.5.8. Configuring Loki to tolerate node failure

The Loki Operator supports setting pod anti-affinity rules to request that pods of the same component are scheduled on different available nodes in the cluster.

Affinity is a property of pods that controls the nodes on which they prefer to be scheduled. Anti-affinity is a property of pods that prevents a pod from being scheduled on a node.

In OpenShift Container Platform, pod affinity and pod anti-affinity allow you to constrain which nodes your pod is eligible to be scheduled on based on the key-value labels on other pods.

The Operator sets default, preferred podAntiAffinity rules for all Loki components, which includes the compactor, distributor, gateway, indexGateway, ingester, querier, queryFrontend, and ruler components.

You can override the preferred podAntiAffinity settings for Loki components by configuring required settings in the requiredDuringSchedulingIgnoredDuringExecution field:

Example user settings for the ingester component

apiVersion: loki.grafana.com/v1
kind: LokiStack
metadata:
  name: logging-loki
  namespace: openshift-logging
spec:
# ...
  template:
    ingester:
      podAntiAffinity:
      # ...
        requiredDuringSchedulingIgnoredDuringExecution: 1
        - labelSelector:
            matchLabels: 2
              app.kubernetes.io/component: ingester
          topologyKey: kubernetes.io/hostname
# ...

1: The stanza to define a required rule.
2: The key-value pair (label) that must be matched to apply the rule.

2.5.9. LokiStack behavior during cluster restarts

When an OpenShift Container Platform cluster is restarted, LokiStack ingestion and the query path continue to operate within the available CPU and memory resources available for the node. This means that there is no downtime for the LokiStack during OpenShift Container Platform cluster updates. This behavior is achieved by using PodDisruptionBudget resources. The Loki Operator provisions PodDisruptionBudget resources for Loki, which determine the minimum number of pods that must be available per component to ensure normal operations under certain conditions.

2.5.9.1. Advanced Deployment and Scalability

Specialized configurations for high availability, scalability, and error handling.

2.5.10. Zone aware data replication

The Loki Operator offers support for zone-aware data replication through pod topology spread constraints. Enabling this feature enhances reliability and safeguards against log loss in the event of a single zone failure. When configuring the deployment size as 1x.extra-small, 1x.small, or 1x.medium, the replication.factor field is automatically set to 2.

To ensure proper replication, you need to have at least as many availability zones as the replication factor specifies. While it is possible to have more availability zones than the replication factor, having fewer zones can lead to write failures. Each zone should host an equal number of instances for optimal operation.

Example LokiStack CR with zone replication enabled

apiVersion: loki.grafana.com/v1
kind: LokiStack
metadata:
 name: logging-loki
 namespace: openshift-logging
spec:
 replicationFactor: 2 1
 replication:
   factor: 2 2
   zones:
   -  maxSkew: 1 3
      topologyKey: topology.kubernetes.io/zone 4

1: Deprecated field, values entered are overwritten by replication.factor.
2: This value is automatically set when deployment size is selected at setup.
3: The maximum difference in number of pods between any two topology domains. The default is 1, and you cannot specify a value of 0.
4: Defines zones in the form of a topology key that corresponds to a node label.

2.5.11. Recovering Loki pods from failed zones

In OpenShift Container Platform a zone failure happens when specific availability zone resources become inaccessible. Availability zones are isolated areas within a cloud provider’s data center, aimed at enhancing redundancy and fault tolerance. If your OpenShift Container Platform cluster is not configured to handle this, a zone failure can lead to service or data loss.

Loki pods are part of a StatefulSet, and they come with Persistent Volume Claims (PVCs) provisioned by a StorageClass object. Each Loki pod and its PVCs reside in the same zone. When a zone failure occurs in a cluster, the StatefulSet controller automatically attempts to recover the affected pods in the failed zone.

Warning

The following procedure will delete the PVCs in the failed zone, and all data contained therein. To avoid complete data loss the replication factor field of the LokiStack CR should always be set to a value greater than 1 to ensure that Loki is replicating.

Prerequisites

Verify your LokiStack CR has a replication factor greater than 1.
Zone failure detected by the control plane, and nodes in the failed zone are marked by cloud provider integration.

The StatefulSet controller automatically attempts to reschedule pods in a failed zone. Because the associated PVCs are also in the failed zone, automatic rescheduling to a different zone does not work. You must manually delete the PVCs in the failed zone to allow successful re-creation of the stateful Loki Pod and its provisioned PVC in the new zone.

Procedure

List the pods in Pending status by running the following command:

$ oc get pods --field-selector status.phase==Pending -n openshift-logging

Example oc get pods output

NAME                           READY   STATUS    RESTARTS   AGE 1
logging-loki-index-gateway-1   0/1     Pending   0          17m
logging-loki-ingester-1        0/1     Pending   0          16m
logging-loki-ruler-1           0/1     Pending   0          16m

1: These pods are in Pending status because their corresponding PVCs are in the failed zone.

List the PVCs in Pending status by running the following command:

$ oc get pvc -o=json -n openshift-logging | jq '.items[] | select(.status.phase == "Pending") | .metadata.name' -r

Example oc get pvc output

storage-logging-loki-index-gateway-1
storage-logging-loki-ingester-1
wal-logging-loki-ingester-1
storage-logging-loki-ruler-1
wal-logging-loki-ruler-1

Delete the PVC(s) for a pod by running the following command:
```
$ oc delete pvc <pvc_name>  -n openshift-logging
```
Delete the pod(s) by running the following command:
```
$ oc delete pod <pod_name>  -n openshift-logging
```
Once these objects have been successfully deleted, they should automatically be rescheduled in an available zone.

2.5.11.1. Troubleshooting PVC in a terminating state

The PVCs might hang in the terminating state without being deleted, if PVC metadata finalizers are set to kubernetes.io/pv-protection. Removing the finalizers should allow the PVCs to delete successfully.

Remove the finalizer for each PVC by running the command below, then retry deletion.

$ oc patch pvc <pvc_name> -p '{"metadata":{"finalizers":null}}' -n openshift-logging

2.5.12. Troubleshooting Loki rate limit errors

If the Log Forwarder API forwards a large block of messages that exceeds the rate limit to Loki, Loki generates rate limit (429) errors.

These errors can occur during normal operation. For example, when adding the logging to a cluster that already has some logs, rate limit errors might occur while the logging tries to ingest all of the existing log entries. In this case, if the rate of addition of new logs is less than the total rate limit, the historical data is eventually ingested, and the rate limit errors are resolved without requiring user intervention.

In cases where the rate limit errors continue to occur, you can fix the issue by modifying the LokiStack custom resource (CR).

Important

The LokiStack CR is not available on Grafana-hosted Loki. This topic does not apply to Grafana-hosted Loki servers.

Conditions

The Log Forwarder API is configured to forward logs to Loki.

Your system sends a block of messages that is larger than 2 MB to Loki. For example:

"values":[["1630410392689800468","{\"kind\":\"Event\",\"apiVersion\":\
.......
......
......
......
\"received_at\":\"2021-08-31T11:46:32.800278+00:00\",\"version\":\"1.7.4 1.6.0\"}},\"@timestamp\":\"2021-08-31T11:46:32.799692+00:00\",\"viaq_index_name\":\"audit-write\",\"viaq_msg_id\":\"MzFjYjJkZjItNjY0MC00YWU4LWIwMTEtNGNmM2E5ZmViMGU4\",\"log_type\":\"audit\"}"]]}]}

After you enter oc logs -n openshift-logging -l component=collector, the collector logs in your cluster show a line containing one of the following error messages:

429 Too Many Requests Ingestion rate limit exceeded

Example Vector error message

2023-08-25T16:08:49.301780Z  WARN sink{component_kind="sink" component_id=default_loki_infra component_type=loki component_name=default_loki_infra}: vector::sinks::util::retries: Retrying after error. error=Server responded with an error: 429 Too Many Requests internal_log_rate_limit=true

Example Fluentd error message

2023-08-30 14:52:15 +0000 [warn]: [default_loki_infra] failed to flush the buffer. retry_times=2 next_retry_time=2023-08-30 14:52:19 +0000 chunk="604251225bf5378ed1567231a1c03b8b" error_class=Fluent::Plugin::LokiOutput::LogPostError error="429 Too Many Requests Ingestion rate limit exceeded for user infrastructure (limit: 4194304 bytes/sec) while attempting to ingest '4082' lines totaling '7820025' bytes, reduce log volume or contact your Loki administrator to see if the limit can be increased\n"

The error is also visible on the receiving end. For example, in the LokiStack ingester pod:

Example Loki ingester error message

level=warn ts=2023-08-30T14:57:34.155592243Z caller=grpc_logging.go:43 duration=1.434942ms method=/logproto.Pusher/Push err="rpc error: code = Code(429) desc = entry with timestamp 2023-08-30 14:57:32.012778399 +0000 UTC ignored, reason: 'Per stream rate limit exceeded (limit: 3MB/sec) while attempting to ingest for stream

Procedure

Update the ingestionBurstSize and ingestionRate fields in the LokiStack CR:
```
apiVersion: loki.grafana.com/v1
kind: LokiStack
metadata:
  name: logging-loki
  namespace: openshift-logging
spec:
  limits:
    global:
      ingestion:
        ingestionBurstSize: 16 1
        ingestionRate: 8 2
# ...
```
1
The ingestionBurstSize field defines the maximum local rate-limited sample size per distributor replica in MB. This value is a hard limit. Set this value to at least the maximum logs size expected in a single push request. Single requests that are larger than the ingestionBurstSize value are not permitted.
2
The ingestionRate field is a soft limit on the maximum amount of ingested samples per second in MB. Rate limit errors occur if the rate of logs exceeds the limit, but the collector retries sending the logs. As long as the total average is lower than the limit, the system recovers and errors are resolved without user intervention.

2.6. Visualization for logging

Visualization for logging is provided by deploying the Logging UI Plugin of the Cluster Observability Operator, which requires Operator installation.

Important

Until the approaching General Availability (GA) release of the Cluster Observability Operator (COO), which is currently in Technology Preview (TP), Red Hat provides support to customers who are using Logging 6.0 or later with the COO for its Logging UI Plugin on OpenShift Container Platform 4.14 or later. This support exception is temporary as the COO includes several independent features, some of which are still TP features, but the Logging UI Plugin is ready for GA.

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Chapter 2. Logging 6.0

2.1. Release notes

2.1.1. Logging 6.0.1

2.1.1.1. Bug fixes

2.1.1.2. CVEs

2.1.2. Logging 6.0.0

2.1.3. Removal notice

2.1.4. New features and enhancements

2.1.5. Technology Preview features

2.1.6. Bug fixes

2.1.7. CVEs

2.2. Logging 6.0

2.2.1. Inputs and Outputs

2.2.2. Receiver Input Type

2.2.3. Pipelines and Filters

2.2.4. Operator Behavior

2.2.5. Validation

2.2.5.1. Quick Start

2.3. Upgrading to Logging 6.0

2.3.1. Using the oc explain command

2.3.1.1. Resource Descriptions

2.3.1.2. Hierarchical Structure

2.3.1.3. Type Information

2.3.1.4. Default Values

2.3.2. Log Storage

2.3.3. Log Visualization

2.3.4. Log Collection and Forwarding

2.3.5. Management, Resource Allocation, and Workload Scheduling

2.3.6. Input Specifications

2.3.6.1. Application Inputs

2.3.6.2. Input Receivers

2.3.7. Output Specifications

2.3.8. Secrets and TLS Configuration

2.3.9. Red Hat Managed Elasticsearch

2.3.10. Red Hat Managed LokiStack

2.3.11. Filters and Pipeline Configuration

2.3.12. Validation and Status

2.4. Configuring log forwarding

2.4.1. Setting up log collection

2.4.1.1. Legacy service accounts

2.4.1.2. Creating service accounts

2.4.1.2.1. Cluster Role Binding for your Service Account

2.4.1.2.2. Writing application logs

2.4.1.2.3. Writing audit logs

2.4.1.2.4. Writing infrastructure logs

2.4.1.2.5. ClusterLogForwarder editor role

2.4.2. Modifying log level in collector

2.4.3. Managing the Operator

2.4.4. Structure of the ClusterLogForwarder

2.4.4.1. Inputs

2.4.4.2. Outputs

2.4.4.3. Pipelines

2.4.4.4. Filters

2.4.4.5. Enabling multi-line exception detection

2.4.4.5.1. Details

2.4.4.6. Configuring content filters to drop unwanted log records

2.4.4.7. Overview of API audit filter

2.4.4.8. Filtering application logs at input by including the label expressions or a matching label key and values

2.4.4.9. Configuring content filters to prune log records

2.4.5. Filtering the audit and infrastructure log inputs by source

2.4.6. Filtering application logs at input by including or excluding the namespace or container name

2.5. Storing logs with LokiStack

2.5.1. Prerequisites

2.5.1.1. Core Setup and Configuration

2.5.2. Authorizing LokiStack rules RBAC permissions

2.5.2.1. Examples

2.5.3. Creating a log-based alerting rule with Loki

2.5.4. Configuring Loki to tolerate memberlist creation failure

2.5.5. Enabling stream-based retention with Loki

2.5.6. Loki pod placement

2.5.6.1. Enhanced Reliability and Performance

2.5.7. Enabling authentication to cloud-based log stores using short-lived tokens

2.5.8. Configuring Loki to tolerate node failure

2.5.9. LokiStack behavior during cluster restarts

2.5.9.1. Advanced Deployment and Scalability

2.5.10. Zone aware data replication

2.5.11. Recovering Loki pods from failed zones

2.5.11.1. Troubleshooting PVC in a terminating state

2.5.12. Troubleshooting Loki rate limit errors

2.3.1. Using the `oc explain` command