Chapter 3. Logging 6.1 3.1. Support Only the configuration options described in this documentation are supported for logging. Do not use any other configuration options, as they are unsupported. Configuration paradigms might change across OpenShift Container Platform releases, and such cases can only be handled gracefully if all configuration possibilities are controlled. If you use configurations other than those described in this documentation, your changes will be overwritten, because Operators are designed to reconcile any differences. Note If you must perform configurations not described in the OpenShift Container Platform documentation, you must set your Red Hat OpenShift Logging Operator to Unmanaged . An unmanaged logging instance is not supported and does not receive updates until you return its status to Managed . 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. Loki is a horizontally scalable, highly available, multi-tenant log aggregation system offered as a GA log store for logging for Red Hat OpenShift that can be visualized with the OpenShift Observability UI. The Loki configuration provided by OpenShift Logging is a short-term log store designed to enable users to perform fast troubleshooting with the collected logs. For that purpose, the logging for Red Hat OpenShift configuration of Loki has short-term storage, and is optimized for very recent queries. Important For long-term storage or queries over a long time period, users should look to log stores external to their cluster. Loki sizing is only tested and supported for short term storage, for a maximum of 30 days. Logging for Red Hat OpenShift is an opinionated collector and normalizer of application, infrastructure, and audit logs. It is intended to be used for forwarding logs to various supported systems. Logging is not: A high scale log collection system Security Information and Event Monitoring (SIEM) compliant A "bring your own" (BYO) log collector configuration Historical or long term log retention or storage A guaranteed log sink Secure storage - audit logs are not stored by default 3.1.1. Supported API custom resource definitions The following table describes the supported Logging APIs. Table 3.1. Logging API support states CustomResourceDefinition (CRD) ApiVersion Support state LokiStack lokistack.loki.grafana.com/v1 Supported from 5.5 RulerConfig rulerconfig.loki.grafana/v1 Supported from 5.7 AlertingRule alertingrule.loki.grafana/v1 Supported from 5.7 RecordingRule recordingrule.loki.grafana/v1 Supported from 5.7 LogFileMetricExporter LogFileMetricExporter.logging.openshift.io/v1alpha1 Supported from 5.8 ClusterLogForwarder clusterlogforwarder.observability.openshift.io/v1 Supported from 6.0 3.1.2. Unsupported configurations You must set the Red Hat OpenShift Logging Operator to the Unmanaged state to modify the following components: The collector configuration file The collector daemonset Explicitly unsupported cases include: Configuring the logging collector using environment variables . You cannot use environment variables to modify the log collector. Configuring how the log collector normalizes logs . You cannot modify default log normalization. 3.1.3. Support policy for unmanaged Operators The management state of an Operator determines whether an Operator is actively managing the resources for its related component in the cluster as designed. If an Operator is set to an unmanaged state, it does not respond to changes in configuration nor does it receive updates. While this can be helpful in non-production clusters or during debugging, Operators in an unmanaged state are unsupported and the cluster administrator assumes full control of the individual component configurations and upgrades. An Operator can be set to an unmanaged state using the following methods: Individual Operator configuration Individual Operators have a managementState parameter in their configuration. This can be accessed in different ways, depending on the Operator. For example, the Red Hat OpenShift Logging Operator accomplishes this by modifying a custom resource (CR) that it manages, while the Cluster Samples Operator uses a cluster-wide configuration resource. Changing the managementState parameter to Unmanaged means that the Operator is not actively managing its resources and will take no action related to the related component. Some Operators might not support this management state as it might damage the cluster and require manual recovery. Warning Changing individual Operators to the Unmanaged state renders that particular component and functionality unsupported. Reported issues must be reproduced in Managed state for support to proceed. Cluster Version Operator (CVO) overrides The spec.overrides parameter can be added to the CVO's configuration to allow administrators to provide a list of overrides to the CVO's behavior for a component. Setting the spec.overrides[].unmanaged parameter to true for a component blocks cluster upgrades and alerts the administrator after a CVO override has been set: Disabling ownership via cluster version overrides prevents upgrades. Please remove overrides before continuing. Warning Setting a CVO override puts the entire cluster in an unsupported state. Reported issues must be reproduced after removing any overrides for support to proceed. 3.1.4. Collecting logging data for Red Hat Support When opening a support case, it is helpful to provide debugging information about your cluster to Red Hat Support. You can use the must-gather tool to collect diagnostic information for project-level resources, cluster-level resources, and each of the logging components. For prompt support, supply diagnostic information for both OpenShift Container Platform and logging. 3.1.4.1. About the must-gather tool The oc adm must-gather CLI command collects the information from your cluster that is most likely needed for debugging issues. For your logging, must-gather collects the following information: Project-level resources, including pods, configuration maps, service accounts, roles, role bindings, and events at the project level Cluster-level resources, including nodes, roles, and role bindings at the cluster level OpenShift Logging resources in the openshift-logging and openshift-operators-redhat namespaces, including health status for the log collector, the log store, and the log visualizer When you run oc adm must-gather , a new pod is created on the cluster. The data is collected on that pod and saved in a new directory that starts with must-gather.local . This directory is created in the current working directory. 3.1.4.2. Collecting logging data You can use the oc adm must-gather CLI command to collect information about logging. Procedure To collect logging information with must-gather : Navigate to the directory where you want to store the must-gather information. Run the oc adm must-gather command against the logging image: USD oc adm must-gather --image=USD(oc -n openshift-logging get deployment.apps/cluster-logging-operator -o jsonpath='{.spec.template.spec.containers[?(@.name == "cluster-logging-operator")].image}') The must-gather tool creates a new directory that starts with must-gather.local within the current directory. For example: must-gather.local.4157245944708210408 . Create a compressed file from the must-gather directory that was just created. For example, on a computer that uses a Linux operating system, run the following command: USD tar -cvaf must-gather.tar.gz must-gather.local.4157245944708210408 Attach the compressed file to your support case on the Red Hat Customer Portal . 3.2. Logging 6.1 3.2.1. Logging 6.1.1 Release Notes This release includes Logging for Red Hat OpenShift Bug Fix Release 6.1.1 . 3.2.1.1. New Features and Enhancements With this update, the Loki Operator supports configuring the workload identity federation on the Google Cloud Platform (GCP) by using the Cluster Credential Operator (CCO) in OpenShift Container Platform 4.17 or later. ( LOG-6420 ) 3.2.1.2. Bug Fixes Before this update, the collector was discarding longer audit log messages with the following error message: Internal log [Found line that exceeds max_line_bytes; discarding.] . With this update, the discarding of longer audit messages is avoided by increasing the audit configuration thresholds: The maximum line size, max_line_bytes , is 3145728 bytes. The maximum number of bytes read during a read cycle, max_read_bytes , is 262144 bytes. ( LOG-6379 ) Before this update, an input receiver service was repeatedly created and deleted, causing issues with mounting the TLS secrets. With this update, the service is created once and only deleted if it is not defined in the ClusterLogForwarder custom resource. ( LOG-6383 ) Before this update, pipeline validation might have entered an infinite loop if a name was a substring of another name. With this update, stricter name equality checks prevent the infinite loop. ( LOG-6405 ) Before this update, the collector alerting rules included the summary and message fields. With this update, the collector alerting rules include the summary and description fields. ( LOG-6407 ) Before this update, setting up the custom audit inputs in the ClusterLogForwarder custom resource with configured LokiStack output caused errors due to the nil pointer dereference. With this update, the Operator performs the nil checks, preventing such errors. ( LOG-6449 ) Before this update, the ValidLokistackOTLPOutputs condition appeared in the status of the ClusterLogForwarder custom resource even when the output type is not LokiStack . With this update, the ValidLokistackOTLPOutputs condition is removed, and the validation messages for the existing output conditions are corrected. ( LOG-6469 ) Before this update, the collector did not correctly mount the /var/log/oauth-server/ path, which prevented the collection of the audit logs. With this update, the volume mount is added, and the audit logs are collected as expected. ( LOG-6484 ) Before this update, the must-gather script of the Red Hat OpenShift Logging Operator might have failed to gather the LokiStack data. With this update, the must-gather script is fixed, and the LokiStack data is gathered reliably. ( LOG-6498 ) Before this update, the collector did not correctly mount the oauth-apiserver audit log file. As a result, such audit logs were not collected. With this update, the volume mount is correctly mounted, and the logs are collected as expected. ( LOG-6533 ) 3.2.1.3. CVEs CVE-2019-12900 CVE-2024-2511 CVE-2024-3596 CVE-2024-4603 CVE-2024-4741 CVE-2024-5535 CVE-2024-10963 CVE-2024-50602 3.2.2. Logging 6.1.0 Release Notes This release includes Logging for Red Hat OpenShift Bug Fix Release 6.1.0 . 3.2.2.1. New Features and Enhancements 3.2.2.1.1. Log Collection This enhancement adds the source iostream to the attributes sent from collected container logs. The value is set to either stdout or stderr based on how the collector received it. ( LOG-5292 ) With this update, the default memory limit for the collector increases from 1024 Mi to 2048 Mi. Users should adjust resource limits based on their cluster's specific needs and specifications. ( LOG-6072 ) With this update, users can now set the syslog output delivery mode of the ClusterLogForwarder CR to either AtLeastOnce or AtMostOnce. ( LOG-6355 ) 3.2.2.1.2. Log Storage With this update, the new 1x.pico LokiStack size supports clusters with fewer workloads and lower log volumes (up to 50GB/day). ( LOG-5939 ) 3.2.2.2. Technology Preview Important The OpenTelemetry Protocol (OTLP) output log forwarder is a Technology Preview feature only. Technology Preview features are not supported with Red Hat production service level agreements (SLAs) and might not be functionally complete. Red Hat does not recommend using them in production. These features provide early access to upcoming product features, enabling customers to test functionality and provide feedback during the development process. For more information about the support scope of Red Hat Technology Preview features, see Technology Preview Features Support Scope . With this update, OpenTelemetry logs can now be forwarded using the OTel (OpenTelemetry) data model to a Red Hat Managed LokiStack instance. To enable this feature, add the observability.openshift.io/tech-preview-otlp-output: "enabled" annotation to your ClusterLogForwarder configuration. For additional configuration information, see OTLP Forwarding . With this update, a dataModel field has been added to the lokiStack output specification. Set the dataModel to Otel to configure log forwarding using the OpenTelemetry data format. The default is set to Viaq . For information about data mapping see OTLP Specification . 3.2.2.3. Bug Fixes None. 3.2.2.4. CVEs CVE-2024-6119 CVE-2024-6232 3.3. Logging 6.1 The ClusterLogForwarder custom resource (CR) is the central configuration point for log collection and forwarding. 3.3.1. Inputs and outputs Inputs specify the sources of logs to be forwarded. Logging provides the following built-in input types that select logs from different parts of your cluster: application receiver infrastructure audit 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. 3.3.2. 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 field defines the configuration for a receiver input. 3.3.3. 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. You can use filters 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. 3.3.4. Operator behavior The Cluster Logging Operator manages the deployment and configuration of the collector based on the managementState field of the ClusterLogForwarder resource: 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. 3.3.5. 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. 3.3.6. Quick start OpenShift Logging supports two data models: ViaQ (General Availability) OpenTelemetry (Technology Preview) You can select either of these data models based on your requirement by configuring the lokiStack.dataModel field in the ClusterLogForwarder . ViaQ is the default data model when forwarding logs to LokiStack. Note In future releases of OpenShift Logging, the default data model will change from ViaQ to OpenTelemetry. 3.3.6.1. Quick start with ViaQ To use the default ViaQ data model, follow these steps: Prerequisites Cluster administrator permissions Procedure Install the Red Hat OpenShift Logging Operator, Loki Operator, and Cluster Observability Operator (COO) 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: '2024-10-01' version: v13 secret: name: logging-loki-s3 type: s3 storageClassName: gp3-csi tenants: mode: openshift-logging Note Ensure that the logging-loki-s3 secret is created beforehand. The contents of this secret vary depending on the object storage in use. For more information, see Secrets and TLS Configuration. Create a service account for the collector: USD oc create sa collector -n openshift-logging Allow the collector's service account to write data to the LokiStack CR: USD oc adm policy add-cluster-role-to-user logging-collector-logs-writer -z collector Note The ClusterRole resource is created automatically during the Cluster Logging Operator installation and does not need to be created manually. Allow the collector's service account to collect logs: USD oc project openshift-logging USD oc adm policy add-cluster-role-to-user collect-application-logs -z collector USD oc adm policy add-cluster-role-to-user collect-audit-logs -z collector USD oc adm policy add-cluster-role-to-user collect-infrastructure-logs -z collector Note The example binds the collector to all three roles (application, infrastructure, and audit), but by default, only application and infrastructure logs are collected. To collect audit logs, update your ClusterLogForwarder configuration to include them. Assign roles based on the specific log types required for your environment. Create a UIPlugin CR 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 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: authentication: token: from: serviceAccount target: name: logging-loki namespace: openshift-logging tls: ca: key: service-ca.crt configMapName: openshift-service-ca.crt pipelines: - name: default-logstore inputRefs: - application - infrastructure outputRefs: - default-lokistack Note The dataModel field is optional and left unset ( dataModel: "" ) by default. This allows the Cluster Logging Operator (CLO) to automatically select a data model. Currently, the CLO defaults to the ViaQ model when the field is unset, but this will change in future releases. Specifying dataModel: ViaQ ensures the configuration remains compatible if the default changes. Verification Verify that logs are visible in the Log section of the Observe tab in the OpenShift web console. 3.3.6.2. Quick start with OpenTelemetry Important The OpenTelemetry Protocol (OTLP) output log forwarder is a Technology Preview feature only. Technology Preview features are not supported with Red Hat production service level agreements (SLAs) and might not be functionally complete. Red Hat does not recommend using them in production. These features provide early access to upcoming product features, enabling customers to test functionality and provide feedback during the development process. For more information about the support scope of Red Hat Technology Preview features, see Technology Preview Features Support Scope . To configure OTLP ingestion and enable the OpenTelemetry data model, follow these steps: Prerequisites Cluster administrator permissions Procedure Install the Red Hat OpenShift Logging Operator, Loki Operator, and Cluster Observability Operator (COO) 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: '2024-10-01' version: v13 secret: name: logging-loki-s3 type: s3 storageClassName: gp3-csi tenants: mode: openshift-logging Note Ensure that the logging-loki-s3 secret is created beforehand. The contents of this secret vary depending on the object storage in use. For more information, see "Secrets and TLS Configuration". Create a service account for the collector: USD oc create sa collector -n openshift-logging Allow the collector's service account to write data to the LokiStack CR: USD oc adm policy add-cluster-role-to-user logging-collector-logs-writer -z collector Note The ClusterRole resource is created automatically during the Cluster Logging Operator installation and does not need to be created manually. Allow the collector's service account to collect logs: USD oc project openshift-logging USD oc adm policy add-cluster-role-to-user collect-application-logs -z collector USD oc adm policy add-cluster-role-to-user collect-audit-logs -z collector USD oc adm policy add-cluster-role-to-user collect-infrastructure-logs -z collector Note The example binds the collector to all three roles (application, infrastructure, and audit). By default, only application and infrastructure logs are collected. To collect audit logs, update your ClusterLogForwarder configuration to include them. Assign roles based on the specific log types required for your environment. Create a UIPlugin CR 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 Create a ClusterLogForwarder CR to configure log forwarding: apiVersion: observability.openshift.io/v1 kind: ClusterLogForwarder metadata: name: collector namespace: openshift-logging annotations: observability.openshift.io/tech-preview-otlp-output: "enabled" 1 spec: serviceAccount: name: collector outputs: - name: loki-otlp type: lokiStack 2 lokiStack: target: name: logging-loki namespace: openshift-logging dataModel: Otel 3 authentication: token: from: serviceAccount tls: ca: key: service-ca.crt configMapName: openshift-service-ca.crt pipelines: - name: my-pipeline inputRefs: - application - infrastructure outputRefs: - loki-otlp 1 Use the annotation to enable the Otel data model, which is a Technology Preview feature. 2 Define the output type as lokiStack . 3 Specifies the OpenTelemetry data model. Note You cannot use lokiStack.labelKeys when dataModel is Otel . To achieve similar functionality when dataModel is Otel , refer to "Configuring LokiStack for OTLP data ingestion". Verification Verify that OTLP is functioning correctly by going to Observe OpenShift Logging LokiStack Writes in the OpenShift web console, and checking Distributor - Structured Metadata . 3.4. 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 3.4.1. 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 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. 3.4.1.1. Legacy service accounts To use the existing legacy service account logcollector , create the following ClusterRoleBinding : USD oc adm policy add-cluster-role-to-user collect-application-logs system:serviceaccount:openshift-logging:logcollector USD 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: USD oc adm policy add-cluster-role-to-user collect-audit-logs system:serviceaccount:openshift-logging:logcollector 3.4.1.2. 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 USD oc adm policy add-cluster-role-to-user <cluster_role_name> system:serviceaccount:<namespace_name>:<service_account_name> 3.4.1.2.1. 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. 3.4.1.2.2. 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 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. 3.4.1.2.3. 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 rules: Defines the permissions granted by this ClusterRole. 2 apiGroups: Specifies the API group loki.grafana.com. 3 loki.grafana.com: The API group responsible for Loki logging resources. 4 resources: Refers to the resource type this role manages, in this case, audit. 5 audit: Specifies that the role manages audit logs within Loki. 6 resourceNames: Defines the specific resources that the role can access. 7 logs: Refers to the logs that can be managed under this role. 8 verbs: The actions allowed on the resources. 9 create: Grants permission to create new audit logs. 3.4.1.2.4. 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. 3.4.1.2.5. 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. 3.4.2. 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 # ... 3.4.3. 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 . 3.4.4. 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. 3.4.4.1. 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. infrastructure Selects logs from nodes and from infrastructure components running in the following namespaces: default kube openshift Containing the kube- or openshift- prefix 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. 3.4.4.2. 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. 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. 3.4.5. Configuring OTLP output Cluster administrators can use the OpenTelemetry Protocol (OTLP) output to collect and forward logs to OTLP receivers. The OTLP output uses the specification defined by the OpenTelemetry Observability framework to send data over HTTP with JSON encoding. Important The OpenTelemetry Protocol (OTLP) output log forwarder is a Technology Preview feature only. Technology Preview features are not supported with Red Hat production service level agreements (SLAs) and might not be functionally complete. Red Hat does not recommend using them in production. These features provide early access to upcoming product features, enabling customers to test functionality and provide feedback during the development process. For more information about the support scope of Red Hat Technology Preview features, see Technology Preview Features Support Scope . Procedure Create or edit a ClusterLogForwarder custom resource (CR) to enable forwarding using OTLP by adding the following annotation: Example ClusterLogForwarder CR apiVersion: observability.openshift.io/v1 kind: ClusterLogForwarder metadata: annotations: observability.openshift.io/tech-preview-otlp-output: "enabled" 1 name: clf-otlp spec: serviceAccount: name: <service_account_name> outputs: - name: otlp type: otlp otlp: tuning: compression: gzip deliveryMode: AtLeastOnce maxRetryDuration: 20 maxWrite: 10M minRetryDuration: 5 url: <otlp_url> 2 pipelines: - inputRefs: - application - infrastructure - audit name: otlp-logs outputRefs: - otlp 1 Use this annotation to enable the OpenTelemetry Protocol (OTLP) output, which is a Technology Preview feature. 2 This URL must be absolute and is a placeholder for the OTLP endpoint where logs are sent. Note The OTLP output uses the OpenTelemetry data model, which is different from the ViaQ data model that is used by other output types. It adheres to the OTLP using OpenTelemetry Semantic Conventions defined by the OpenTelemetry Observability framework. 3.4.5.1. 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. 3.4.5.2. 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: 3.4.5.3. 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> 3.4.5.3.1. 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 3.4.5.4. 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: USD 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" # ... 3.4.5.5. 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. 3.4.5.6. 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: USD oc apply -f <filename>.yaml 3.4.5.7. 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: USD oc apply -f <filename>.yaml 3.4.6. 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: USD oc apply -f <filename>.yaml 3.4.7. 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 type: application # ... 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: USD oc apply -f <filename>.yaml 3.5. Storing logs with LokiStack You can configure a LokiStack CR to store application, audit, and infrastructure-related logs. Loki is a horizontally scalable, highly available, multi-tenant log aggregation system offered as a GA log store for logging for Red Hat OpenShift that can be visualized with the OpenShift Observability UI. The Loki configuration provided by OpenShift Logging is a short-term log store designed to enable users to perform fast troubleshooting with the collected logs. For that purpose, the logging for Red Hat OpenShift configuration of Loki has short-term storage, and is optimized for very recent queries. Important For long-term storage or queries over a long time period, users should look to log stores external to their cluster. Loki sizing is only tested and supported for short term storage, for a maximum of 30 days. 3.5.1. Loki deployment sizing Sizing for Loki follows the format of 1x.<size> where the value 1x is number of instances and <size> specifies performance capabilities. The 1x.pico configuration defines a single Loki deployment with minimal resource and limit requirements, offering high availability (HA) support for all Loki components. This configuration is suited for deployments that do not require a single replication factor or auto-compaction. Disk requests are similar across size configurations, allowing customers to test different sizes to determine the best fit for their deployment needs. Important It is not possible to change the number 1x for the deployment size. Table 3.2. Loki sizing 1x.demo 1x.pico [6.1+ only] 1x.extra-small 1x.small 1x.medium Data transfer Demo use only 50GB/day 100GB/day 500GB/day 2TB/day Queries per second (QPS) Demo use only 1-25 QPS at 200ms 1-25 QPS at 200ms 25-50 QPS at 200ms 25-75 QPS at 200ms Replication factor None 2 2 2 2 Total CPU requests None 7 vCPUs 14 vCPUs 34 vCPUs 54 vCPUs Total CPU requests if using the ruler None 8 vCPUs 16 vCPUs 42 vCPUs 70 vCPUs Total memory requests None 17Gi 31Gi 67Gi 139Gi Total memory requests if using the ruler None 18Gi 35Gi 83Gi 171Gi Total disk requests 40Gi 590Gi 430Gi 430Gi 590Gi Total disk requests if using the ruler 80Gi 910Gi 750Gi 750Gi 910Gi 3.5.2. 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. 3.5.3. Core Setup and Configuration Role-based access controls, basic monitoring, and pod placement to deploy Loki. 3.5.4. 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. 3.5.4.1. 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 USD 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 USD oc adm policy add-cluster-role-to-user alertingrules.loki.grafana.com-v1-admin <username> 3.5.5. 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 3.3. 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: USD oc apply -f <filename>.yaml 3.5.6. 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: USD 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 # ... 3.5.7. 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: USD oc apply -f <filename>.yaml 3.5.8. 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 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: USD 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: USD 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. ... 3.5.8.1. Enhanced Reliability and Performance Configurations to ensure Loki's reliability and efficiency in production. 3.5.8.2. 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> 3.5.8.3. 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. 3.5.8.4. 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. 3.5.8.5. Advanced Deployment and Scalability Specialized configurations for high availability, scalability, and error handling. 3.5.8.6. 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. 3.5.8.7. 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: USD 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: USD 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: USD oc delete pvc <pvc_name> -n openshift-logging Delete the pod(s) by running the following command: USD oc delete pod <pod_name> -n openshift-logging Once these objects have been successfully deleted, they should automatically be rescheduled in an available zone. 3.5.8.7.1. 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. USD oc patch pvc <pvc_name> -p '{"metadata":{"finalizers":null}}' -n openshift-logging 3.5.8.8. 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 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. 3.6. OTLP data ingestion in Loki You can use an API endpoint by using the OpenTelemetry Protocol (OTLP) with Logging 6.1. As OTLP is a standardized format not specifically designed for Loki, OTLP requires an additional Loki configuration to map data format of OpenTelemetry to data model of Loki. OTLP lacks concepts such as stream labels or structured metadata . Instead, OTLP provides metadata about log entries as attributes , grouped into the following three categories: Resource Scope Log You can set metadata for multiple entries simultaneously or individually as needed. 3.6.1. Configuring LokiStack for OTLP data ingestion Important The OpenTelemetry Protocol (OTLP) output log forwarder is a Technology Preview feature only. Technology Preview features are not supported with Red Hat production service level agreements (SLAs) and might not be functionally complete. Red Hat does not recommend using them in production. These features provide early access to upcoming product features, enabling customers to test functionality and provide feedback during the development process. For more information about the support scope of Red Hat Technology Preview features, see Technology Preview Features Support Scope . To configure a LokiStack custom resource (CR) for OTLP ingestion, follow these steps: Prerequisites Ensure that your Loki setup supports structured metadata, introduced in schema version 13 to enable OTLP log ingestion. Procedure Set the schema version: When creating a new LokiStack CR, set version: v13 in the storage schema configuration. Note For existing configurations, add a new schema entry with version: v13 and an effectiveDate in the future. For more information on updating schema versions, see Upgrading Schemas (Grafana documentation). Configure the storage schema as follows: Example configure storage schema # ... spec: storage: schemas: - version: v13 effectiveDate: 2024-10-25 Once the effectiveDate has passed, the v13 schema takes effect, enabling your LokiStack to store structured metadata. 3.6.2. Attribute mapping When you set the Loki Operator to the openshift-logging mode, Loki Operator automatically applies a default set of attribute mappings. These mappings align specific OTLP attributes with stream labels and structured metadata of Loki. For typical setups, these default mappings are sufficient. However, you might need to customize attribute mapping in the following cases: Using a custom collector: If your setup includes a custom collector that generates additional attributes, consider customizing the mapping to ensure these attributes are retained in Loki. Adjusting attribute detail levels: If the default attribute set is more detailed than necessary, you can reduce it to essential attributes only. This can avoid excessive data storage and streamline the logging process. Important Attributes that are not mapped to either stream labels or structured metadata are not stored in Loki. 3.6.2.1. Custom attribute mapping for OpenShift When using the Loki Operator in openshift-logging mode, attribute mapping follow OpenShift default values, but you can configure custom mappings to adjust default values. In the openshift-logging mode, you can configure custom attribute mappings globally for all tenants or for individual tenants as needed. When you define custom mappings, they are appended to the OpenShift default values. If you do not need default labels, you can disable them in the tenant configuration. Note A major difference between the Loki Operator and Loki lies in inheritance handling. Loki copies only default_resource_attributes_as_index_labels to tenants by default, while the Loki Operator applies the entire global configuration to each tenant in the openshift-logging mode. Within LokiStack , attribute mapping configuration is managed through the limits setting. See the following example LokiStack configuration: # ... spec: limits: global: otlp: {} 1 tenants: application: otlp: {} 2 1 Defines global OTLP attribute configuration. 2 OTLP attribute configuration for the application tenant within openshift-logging mode. Note Both global and per-tenant OTLP configurations can map attributes to stream labels or structured metadata. At least one stream label is required to save a log entry to Loki storage, so ensure this configuration meets that requirement. Stream labels derive only from resource-level attributes, which the LokiStack resource structure reflects: spec: limits: global: otlp: streamLabels: resourceAttributes: - name: "k8s.namespace.name" - name: "k8s.pod.name" - name: "k8s.container.name" Structured metadata, in contrast, can be generated from resource, scope or log-level attributes: # ... spec: limits: global: otlp: streamLabels: # ... structuredMetadata: resourceAttributes: - name: "process.command_line" - name: "k8s\\.pod\\.labels\\..+" regex: true scopeAttributes: - name: "service.name" logAttributes: - name: "http.route" Tip Use regular expressions by setting regex: true for attributes names when mapping similar attributes in Loki. Important Avoid using regular expressions for stream labels, as this can increase data volume. 3.6.2.2. Customizing OpenShift defaults In openshift-logging mode, certain attributes are required and cannot be removed from the configuration due to their role in OpenShift functions. Other attributes, labeled recommended , might be disabled if performance is impacted. When using the openshift-logging mode without custom attributes, you can achieve immediate compatibility with OpenShift tools. If additional attributes are needed as stream labels or structured metadata, use custom configuration. Custom configurations can merge with default configurations. 3.6.2.3. Removing recommended attributes To reduce default attributes in openshift-logging mode, disable recommended attributes: # ... spec: tenants: mode: openshift-logging openshift: otlp: disableRecommendedAttributes: true 1 1 Set disableRecommendedAttributes: true to remove recommended attributes, which limits default attributes to the required attributes . Note This option is beneficial if the default attributes causes performance or storage issues. This setting might negatively impact query performance, as it removes default stream labels. You should pair this option with a custom attribute configuration to retain attributes essential for queries. 3.6.3. Additional resources Loki labels Structured metadata OpenTelemetry attribute 3.7. OpenTelemetry data model This document outlines the protocol and semantic conventions for Red Hat OpenShift Logging's OpenTelemetry support with Logging 6.1. Important The OpenTelemetry Protocol (OTLP) output log forwarder is a Technology Preview feature only. Technology Preview features are not supported with Red Hat production service level agreements (SLAs) and might not be functionally complete. Red Hat does not recommend using them in production. These features provide early access to upcoming product features, enabling customers to test functionality and provide feedback during the development process. For more information about the support scope of Red Hat Technology Preview features, see Technology Preview Features Support Scope . 3.7.1. Forwarding and ingestion protocol Red Hat OpenShift Logging collects and forwards logs to OpenTelemetry endpoints using OTLP Specification . OTLP encodes, transports, and delivers telemetry data. You can also deploy Loki storage, which provides an OTLP endpont to ingest log streams. This document defines the semantic conventions for the logs collected from various OpenShift cluster sources. 3.7.2. Semantic conventions The log collector in this solution gathers the following log streams: Container logs Cluster node journal logs Cluster node auditd logs Kubernetes and OpenShift API server logs OpenShift Virtual Network (OVN) logs You can forward these streams according to the semantic conventions defined by OpenTelemetry semantic attributes. The semantic conventions in OpenTelemetry define a resource as an immutable representation of the entity producing telemetry, identified by attributes. For example, a process running in a container includes attributes such as container_name , cluster_id , pod_name , namespace , and possibly deployment or app_name . These attributes are grouped under the resource object, which helps reduce repetition and optimizes log transmission as telemetry data. In addition to resource attributes, logs might also contain scope attributes specific to instrumentation libraries and log attributes specific to each log entry. These attributes provide greater detail about each log entry and enhance filtering capabilities when querying logs in storage. The following sections define the attributes that are generally forwarded. 3.7.2.1. Log entry structure All log streams include the following log data fields: The Applicable Sources column indicates which log sources each field applies to: all : This field is present in all logs. container : This field is present in Kubernetes container logs, both application and infrastructure. audit : This field is present in Kubernetes, OpenShift API, and OVN logs. auditd : This field is present in node auditd logs. journal : This field is present in node journal logs. Name Applicable Sources Comment body all observedTimeUnixNano all timeUnixNano all severityText container, journal attributes all (Optional) Present when forwarding stream specific attributes 3.7.2.2. Attributes Log entries include a set of resource, scope, and log attributes based on their source, as described in the following table. The Location column specifies the type of attribute: resource : Indicates a resource attribute scope : Indicates a scope attribute log : Indicates a log attribute The Storage column indicates whether the attribute is stored in a LokiStack using the default openshift-logging mode and specifies where the attribute is stored: stream label : Enables efficient filtering and querying based on specific labels. Can be labeled as required if the Loki Operator enforces this attribute in the configuration. structured metadata : Allows for detailed filtering and storage of key-value pairs. Enables users to use direct labels for streamlined queries without requiring JSON parsing. With OTLP, users can filter queries directly by labels rather than using JSON parsing, improving the speed and efficiency of queries. Name Location Applicable Sources Storage (LokiStack) Comment log_source resource all required stream label (DEPRECATED) Compatibility attribute, contains same information as openshift.log.source log_type resource all required stream label (DEPRECATED) Compatibility attribute, contains same information as openshift.log.type kubernetes.container_name resource container stream label (DEPRECATED) Compatibility attribute, contains same information as k8s.container.name kubernetes.host resource all stream label (DEPRECATED) Compatibility attribute, contains same information as k8s.node.name kubernetes.namespace_name resource container required stream label (DEPRECATED) Compatibility attribute, contains same information as k8s.namespace.name kubernetes.pod_name resource container stream label (DEPRECATED) Compatibility attribute, contains same information as k8s.pod.name openshift.cluster_id resource all (DEPRECATED) Compatibility attribute, contains same information as openshift.cluster.uid level log container, journal (DEPRECATED) Compatibility attribute, contains same information as severityText openshift.cluster.uid resource all required stream label openshift.log.source resource all required stream label openshift.log.type resource all required stream label openshift.labels.* resource all structured metadata k8s.node.name resource all stream label k8s.namespace.name resource container required stream label k8s.container.name resource container stream label k8s.pod.labels.* resource container structured metadata k8s.pod.name resource container stream label k8s.pod.uid resource container structured metadata k8s.cronjob.name resource container stream label Conditionally forwarded based on creator of pod k8s.daemonset.name resource container stream label Conditionally forwarded based on creator of pod k8s.deployment.name resource container stream label Conditionally forwarded based on creator of pod k8s.job.name resource container stream label Conditionally forwarded based on creator of pod k8s.replicaset.name resource container structured metadata Conditionally forwarded based on creator of pod k8s.statefulset.name resource container stream label Conditionally forwarded based on creator of pod log.iostream log container structured metadata k8s.audit.event.level log audit structured metadata k8s.audit.event.stage log audit structured metadata k8s.audit.event.user_agent log audit structured metadata k8s.audit.event.request.uri log audit structured metadata k8s.audit.event.response.code log audit structured metadata k8s.audit.event.annotation.* log audit structured metadata k8s.audit.event.object_ref.resource log audit structured metadata k8s.audit.event.object_ref.name log audit structured metadata k8s.audit.event.object_ref.namespace log audit structured metadata k8s.audit.event.object_ref.api_group log audit structured metadata k8s.audit.event.object_ref.api_version log audit structured metadata k8s.user.username log audit structured metadata k8s.user.groups log audit structured metadata process.executable.name resource journal structured metadata process.executable.path resource journal structured metadata process.command_line resource journal structured metadata process.pid resource journal structured metadata service.name resource journal stream label systemd.t.* log journal structured metadata systemd.u.* log journal structured metadata Note Attributes marked as Compatibility attribute support minimal backward compatibility with the ViaQ data model. These attributes are deprecated and function as a compatibility layer to ensure continued UI functionality. These attributes will remain supported until the Logging UI fully supports the OpenTelemetry counterparts in future releases. Loki changes the attribute names when persisting them to storage. The names will be lowercased, and all characters in the set: ( . , / , - ) will be replaced by underscores ( _ ). For example, k8s.namespace.name will become k8s_namespace_name . 3.7.3. Additional resources Semantic Conventions Logs Data Model General Logs Attributes 3.8. 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.

Commands:
Disabling ownership via cluster version overrides prevents upgrades. Please remove overrides before continuing.
oc adm must-gather --image=USD(oc -n openshift-logging get deployment.apps/cluster-logging-operator -o jsonpath='{.spec.template.spec.containers[?(@.name == "cluster-logging-operator")].image}')
tar -cvaf must-gather.tar.gz must-gather.local.4157245944708210408
apiVersion: loki.grafana.com/v1 kind: LokiStack metadata: name: logging-loki namespace: openshift-logging spec: managementState: Managed size: 1x.extra-small storage: schemas: - effectiveDate: '2024-10-01' version: v13 secret: name: logging-loki-s3 type: s3 storageClassName: gp3-csi tenants: mode: openshift-logging
oc create sa collector -n openshift-logging
oc adm policy add-cluster-role-to-user logging-collector-logs-writer -z collector
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
apiVersion: observability.openshift.io/v1alpha1 kind: UIPlugin metadata: name: logging spec: type: Logging logging: lokiStack: name: logging-loki
apiVersion: observability.openshift.io/v1 kind: ClusterLogForwarder metadata: name: collector namespace: openshift-logging spec: serviceAccount: name: collector outputs: - name: default-lokistack type: lokiStack lokiStack: authentication: token: from: serviceAccount target: name: logging-loki namespace: openshift-logging tls: ca: key: service-ca.crt configMapName: openshift-service-ca.crt pipelines: - name: default-logstore inputRefs: - application - infrastructure outputRefs: - default-lokistack
apiVersion: loki.grafana.com/v1 kind: LokiStack metadata: name: logging-loki namespace: openshift-logging spec: managementState: Managed size: 1x.extra-small storage: schemas: - effectiveDate: '2024-10-01' version: v13 secret: name: logging-loki-s3 type: s3 storageClassName: gp3-csi tenants: mode: openshift-logging
oc create sa collector -n openshift-logging
oc adm policy add-cluster-role-to-user logging-collector-logs-writer -z collector
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
apiVersion: observability.openshift.io/v1alpha1 kind: UIPlugin metadata: name: logging spec: type: Logging logging: lokiStack: name: logging-loki
apiVersion: observability.openshift.io/v1 kind: ClusterLogForwarder metadata: name: collector namespace: openshift-logging annotations: observability.openshift.io/tech-preview-otlp-output: "enabled" 1 spec: serviceAccount: name: collector outputs: - name: loki-otlp type: lokiStack 2 lokiStack: target: name: logging-loki namespace: openshift-logging dataModel: Otel 3 authentication: token: from: serviceAccount tls: ca: key: service-ca.crt configMapName: openshift-service-ca.crt pipelines: - name: my-pipeline inputRefs: - application - infrastructure outputRefs: - loki-otlp
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
oc adm policy add-cluster-role-to-user collect-audit-logs system:serviceaccount:openshift-logging:logcollector
oc adm policy add-cluster-role-to-user <cluster_role_name> system:serviceaccount:<namespace_name>:<service_account_name>
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
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
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
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
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
apiVersion: observability.openshift.io/v1 kind: ClusterLogForwarder metadata: name: collector annotations: observability.openshift.io/log-level: debug
apiVersion: observability.openshift.io/v1 kind: ClusterLogForwarder metadata: annotations: observability.openshift.io/tech-preview-otlp-output: "enabled" 1 name: clf-otlp spec: serviceAccount: name: <service_account_name> outputs: - name: otlp type: otlp otlp: tuning: compression: gzip deliveryMode: AtLeastOnce maxRetryDuration: 20 maxWrite: 10M minRetryDuration: 5 url: <otlp_url> 2 pipelines: - inputRefs: - application - infrastructure - audit name: otlp-logs outputRefs: - otlp
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)
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>
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>"]
oc apply -f <filename>.yaml
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"
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"
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
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
oc apply -f <filename>.yaml
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>"]
oc apply -f <filename>.yaml
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
oc apply -f <filename>.yaml
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 type: application
oc apply -f <filename>.yaml
oc adm policy add-role-to-user alertingrules.loki.grafana.com-v1-admin -n <namespace> <username>
oc adm policy add-cluster-role-to-user alertingrules.loki.grafana.com-v1-admin <username>
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
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
oc apply -f <filename>.yaml
oc patch LokiStack logging-loki -n openshift-logging --type=merge -p '{"spec": {"hashRing":{"memberlist":{"instanceAddrType":"podIP"},"type":"memberlist"}}}'
apiVersion: loki.grafana.com/v1 kind: LokiStack metadata: name: logging-loki namespace: openshift-logging spec: hashRing: type: memberlist memberlist: instanceAddrType: podIP
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
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
oc apply -f <filename>.yaml
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: ""
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 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
oc explain lokistack.spec.template
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.
oc explain lokistack.spec.template.compactor
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.
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>
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>
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
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
oc get pods --field-selector status.phase==Pending -n openshift-logging
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
oc get pvc -o=json -n openshift-logging | jq '.items[] | select(.status.phase == "Pending") | .metadata.name' -r
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
oc delete pvc <pvc_name> -n openshift-logging
oc delete pod <pod_name> -n openshift-logging
oc patch pvc <pvc_name> -p '{"metadata":{"finalizers":null}}' -n openshift-logging
"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\"}"]]}]}
429 Too Many Requests Ingestion rate limit exceeded
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
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
apiVersion: loki.grafana.com/v1 kind: LokiStack metadata: name: logging-loki namespace: openshift-logging spec: limits: global: ingestion: ingestionBurstSize: 16 1 ingestionRate: 8 2
spec: storage: schemas: - version: v13 effectiveDate: 2024-10-25
spec: limits: global: otlp: {} 1 tenants: application: otlp: {} 2
spec: limits: global: otlp: streamLabels: resourceAttributes: - name: "k8s.namespace.name" - name: "k8s.pod.name" - name: "k8s.container.name"
spec: limits: global: otlp: streamLabels: structuredMetadata: resourceAttributes: - name: "process.command_line" - name: "k8s\\.pod\\.labels\\..+" regex: true scopeAttributes: - name: "service.name" logAttributes: - name: "http.route"
spec: tenants: mode: openshift-logging openshift: otlp: disableRecommendedAttributes: true 1