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Configuring your logging deployment

You can configure your logging subsystem deployment with Custom Resource (CR) YAML files implemented by each Operator.

Red Hat Openshift Logging Operator:

  • ClusterLogging (CL) - Deploys the collector and forwarder which currently are both implemented by a daemonset running on each node.

  • ClusterLogForwarder (CLF) - Generates collector configuration to forward logs per user configuration.

Loki Operator:

  • LokiStack - Controls the Loki cluster as log store and the web proxy with OpenShift Container Platform authentication integration to enforce multi-tenancy.

OpenShift Elasticsearch Operator:

These CRs are generated and managed by the ClusterLogging Operator, manual changes cannot be made without being overwritten by the Operator.

  • ElasticSearch - Configure and deploy an Elasticsearch instance as the default log store.

  • Kibana - Configure and deploy Kibana instance to search, query and view logs.

Only the configuration options described in this documentation are supported for the logging subsystem.

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.

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 subsystem for Red Hat OpenShift is not supported and does not receive updates until you return its status to Managed.

Enabling stream-based retention with Loki

With Logging version 5.6 and higher, 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.

  1. To enable stream-based retention, create a LokiStack custom resource (CR):

    Example global stream-based retention
    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: v11
    secret:
      name: logging-loki-s3
      type: aws
  storageClassName: standard
  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.
    Example per-tenant stream-based retention
    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: v11
    secret:
      name: logging-loki-s3
      type: aws
  storageClassName: standard
  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.

  2. Apply the LokiStack CR:

    $ oc apply -f <filename>.yaml

This is not for managing the retention for stored logs. Global retention periods for stored logs to a supported maximum of 30 days is configured with your object storage.

Enabling multi-line exception detection

Enables multi-line error detection of container logs.

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, with a value of true.

Example ClusterLogForwarder CR
apiVersion: logging.openshift.io/v1
kind: ClusterLogForwarder
metadata:
  name: instance
  namespace: openshift-logging
spec:
  pipelines:
    - name: my-app-logs
      inputRefs:
        - application
      outputRefs:
        - default
      detectMultilineErrors: true

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.

Table 1. Supported languages per collector:
Language Fluentd Vector

Java

✓

✓

JS

✓

✓

Ruby

✓

✓

Python

✓

✓

Golang

✓

✓

PHP

✓

Dart

✓

✓

Troubleshooting

When enabled, the collector configuration will include a new section with type: detect_exceptions

Example vector configuration section
[transforms.detect_exceptions_app-logs]
 type = "detect_exceptions"
 inputs = ["application"]
 languages = ["All"]
 group_by = ["kubernetes.namespace_name","kubernetes.pod_name","kubernetes.container_name"]
 expire_after_ms = 2000
 multiline_flush_interval_ms = 1000
Example fluentd config section
<label @MULTILINE_APP_LOGS>
  <match kubernetes.**>
    @type detect_exceptions
    remove_tag_prefix 'kubernetes'
    message message
    force_line_breaks true
    multiline_flush_interval .2
  </match>
</label>