Observability in OpenShift Pipelines


Red Hat OpenShift Pipelines 1.10

Observability features of OpenShift Pipelines

Red Hat OpenShift Documentation Team

Abstract

This document provides information about observability features of OpenShift Pipelines.

The logs generated by pipeline runs, task runs, and event listeners are stored in their respective pods. It is useful to review and analyze logs for troubleshooting and audits.

However, retaining the pods indefinitely leads to unnecessary resource consumption and cluttered namespaces.

To eliminate any dependency on the pods for viewing pipeline logs, you can use the OpenShift Elasticsearch Operator and the OpenShift Logging Operator. These Operators help you to view pipeline logs by using the Elasticsearch Kibana stack, even after you have deleted the pods that contained the logs.

1.1. Prerequisites

Before trying to view pipeline logs in a Kibana dashboard, ensure the following:

  • The steps are performed by a cluster administrator.
  • Logs for pipeline runs and task runs are available.
  • The OpenShift Elasticsearch Operator and the OpenShift Logging Operator are installed.

1.2. Viewing pipeline logs in Kibana

To view pipeline logs in the Kibana web console:

Procedure

  1. Log in to OpenShift Container Platform web console as a cluster administrator.
  2. In the top right of the menu bar, click the grid icon → ObservabilityLogging. The Kibana web console is displayed.
  3. Create an index pattern:

    1. On the left navigation panel of the Kibana web console, click Management.
    2. Click Create index pattern.
    3. Under Step 1 of 2: Define index patternIndex pattern, enter a * pattern and click Next Step.
    4. Under Step 2 of 2: Configure settingsTime filter field name, select @timestamp from the drop-down menu, and click Create index pattern.
  4. Add a filter:

    1. On the left navigation panel of the Kibana web console, click Discover.
    2. Click Add a filter +Edit Query DSL.

      Note
      • For each of the example filters that follows, edit the query and click Save.
      • The filters are applied one after another.
      1. Filter the containers related to pipelines:

        Example query to filter pipelines containers

        {
          "query": {
        	"match": {
          	"kubernetes.flat_labels": {
            	"query": "app_kubernetes_io/managed-by=tekton-pipelines",
            	"type": "phrase"
          	}
        	}
          }
        }
        Copy to Clipboard Toggle word wrap

      2. Filter all containers that are not place-tools container. As an illustration of using the graphical drop-down menus instead of editing the query DSL, consider the following approach:

        Figure 1.1. Example of filtering using the drop-down fields

        Not place-tools
      3. Filter pipelinerun in labels for highlighting:

        Example query to filter pipelinerun in labels for highlighting

        {
          "query": {
        	"match": {
          	"kubernetes.flat_labels": {
            	"query": "tekton_dev/pipelineRun=",
            	"type": "phrase"
          	}
        	}
          }
        }
        Copy to Clipboard Toggle word wrap

      4. Filter pipeline in labels for highlighting:

        Example query to filter pipeline in labels for highlighting

        {
          "query": {
        	"match": {
          	"kubernetes.flat_labels": {
            	"query": "tekton_dev/pipeline=",
            	"type": "phrase"
          	}
        	}
          }
        }
        Copy to Clipboard Toggle word wrap

    3. From the Available fields list, select the following fields:

      • kubernetes.flat_labels
      • message

        Ensure that the selected fields are displayed under the Selected fields list.

    4. The logs are displayed under the message field.

      Figure 1.2. Filtered messages

      Filtered messages

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