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Using Tekton Results for OpenShift Pipelines observability | Observability in OpenShift Pipelines | Red Hat OpenShift Pipelines 1.16
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Using Tekton Results for OpenShift Pipelines observability

Tekton Results is a service that archives the complete information for every pipeline run and task run. You can prune the PipelineRun and TaskRun resources as necessary and use the Tekton Results API or the opc command line utility to access their YAML manifests as well as logging information.

Tekton Results 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.

Tekton Results concepts

Tekton Results archives pipeline runs and task runs in the form of results and records.

For every PipelineRun and TaskRun custom resource (CR) that completes running, Tekton Results creates a record.

A result can contain one or several records. A record is always a part of exactly one result.

A result corresponds to a pipeline run, and includes the records for the PipelineRun CR itself and for all the TaskRun CRs that were started as a part of the pipeline run.

If a task run was started directly, without the use of a pipeline run, a result is created for this task run. This result contains the record for the same task run.

Each result has a name that includes the namespace in which the PipelineRun or TaskRun CR was created and the UUID of the CR. The format for the result name is <namespace_name>/results/<parent_run_uuid>. In this format, <parent_run_uuid> is the UUUD of a pipeline run or else of a task run that was started directly.

Example result name
results-testing/results/04e2fbf2-8653-405f-bc42-a262bcf02bed

Each record has a name that includes name of the result that contains the record, as well as the UUID of the PipelineRun or TaskRun CR to which the record corresponds. The format for the result name is <namespace_name>/results/<parent_run_uuid>/results/<run_uuid>.

Example record name
results-testing/results/04e2fbf2-8653-405f-bc42-a262bcf02bed/records/e9c736db-5665-441f-922f-7c1d65c9d621

The record includes the full YAML manifest of the TaskRun or PipelineRun CR as it existed after the completion of the run. This manifest contains the specification of the run, any annotation specified for the run, as well as certain information about the results of the run, such as the time when it was completed and whether the run was successful.

While the TaskRun or PipelineRun CR exists, you can view the YAML manifest by using the following command:

$ oc get pipelinerun <cr_name> -o yaml

Tekton Results preserves this manifest after the TaskRun or PipelineRun CR is deleted and makes it available for viewing and searching.

Example YAML manifest of a pipeline run after its completion
  kind: PipelineRun
  spec:
    params:
      - name: message
        value: five
    timeouts:
      pipeline: 1h0m0s
    pipelineRef:
      name: echo-pipeline
    taskRunTemplate:
      serviceAccountName: pipeline
  status:
    startTime: "2023-08-07T11:41:40Z"
    conditions:
      - type: Succeeded
        reason: Succeeded
        status: "True"
        message: 'Tasks Completed: 1 (Failed: 0, Cancelled 0), Skipped: 0'
        lastTransitionTime: "2023-08-07T11:41:49Z"
    pipelineSpec:
      tasks:
        - name: echo-task
          params:
            - name: message
              value: five
          taskRef:
            kind: Task
            name: echo-task-pipeline
      params:
        - name: message
          type: string
    completionTime: "2023-08-07T11:41:49Z"
    childReferences:
      - kind: TaskRun
        name: echo-pipeline-run-gmzrx-echo-task
        apiVersion: tekton.dev/v1
        pipelineTaskName: echo-task
  metadata:
    uid: 62c3b02e-f12b-416c-9771-c02af518f6d4
    name: echo-pipeline-run-gmzrx
    labels:
      tekton.dev/pipeline: echo-pipeline
    namespace: releasetest-js5tt
    finalizers:
      - chains.tekton.dev/pipelinerun
    generation: 2
    annotations:
      results.tekton.dev/log: releasetest-js5tt/results/62c3b02e-f12b-416c-9771-c02af518f6d4/logs/c1e49dd8-d641-383e-b708-e3a02b6a4378
      chains.tekton.dev/signed: "true"
      results.tekton.dev/record: releasetest-js5tt/results/62c3b02e-f12b-416c-9771-c02af518f6d4/records/62c3b02e-f12b-416c-9771-c02af518f6d4
      results.tekton.dev/result: releasetest-js5tt/results/62c3b02e-f12b-416c-9771-c02af518f6d4
    generateName: echo-pipeline-run-
    managedFields:
      - time: "2023-08-07T11:41:39Z"
        manager: kubectl-create
        fieldsV1:
          f:spec:
            .: {}
            f:params: {}
            f:pipelineRef:
              .: {}
              f:name: {}
          f:metadata:
            f:generateName: {}
        operation: Update
        apiVersion: tekton.dev/v1
        fieldsType: FieldsV1
      - time: "2023-08-07T11:41:40Z"
        manager: openshift-pipelines-controller
        fieldsV1:
          f:metadata:
            f:labels:
              .: {}
              f:tekton.dev/pipeline: {}
        operation: Update
        apiVersion: tekton.dev/v1
        fieldsType: FieldsV1
      - time: "2023-08-07T11:41:49Z"
        manager: openshift-pipelines-chains-controller
        fieldsV1:
          f:metadata:
            f:finalizers:
              .: {}
              v:"chains.tekton.dev/pipelinerun": {}
            f:annotations:
              .: {}
              f:chains.tekton.dev/signed: {}
        operation: Update
        apiVersion: tekton.dev/v1
        fieldsType: FieldsV1
      - time: "2023-08-07T11:41:49Z"
        manager: openshift-pipelines-controller
        fieldsV1:
          f:status:
            f:startTime: {}
            f:conditions: {}
            f:pipelineSpec:
              .: {}
              f:tasks: {}
              f:params: {}
            f:completionTime: {}
            f:childReferences: {}
        operation: Update
        apiVersion: tekton.dev/v1
        fieldsType: FieldsV1
        subresource: status
      - time: "2023-08-07T11:42:15Z"
        manager: openshift-pipelines-results-watcher
        fieldsV1:
          f:metadata:
            f:annotations:
              f:results.tekton.dev/log: {}
              f:results.tekton.dev/record: {}
              f:results.tekton.dev/result: {}
        operation: Update
        apiVersion: tekton.dev/v1
        fieldsType: FieldsV1
    resourceVersion: "126429"
    creationTimestamp: "2023-08-07T11:41:39Z"
    deletionTimestamp: "2023-08-07T11:42:23Z"
    deletionGracePeriodSeconds: 0
  apiVersion: tekton.dev/v1

Tekton Results also creates a log record that contains the logging information of all the tools that ran as a part of a pipeline run or task run.

You can access every result and record by its name. You can also use Common Expression Language (CEL) queries to search for results and records by the information they contain, including the YAML manifest.

Preparing to install Tekton Results

You must complete several preparatory steps before installing Tekton Results.

Preparing a secret with an SSL certificate

Tekton Results provides a REST API using the HTTPS protocol, which requires an SSL certificate. Provide a secret with this certificate. If you have an existing certificate provided by a certificate authority (CA), use this certificate, otherwise create a self-signed certificate.

Prerequisites

  • The openssl command-line utility is installed.

Procedure

  1. If you do not have a certificate provided by a CA, create a self-signed certificate by entering the following command:

    $ openssl req -x509 \
-newkey rsa:4096 \
-keyout key.pem \
-out cert.pem \
-days 365 \
-nodes \
-subj "/CN=tekton-results-api-service.openshift-pipelines.svc.cluster.local" \
-addext "subjectAltName = dns:tekton-results-api-service.openshift-pipelines.svc.cluster.local"

    Replace tekton-results-api-service.openshift-pipelines.svc.cluster.local with the route endpoint that you plan to use for the Tekton Results API.

  2. Create a transport security layer (TLS) secret from the certificate by entering the following command:

    $ oc create secret tls -n openshift-pipelines tekton-results-tls --cert=cert.pem --key=key.pem

    If you want to use an existing certificate provided by a CA, replace cert.pem with the name of the file containing this certificate.

Preparing a secret with the database credentials

Tekton Results uses a PostgreSQL database to store data. You can configure the installation to use either a PostgreSQL server that is automatically installed with Tekton Results or an external PostgreSQL server that already exists in your deployment. In both cases, provide a secret with the database credentials.

Procedure

Complete one of the following steps:

  • If you do not need to use an external PostgreSQL server, create a secret with the database user named result and a random password in the openshift-pipelines namespace by entering the following command:

    $ oc create secret generic tekton-results-postgres \
  --namespace=openshift-pipelines \
  --from-literal=POSTGRES_USER=result \
  --from-literal=POSTGRES_PASSWORD=$(openssl rand -base64 20)

    In this command and in subsequent commads, if you configured a custom target namespace for OpenShift Pipelines, use the name of this namespace instead of openshift-pipelines.

  • If you want to use an external PostgreSQL database server to store Tekton Results data, create a secret with the credentials for this server by entering the following command:

    $ oc create secret generic tekton-results-postgres \
  --namespace=openshift-pipelines \
  --from-literal=POSTGRES_USER=<user> \ (1)
  --from-literal=POSTGRES_PASSWORD=<password> (2)

    Replace <user> with the username for the PostgreSQL user that Tekton Results must use. Replace <password> with the password for the same account.

Preparing storage or LokiStack forwarding for logging information

Tekton Results uses separate storage for logging information related to pipeline runs and task runs. You can configure any one of the following types of storage:

  • Persistent volume claim (PVC) on your Red Hat OpenShift Pipelines cluster

  • Google Cloud Storage

  • S3 bucket storage

Alternatively, you can install LokiStack and OpenShift Logging on your OpenShift Container Platform cluster and configure forwarding of the logging information to LokiStack. This option provides better scalability for higher loads.

In OpenShift Pipelines 1.16, the Tekton Results ability to natively store logging information on a PVC, in Google Cloud Storage, and in S3 bucket storage is deprecated and is planned to be removed in a future release.

Logging information is available using the Tekton Results command-line interface and API, irrespective of the type of logging information storage or LokiStack forwarding that you configure.

Procedure

Complete one of the following procedures:

  • To use a PVC, complete the following steps:

    1. Create a file named pvc.yaml with the following definition for the PVC:

        apiVersion: v1
  kind: PersistentVolumeClaim
  metadata:
    name: tekton-logs
  spec:
    accessModes:
    - ReadWriteOnce
    resources:
      requests:
        storage: 1Gi

    2. Apply the definition by entering the following command:

      $ oc apply -n openshift-pipelines -f pvc.yaml

  • To use Google Cloud Storage, complete the following steps:

    1. Create an application credentials file by using the gcloud command. For instructions about providing application credentials in a file, see User credentials provided by using the gcloud CLI in the Google Cloud documentation.

    2. Create a secret from the application credentials file by entering the following command:

      $ oc create secret generic gcs-credentials \
  --from-file=$HOME/.config/gcloud/application_default_credentials.json \
  -n openshift-pipelines

      Adjust the path and filename of the application credentials file as necessary.

  • To use S3 bucket storage, complete the following steps:

    1. Create a file named s3_secret.yaml with the following content:

        apiVersion: v1
  kind: Secret
  metadata:
    name: my_custom_secret
    namespace: tekton-pipelines
  type: Opaque
  stringData:
    S3_BUCKET_NAME: bucket1 (1)
    S3_ENDPOINT: https://example.localhost.com (2)
    S3_HOSTNAME_IMMUTABLE: "false"
    S3_REGION: region-1 (3)
    S3_ACCESS_KEY_ID: "1234" (4)
    S3_SECRET_ACCESS_KEY: secret_key (5)
    S3_MULTI_PART_SIZE: "5242880"
      1 The name of the S3 storage bucket
      2 The S3 API endpoint URL
      3 The S3 region
      4 The S3 access key ID
      5 The S3 secret access key

    2. Create a secret from the file by entering the following command:

      $ oc create secret generic s3-credentials \
  --from-file=s3_secret.yaml -n openshift-pipelines

      1. To configure LokiStack forwarding, complete the following steps:

    3. On your OpenShift Container Platform cluster, install LokiStack by using the Loki Operator and also install the OpenShift Logging Operator.

    4. Create a ClusterLogForwarder.yaml manifest file for the ClusterLogForwarder custom resource (CR) with one of the following YAML manifests, dependings on whether you installed OpenShift Logging version 6 or version 5:

      YAML manifest for the ClusterLogForwarder CR if you installed OpenShift Logging version 6
      apiVersion: observability.openshift.io/v1
kind: ClusterLogForwarder
metadata:
  name: collector
  namespace: openshift-logging
spec:
  inputs:
  - application:
      selector:
        matchLabels:
          app.kubernetes.io/managed-by: tekton-pipelines
    name: only-tekton
    type: application
  managementState: Managed
  outputs:
  - lokiStack:
      labelKeys:
        application:
          ignoreGlobal: true
          labelKeys:
          - log_type
          - kubernetes.namespace_name
          - openshift_cluster_id
      authentication:
        token:
          from: serviceAccount
      target:
        name: logging-loki
        namespace: openshift-logging
    name: default-lokistack
    tls:
      ca:
        configMapName: openshift-service-ca.crt
        key: service-ca.crt
    type: lokiStack
  pipelines:
  - inputRefs:
    - only-tekton
    name: default-logstore
    outputRefs:
    - default-lokistack
  serviceAccount:
    name: collector
      YAML manifest for the ClusterLogForwarder CR if you installed OpenShift Logging version 5
      apiVersion: "logging.openshift.io/v1"
kind: ClusterLogForwarder
metadata:
  name: instance
  namespace: openshift-logging
spec:
  inputs:
  - name: only-tekton
    application:
      selector:
        matchLabels:
          app.kubernetes.io/managed-by: tekton-pipelines
  pipelines:
    - name: enable-default-log-store
      inputRefs: [ only-tekton ]
      outputRefs: [ default ]

    5. To create the ClusterLogForwarder CR in the openshift-logging namespace, log into your OpenShift Container Platform cluster with the OpenShift CLI (oc) as a cluster administrator user, and then enter the following command:

      $ oc apply -n openshift-logging ClusterLogForwarder.yaml

Installing Tekton Results

To install Tekton Results, you must provide the required resources and then create and apply a TektonResult custom resource (CR). The OpenShift Pipelines Operator installs the Results services when you apply the TektonResult custom resource.

Prerequisites

  • You installed OpenShift Pipelines using the Operator.

  • You prepared a secret with the SSL certificate.

  • You prepared storage for the logging information.

  • You prepared a secret with the database credentials.

Procedure

  1. Create the resource definition file named result.yaml based on the following example. You can adjust the settings as necessary.

      apiVersion: operator.tekton.dev/v1alpha1
  kind: TektonResult
  metadata:
    name: result
  spec:
    targetNamespace: openshift-pipelines
    logs_api: true
    log_level: debug
    db_port: 5432
    db_host: tekton-results-postgres-service.openshift-pipelines.svc.cluster.local
    logs_path: /logs
    logs_type: File
    logs_buffer_size: 32768
    auth_disable: true
    tls_hostname_override: tekton-results-api-service.openshift-pipelines.svc.cluster.local
    db_enable_auto_migration: true
    server_port: 8080
    prometheus_port: 9090

  2. Add storage or forwarding configuration for logging information to this file:

    • If you configured a persistent volume claim (PVC), add the following line to provide the name of the PVC:

          logging_pvc_name: tekton-logs

    • If you configured Google Cloud Storage, add the following lines to provide the secret name, the credentials file name, and the name of the Google Cloud Storage bucket:

          gcs_creds_secret_name: gcs-credentials
    gcs_creds_secret_key: application_default_credentials.json (1)
    gcs_bucket_name: bucket-name (2)
      1 Provide the name, without the path, of the application credentials file that you used when creating the secret.
      2 Provide the name of a bucket in Google Cloud Storage. Tekton Chains uses this bucket to store logging information for pipeline runs and task runs.

    • If you configured S3 bucket storage, add the following line to provide the name of the S3 secret:

          secret_name: s3-credentials

    • If you configured LokiStack forwarding, add the following lines to enable forwarding logging information to LokiStack:

          loki_stack_name: logging-loki (1)
    loki_stack_namespace: openshift-logging (2)
      1 The name of the LokiStack CR, typically logging-loki.
      2 The name of the namespace where LokiStack is deployed, typically openshift-logging.

  3. Optional: If you want to use an external PostgreSQL database server to store Tekton Results information, add the following lines to the file:

        db_host: postgres.internal.example.com (1)
    db_port: 5432 (2)
    is_external_db: true
    1 The host name for the PostgreSQL server.
    2 The port for the PostgreSQL server.

  4. Apply the resource definition by entering the following command:

    $ oc apply -n openshift-pipelines -f result.yaml

  5. Expose the route for the Tekton Results service API by entering the following command:

    $ oc create route -n openshift-pipelines \
  passthrough tekton-results-api-service \
  --service=tekton-results-api-service --port=8080

Configuring the retention policy for Tekton Results

By default, Tekton Results stores pipeline runs, task runs, events, and logs indefinitely. This leads to an unnecesary use of storage resources and can affect your database performance.

You can configure the retention policy for Tekton Results at the cluster level to remove older results and their associated records and logs. You can achieve this by editing the TektonResult custom resource (CR).

Prerequisites

  • You installed Tekton Results.

Procedure

  • In the TektonResult CR, configure the retention policy for Tekton Results, as shown in the following example:

    Example retention policy for Tekton Results
    apiVersion: operator.tekton.dev/v1alpha1
kind: TektonResult
metadata:
  name: result
spec:
  options:
    configMaps:
      config-results-retention-policy:
        data:
          runAt: "3 5 * * 0" (1)
          maxRetention: "30" (2)
    1 Specify, in cron format, when to run the pruning job in the database. This example runs the job at 5:03 AM every Sunday.
    2 Specify how many days to keep the data in the database. This example retains the data for 30 days.

Querying Tekton Results using the opc command line utility

You can use the opc command line utility to query Tekton Results for results and records. To install the opc command line utility, install the package for the tkn command line utility. For instructions about installing this package, see Installing tkn.

You can use the names of records and results to retrieve the data in them.

You can search for results and records using Common Expression Language (CEL) queries. These searches display the UUIDs of the results or records. You can use the provided examples to create queries for common search types. You can also use reference information to create other queries.

Preparing the opc utility environment for querying Tekton Results

Before you can query Tekton Results, you must prepare the environment for the opc utility.

Prerequisites

  • You installed Tekton Results.

  • You installed the opc utility.

Procedure

  1. Set the RESULTS_API environment variable to the route to the Tekton Results API by entering the following command:

    $ export RESULTS_API=$(oc get route tekton-results-api-service -n openshift-pipelines --no-headers -o custom-columns=":spec.host"):443

  2. Create an authentication token for the Tekton Results API by entering the following command:

    $ oc create token <service_account>

    Save the string that this command outputs.

  3. Optional: Create the ~/.config/tkn/results.yaml file for automatic authentication with the Tekton Results API. The file must have the following contents:

    address: <tekton_results_route> (1)
token: <authentication_token> (2)
ssl:
   roots_file_path: /home/example/cert.pem (3)
   server_name_override: tekton-results-api-service.openshift-pipelines.svc.cluster.local (4)
 service_account:
   namespace: service_acc_1 (5)
   name: service_acc_1 (5)
    1 The route to the Tekton Results API. Use the same value as you set for RESULTS_API.
    2 The authentication token that was created by the oc create token command. If you provide this token, it overrides the service_account setting and opc uses this token to authenticate.
    3 The location of the file with the SSL certificate that you configured for the API endpoint.
    4 If you configured a custom target namespace for OpenShift Pipelines, replace openshift-pipelines with the name of this namespace.
    5 The name of a service account for authenticating with the Tekton Results API. If you provided the authentication token, you do not need to provide the service_account parameters.

    Alternatively, if you do not create the ~/.config/tkn/results.yaml file, you can pass the token to each opc command by using the --authtoken option.

Querying for results and records by name

You can list and query results and records using their names.

Prerequisites

  • You installed Tekton Results.

  • You installed the opc utility and prepared its environment to query Tekton Results.

  • You installed the jq package.

Procedure

  1. List the names of all results that correspond to pipeline runs and task runs created in a namespace. Enter the following command:

    $ opc results list --addr ${RESULTS_API} <namespace_name>
    Example command
    $ opc results list --addr ${RESULTS_API} results-testing
    Example output
    Name                                                          Start                                   Update
results-testing/results/04e2fbf2-8653-405f-bc42-a262bcf02bed  2023-06-29 02:49:53 +0530 IST           2023-06-29 02:50:05 +0530 IST
results-testing/results/ad7eb937-90cc-4510-8380-defe51ad793f  2023-06-29 02:49:38 +0530 IST           2023-06-29 02:50:06 +0530 IST
results-testing/results/d064ce6e-d851-4b4e-8db4-7605a23671e4  2023-06-29 02:49:45 +0530 IST           2023-06-29 02:49:56 +0530 IST

  2. List the names of all records in a result by entering the following command:

    $ opc results records list --addr ${RESULTS_API} <result_name>
    Example command
    $ opc results records list --addr ${RESULTS_API} results-testing/results/04e2fbf2-8653-405f-bc42-a262bcf02bed
    Example output
    Name                                                                                                   Type                                    Start                                   Update
results-testing/results/04e2fbf2-8653-405f-bc42-a262bcf02bed/records/e9c736db-5665-441f-922f-7c1d65c9d621  tekton.dev/v1.TaskRun              2023-06-29 02:49:53 +0530 IST           2023-06-29 02:49:57 +0530 IST
results-testing/results/04e2fbf2-8653-405f-bc42-a262bcf02bed/records/5de23a76-a12b-3a72-8a6a-4f15a3110a3e  results.tekton.dev/v1alpha2.Log         2023-06-29 02:49:57 +0530 IST           2023-06-29 02:49:57 +0530 IST
results-testing/results/04e2fbf2-8653-405f-bc42-a262bcf02bed/records/57ce92f9-9bf8-3a0a-aefb-dc20c3e2862d  results.tekton.dev/v1alpha2.Log         2023-06-29 02:50:05 +0530 IST           2023-06-29 02:50:05 +0530 IST
results-testing/results/04e2fbf2-8653-405f-bc42-a262bcf02bed/records/e9a0c21a-f826-42ab-a9d7-a03bcefed4fd  tekton.dev/v1.TaskRun              2023-06-29 02:49:57 +0530 IST           2023-06-29 02:50:05 +0530 IST
results-testing/results/04e2fbf2-8653-405f-bc42-a262bcf02bed/records/04e2fbf2-8653-405f-bc42-a262bcf02bed  tekton.dev/v1.PipelineRun          2023-06-29 02:49:53 +0530 IST           2023-06-29 02:50:05 +0530 IST
results-testing/results/04e2fbf2-8653-405f-bc42-a262bcf02bed/records/e6eea2f9-ec80-388c-9982-74a018a548e4  results.tekton.dev/v1alpha2.Log         2023-06-29 02:50:05 +0530 IST           2023-06-29 02:50:05 +0530 IST

  3. Retrieve the YAML manifest for a pipeline run or task run from a record by entering the following command:

    $ opc results records get --addr ${RESULTS_API} <record_name> \
  | jq -r .data.value | base64 -d | \
  xargs -0 python3 -c 'import sys, yaml, json; j=json.loads(sys.argv[1]); print(yaml.safe_dump(j))'
    Example command
    $ opc results records get --addr ${RESULTS_API} \
  results-testing/results/04e2fbf2-8653-405f-bc42-a262bcf02bed/records/e9c736db-5665-441f-922f-7c1d65c9d621 | \
  jq -r .data.value | base64 -d | \
  xargs -0 python3 -c 'import sys, yaml, json; j=json.loads(sys.argv[1]); print(yaml.safe_dump(j))'

  4. Optional: Retrieve the logging information for a task run from a record using the log record name. To get the log record name, replace records with logs in the record name. Enter the following command:

    $ opc results logs get --addr ${RESULTS_API} <log_record_name> | jq -r .data | base64 -d
    Example command
    $ opc results logs get --addr ${RESULTS_API} \
  results-testing/results/04e2fbf2-8653-405f-bc42-a262bcf02bed/logs/e9c736db-5665-441f-922f-7c1d65c9d621 | \
  jq -r .data | base64 -d

Searching for results

You can search for results using Common Expression Language (CEL) queries. For example, you can find results for pipeline runs that did not succeed. However, most of the relevant information is not contained in result objects; to search by the names, completion times, and other data, search for records.

Prerequisites

  • You installed Tekton Results.

  • You installed the opc utility and prepared its environment to query Tekton Results.

Procedure

  • Search for results using a CEL query by entering the following command:

    $ opc results list --addr ${RESULTS_API} --filter="<cel_query>" <namespace-name>

Replace <namespace_name> with the namespace in which the pipeline runs or task runs were created.

Table 1. Example CEL queries for results
Purpose CEL query

The results of all runs that failed

!(summary.status == SUCCESS)

The results all pipeline runs that contained the annotations ann1 and ann2

summary.annotations.contains('ann1') && summary.annotations.contains('ann2') && summary.type=='PIPELINE_RUN'

Searching for records

You can search for records using Common Expression Language (CEL) queries. As each record contains full YAML information for a pipeline run or task run, you can find records by many different criteria.

Prerequisites

  • You installed Tekton Results.

  • You installed the opc utility and prepared its environment to query Tekton Results.

Procedure

  • Search for records using a CEL query by entering the following command:

    $ opc results records list --addr ${RESULTS_API} --filter="<cel_query>" <namespace_name>/result/-

    Replace <namespace_name> with the namespace in which the pipeline runs or task runs were created. Alternatively, search for records within a single result by entering the following command:

    $ opc results records list --addr ${RESULTS_API} --filter="<cel_query>" <result_name>

    Replace <result_name> with the full name of the result.

Table 2. Example CEL queries for records
Purpose CEL query

Records of all task runs or pipeline runs that failed

!(data.status.conditions[0].status == 'True')

Records where the name of the TaskRun or PipelineRun custom resource (CR) was run1

data.metadata.name == 'run1'

Records for all task runs that were started by the PipelineRun CR named run1

data_type == 'TASK_RUN' && data.metadata.labels['tekton.dev/pipelineRun'] == 'run1'

Records of all pipeline runs and task runs that were created from a Pipeline CR named pipeline1

data.metadata.labels['tekton.dev/pipeline'] == 'pipeline1'

Records of all pipeline runs that were created from a Pipeline CR named pipeline1

data.metadata.labels['tekton.dev/pipeline'] == 'pipeline1' && data_type == 'PIPELINE_RUN'

Records of all task runs where the TaskRun CR name stared with hello

data.metadata.name.startsWith('hello') && data_type=='TASK_RUN'

Records of all pipeline runs that took more than five minutes to complete

data.status.completionTime - data.status.startTime > duration('5m') && data_type == 'PIPELINE_RUN'

Records of all pipeline runs and task runs that completed on October 7, 2023

data.status.completionTime.getDate() == 7 && data.status.completionTime.getMonth() == 10 && data.status.completionTime.getFullYear() == 2023

Records of all pipeline runs that included three or more tasks

size(data.status.pipelineSpec.tasks) >= 3 && data_type == 'PIPELINE_RUN'

Records of all pipeline runs that had annotations containing ann1

data.metadata.annotations.contains('ann1') && data_type == 'PIPELINE_RUN'

Records of all pipeline runs that had annotations containing ann1 and the name of the PipelineRun CR started with hello

data.metadata.annotations.contains('ann1') && data.metadata.name.startsWith('hello') && data_type == 'PIPELINE_RUN'

Reference information for searching results

You can use the following fields in Common Expression Language (CEL) queries for results:

Table 3. Fields available in CEL queries for results
CEL field Description

parent

The namespace in which the PipelineRun or TaskRun custom resource (CR) was created.

uid

Unique identifier for the result.

annotations

Annotations added to the PipelineRun or TaskRun CR.

summary

The summary of the result.

create_time

The creation time of the result.

update_time

The last update time of the result.

You can use the summary.status field to determine whether the pipeline run was successful. This field can have the following values:

  • UNKNOWN

  • SUCCESS

  • FAILURE

  • TIMEOUT

  • CANCELLED

Do not use quote characters such as " or ' to provide the value for this field.

Reference information for searching records

You can use the following fields in Common Expression Language (CEL) queries for records:

Table 4. Fields available in CEL queries for records
CEL field Description Values

name

Record name

data_type

Record type identifier

tekton.dev/v1.TaskRun or TASK_RUN tekton.dev/v1.PipelineRun or PIPELINE_RUN results.tekton.dev/v1alpha2.Log

data

The YAML data for the task run or pipeline run. In log records, this field contains the logging output.

Because the data field contains the entire YAML data for the task run or pipeline run, you can use all elements of this data in your CEL query. For example, data.status.completionTime contains the completion time of the task run or pipeline run.

Additional resources