Skip to content

Latest commit

 

History

History
300 lines (247 loc) · 10.3 KB

TektonResult.md

File metadata and controls

300 lines (247 loc) · 10.3 KB

Tekton Result

TektonResult custom resource allows user to install and manage Tekton Result.

TektonResult is an optional component and currently cannot be installed through TektonConfig. It has to be installed seperately.

To install Tekton Result on your cluster follow steps as given below:

  • Make sure Tekton Pipelines is installed on your cluster, using the Operator.

  • Generate a database root password. A database root password must be generated and stored in a Kubernetes Secret before installing results. By default, Tekton Results expects this secret to have the following properties:

    • namespace: tekton-pipelines
    • name: tekton-results-postgres
    • contains the fields:
      • user=<user name>
      • password=<your password>

    If you are not using a particular password management strategy, the following command will generate a random password for you: Update namespace value in the command if Tekton Pipelines is installed in a different namespace..

    export NAMESPACE="tekton-pipelines"
    kubectl create secret generic tekton-results-postgres --namespace=${NAMESPACE} --from-literal=POSTGRES_USER=result --from-literal=POSTGRES_PASSWORD=$(openssl rand -base64 20)
  • Generate cert/key pair. Note: Feel free to use any cert management software to do this!

    Tekton Results expects the cert/key pair to be stored in a TLS Kubernetes Secret. Update the namespace value in below export command if Tekton Pipelines is installed in a different namespace.

    export NAMESPACE="tekton-pipelines"
    # Generate new self-signed cert.
    openssl req -x509 \
    -newkey rsa:4096 \
    -keyout key.pem \
    -out cert.pem \
    -days 365 \
    -nodes \
    -subj "/CN=tekton-results-api-service.${NAMESPACE}.svc.cluster.local" \
    -addext "subjectAltName = DNS:tekton-results-api-service.${NAMESPACE}.svc.cluster.local"
    # Create new TLS Secret from cert.
    kubectl create secret tls -n ${NAMESPACE} tekton-results-tls \
    --cert=cert.pem \
    --key=key.pem
  • Create PVC if using PVC for logging

cat <<EOF > pvc.yaml
apiVersion: v1
kind: PersistentVolumeClaim
metadata:
  name: tekton-logs
  namespace: tekton-pipelines
spec:
  accessModes:
  - ReadWriteOnce
  resources:
    requests:
      storage: 1Gi
EOF
// Apply the above PVC
kubectl apply -f pvc.yaml
  • Once the secrets are created create a TektonResult CR (Check ##Properties) as below.
    kubectl apply -f config/crs/kubernetes/result/operator_v1alpha1_result_cr.yaml
  • Check the status of installation using following command
    kubectl get tektonresults.operator.tekton.dev

Spec

The TektonResult CR is like below:

apiVersion: operator.tekton.dev/v1alpha1
kind: TektonResult
metadata:
  name: result
spec:
  targetNamespace: tekton-pipelines
  db_host: localhost
  db_port: 5342
  db_sslmode: false
  db_enable_auto_migration: true
  log_level: debug
  logs_api: true
  logs_type: File
  logs_buffer_size: 90kb
  logs_path: /logs
  auth_disable: true
  logging_pvc_name: tekton-logs
  secret_name: # optional
  gcs_creds_secret_name: <value>
  gcc_creds_secret_key: <value>
  gcs_bucket_name: <value>
  is_external_db: false
  loki_stack_name: #optional
  loki_stack_namespace: #optional
  

These properties are analogous to the one in configmap of tekton results api tekton-results-api-config documented at [api.md]:https://github.com/tektoncd/results/blob/4472848a0fb7c1473cfca8b647553170efac78a1/cmd/api/README.md

Property "secret_name":

secret_name - name of your custom secret or leave it as empty. It an optional property. The secret should be created by the user on the targetNamespace. The secret can contain S3_ prefixed keys from the result API properties. Please note: the key of the secret should be in UPPER_CASE and values should be in string format. The following keys are supported by this secret.

  • S3_BUCKET_NAME
  • S3_ENDPOINT
  • S3_HOSTNAME_IMMUTABLE
  • S3_REGION
  • S3_ACCESS_KEY_ID
  • S3_SECRET_ACCESS_KEY
  • S3_MULTI_PART_SIZE

Sample Secret File

apiVersion: v1
kind: Secret
metadata:
  name: my_custom_secret
  namespace: tekton-pipelines
type: Opaque
stringData:
  S3_BUCKET_NAME: foo
  S3_ENDPOINT: https://example.localhost.com
  S3_HOSTNAME_IMMUTABLE: "false"
  S3_REGION: region-1
  S3_ACCESS_KEY_ID: "1234"
  S3_SECRET_ACCESS_KEY: secret_key
  S3_MULTI_PART_SIZE: "5242880"

GCS specific Property

The follow keys are needed for enabling GCS storage of logs:

apiVersion: operator.tekton.dev/v1alpha1
kind: TektonResult
metadata:
  name: result
spec:
  gcs_creds_secret_name: <value>
  gcc_creds_secret_key: <value>
  gcs_bucket_name: <value>

We need to create a secret with google application creds for a bucket foo-bar like below:

kubectl create secret generic gcs-credentials --from-file=creds.json

To know more about Application Default Credentials in creds.json that is use to create above secret for GCS, please visit: https://cloud.google.com/docs/authentication/application-default-credentials

In the above example, our properties are:

gcs_creds_secret_name: gcs-credentials
gcc_creds_secret_key: creds.json
gcs_bucket_name: foo-bar

External DB

It is not recommended to use internal DB, operator hard code PVC configuration and DB settings.

If you want to move from internal DB to external DB, please take backup of the DB. If you want to start fresh, then delete previous TektonResult CR. and recreate the fresh one with following instructions:

  • Generate a secret with user name and password for Postgres (subsitute ${password} with your password):
   export NAMESPACE="tekton-pipelines" # Put the targetNamespace of TektonResult where it is going to be installed.
   kubectl create secret generic tekton-results-postgres --namespace=${NAMESPACE} --from-literal=POSTGRES_USER=result --from-literal=POSTGRES_PASSWORD=${password}
  • Create a TektonResult CR like below:
  • Add db_host with DB url without port.
  • Add db_port with your DB port.
  • Set is_external_db to true.
apiVersion: operator.tekton.dev/v1alpha1
kind: TektonResult
metadata:
  name: result
spec:
  targetNamespace: tekton-pipelines
  db_port: 5432
  db_user: result
  db_host: tekton-results-postgres-external-service.pg-redhat.svc.cluster.local
  is_external_db: true
...

LokiStack + TektonResult

Tekton Results leverages external Third Party APIs to query data. Storing of data via Tekton Results is inefficient and bad for performance. It's better to use forwarders like Vector, Promtail, Fluentd for forwarding TaskRun pod Logs from nodes.

Kubernetes (GCP) + LokiStack/Loki

Loki

You can either use Grafana's Helm Repo or operator from OperatorHub to install Loki. Installing via operator simplies certain operations for Tekton Operator. You just need to configure lokistack_name and lokistack_namespace.

In case of helm installation, you will need to configure options field to configure Results API configMap tekton-results-api-config:

LOGS_API
LOGGING_PLUGIN_PROXY_PATH
LOGGING_PLUGIN_API_URL
LOGGING_PLUGIN_TOKEN_PATH
LOGGING_PLUGIN_NAMESPACE_KEY
LOGGING_PLUGIN_STATIC_LABELS
LOGGING_PLUGIN_TLS_VERIFICATION_DISABLE
LOGGING_PLUGIN_FORWARDER_DELAY_DURATION
LOGGING_PLUGIN_QUERY_PARAMS
LOGGING_PLUGIN_QUERY_LIMIT

Please consult the docs here for information on these fields.

These fields allow you to configure how Tekton Results interacts with your Loki backend.

You might need to configure following environment variable to Tekton Results API deployment if you are using some custom CA to generate TLS certificate:

LOGGING_PLUGIN_CA_CERT
  • LOGGING_PLUGIN_FORWARDER_DELAY_DURATION: This is the max duration in minutes taken by third party logging system to forward and store the logs after completion of taskrun and pipelinerun. This is used to search between start time of runs and completion plus buffer duration.

Forwarder

You need to configure forwarder systems to add labels for namespace, pass TaskRun UID/PipelineRun UID in pods and a common label key:value alongwith logs from nodes.

A sample configuration for vector: values.yaml.

OpenShift (LokiStack + OpenShift Logging)

To configure LokiStack with TektonResult, you can use the lokistack_name and lokistack_namespace properties in the TektonResult custom resource. Here's how to do it:

  1. First, ensure that you have LokiStack installed in your cluster.

  2. Then, create or update your TektonResult CR with the following properties:

apiVersion: operator.tekton.dev/v1alpha1
kind: TektonResult
metadata:
  name: result
spec:
  targetNamespace: tekton-pipelines
  // ... other properties ...
  lokistack_name: your-lokistack-name
  lokistack_namespace: your-lokistack-namespace

Replace your-lokistack-name with the name of your LokiStack instance and your-lokistack-namespace with the namespace where LokiStack is installed.

By setting these properties, Operator will configure Tekton Result to use the specified LokiStack instance for log retrieval.

OpenShift Logging

Install the openshift logging operator by following this: Deploying Cluster Logging

If you are installing OpenShift Logging Operator only for TaskRun Logs, then you also need to configure a ClusterLogForwarder:

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 ]