Observability API overview

The Observability API uses Kubernetes custom resources and relies on the Kubernetes Resource Model (KRM) for provisioning and managing logging and monitoring resources.

Use the Observability API to manage the lifecycle of Observability services in a given organization or custom project. The lifecycle of Observability services includes operations such as install, upgrade, and uninstall. You must deploy a custom resource to your project according to the Observability service you want to manage.

Many Observability services are available automatically for a provisioned project, for example, logging, monitoring, and alerting.

Service endpoint

The following URLs are the API endpoints for the Observability KRM API:

  • Logging group:

    https://GDC_API_SERVER_ENDPOINT/apis/logging.gdc.goog/v1
    
  • Monitoring group:

    https://GDC_API_SERVER_ENDPOINT/apis/monitoring.gdc.goog/v1
    
  • Observability group:

    https://GDC_API_SERVER_ENDPOINT/apis/observability.gdc.goog/v1
    

Replace GDC_API_SERVER_ENDPOINT with the endpoint of the GDC API server.

Discovery document

Use the kubectl proxy --port=8001 command to open a proxy to the API server on your local machine. From there, you can access the discovery document at one of the following URLs:

  • http://127.0.0.1:8001/apis/logging.gdc.goog/v1
  • http://127.0.0.1:8001/apis/monitoring.gdc.goog/v1
  • http://127.0.0.1:8001/apis/observability.gdc.goog/v1

Example resources

This section contains example resources that use the Observability KRM API.

Logging group

The following is an example of a LoggingTarget custom resource to collect logs from specific services on the project-1 project:

# Configures a log scraping job
apiVersion: logging.gdc.goog/v1
kind: LoggingTarget
metadata:
  # Choose a namespace that matches the namespace of the workload pods
  namespace: project-1
  name: my-service-logging-target
spec:
  # Choose a matching pattern that identifies the pods for this job
  # Optional
  # Relationship between different selectors: 'AND'
  selector:
    # The clusters to collect logs from.
    # The default configuration is to collect logs from all clusters.
    # The relationship between different clusters is an 'OR' relationship.
    # For example, the value '["admin", "system"]' indicates to consider
    # the admin cluster 'OR' the system cluster.
    # Optional
    matchClusters:
    - cluster-1
    - cluster-2

    # The pod name prefixes to collect logs from.
    # The Observability platform scrapes all pods with names
    # that start with the specified prefixes.
    # The values must contain '[a-z0-9-]' characters only.
    # The relationship between different list elements is an 'OR' relationship.
    # Optional
    matchPodNames:
      - pod-1
      - pod-2

    # The container name prefixes to collect logs from.
    # The Observability platform scrapes all containers with names
    # that start with the specified prefixes.
    # The values must contain '[a-z0-9-]' characters only.
    # The relationship between different list elements is an 'OR' relationship.
    # Optional
    matchContainerNames:
      - container-1
      - container-2

  # Choose the predefined parser for log entries.
  # Use parsers to map the log output to labels and extract fields.
  # Specify the log format.
  # Optional
  # Options: klog_text, klog_json, klogr, gdch_json, json
  parser: klog_text

  # Specify an access level for log entries.
  # The default value is 'ao'.
  # Optional
  # Options: ao, pa, io
  logAccessLevel: ao

  # Specify a service name to be applied as a label
  # For user workloads consider this field as a workload name
  # Required
  serviceName: service-name

  # The additional static fields to apply to log entries.
  # The field is a key-value pair, where the field name is the key and
  # the field value is the value.
  # Optional
  additionalFields:
    app: workload2
    key: value

Monitoring group

The following is an example of a MonitoringTarget custom resource to collect metrics from workloads on the project-1 project:

apiVersion: monitoring.gdc.goog/v1
kind: MonitoringTarget
metadata:
  # Choose the same namespace as the workload pods
  namespace: project-1
  name: string
spec:
  # Choose matching pattern that identifies pods for this job
  # Optional
  # Relationship between different selectors: AND
  selector:
    # Choose clusters to consider for this job
    # Optional
    # List
    # Default: All clusters applicable to this project.
    # Relationship between different list elements: OR
    matchClusters:
      - string

    # Choose pod-labels to consider for this job
    # Optional: Map of key-value pairs.
    # Default: No filtering by label.
    # Relationship between different pairs: AND
    matchLabels:
      key1: value1

    # Choose annotations to consider for this job
    # Optional: Map of key-value pairs
    # Default: No filtering by annotation
    # Relationship between different pairs: AND
    matchAnnotations:
      key1: value1

  # Configure the endpoint exposed for this job
  podMetricsEndpoints:
    # Choose port either via static value or annotation
    # Optional
    # Annotation takes priority
    # Default: static port 80
    port:
      value: integer
      annotation: string

    # Choose path either via static value or annotation
    # Optional
    # Annotation takes priority
    # Default: static path /metrics
    path:
      value: string
      annotation: string

    # Choose scheme either via static value (http or https) or annotation
    # Optional
    # Annotation takes priority
    # Default: static scheme http
    scheme:
      value: string
      annotation: string

    # Choose the frequency to scrape the metrics endpoint defined in podMetricsEndpoints
    # Optional
    # Default: 60s
    scrapeInterval: string

    # Dynamically rewrite the label set of a target before it gets scraped.
    # https://prometheus.io/docs/prometheus/latest/configuration/configuration/#relabel_config
    # Optional
    # Default: No filtering by label
    metricsRelabelings:
      - sourceLabels:
          - string
        separator: string
        regex: string
        action: string
        targetLabel: string
        replacement: string

Observability group

The following is an example of the ObservabilityPipeline custom resource to update the storage size for dashboards in the platform-obs project namespace:

# Configure observability pipeline
apiVersion: observability.gdc.goog/v1
kind: ObservabilityPipeline
metadata:
  # Don't change the namespace or name.
  namespace: platform-obs
  name: observability-config
spec:
  ...
  monitoring:
    grafana:
      storageSize: 1Gi # Configure the new storage size for dashboards in the project.
    ...