Visão geral da API Observability

A API Observability usa recursos personalizados do Kubernetes e depende do modelo de recursos do Kubernetes (KRM) para provisionar e gerenciar recursos de geração de registros e monitoramento.

Use a API Observability para gerenciar o ciclo de vida dos serviços de observabilidade em uma determinada organização ou projeto personalizado. O ciclo de vida dos serviços de observabilidade inclui operações como instalação, upgrade e desinstalação. Implante um recurso personalizado no seu projeto de acordo com o serviço de observabilidade que você quer gerenciar.

Muitos serviços de observabilidade estão disponíveis automaticamente para um projeto provisionado, por exemplo, geração de registros, monitoramento e alertas.

Endpoint de serviço

Os URLs a seguir são os endpoints da API KRM de observabilidade:

  • Grupo de geração de registros:

    https://MANAGEMENT_API_SERVER_ENDPOINT/apis/logging.gdc.goog/v1
    
  • Grupo de monitoramento:

    https://MANAGEMENT_API_SERVER_ENDPOINT/apis/monitoring.gdc.goog/v1
    
  • Grupo de observabilidade:

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

Substitua MANAGEMENT_API_SERVER_ENDPOINT pelo endpoint do servidor da API Management.

Documento de descoberta

Use o comando kubectl proxy --port=8001 para abrir um proxy para o servidor de API na máquina local. Lá, você pode acessar o documento de descoberta em um dos seguintes 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

Recursos de exemplo

Esta seção contém exemplos de recursos que usam a API KRM de observabilidade.

Grupo de registros

Confira a seguir um exemplo de recurso personalizado LoggingTarget para coletar registros de serviços específicos no projeto project-1:

# 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

Grupo de monitoramento

Confira um exemplo de recurso personalizado MonitoringTarget para coletar métricas de cargas de trabalho no projeto project-1:

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

Grupo de observabilidade

Confira um exemplo do recurso personalizado ObservabilityPipeline para atualizar o tamanho do armazenamento dos painéis no namespace do projeto platform-obs:

# 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.
    ...