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/v1Monitoring group:
https://GDC_API_SERVER_ENDPOINT/apis/monitoring.gdc.goog/v1Observability 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/v1http://127.0.0.1:8001/apis/monitoring.gdc.goog/v1http://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.
...