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Monitoring

Readiness & Liveness probes

HTTP

Flagd exposes HTTP liveness and readiness probes. These probes can be used for K8s deployments. With default start-up configurations, these probes are exposed on the management port (default: 8014) at the following URLs,

gRPC

Flagd exposes a standard gRPC liveness check on the management port (default: 8014).

Definition of Liveness

The liveness probe becomes active and HTTP 200 status is served as soon as Flagd service is up and running.

Definition of Readiness

The readiness probe becomes active similar to the liveness probe as soon as Flagd service is up and running. However, the probe emits HTTP 412 until all sync providers are ready. This status changes to HTTP 200 when all sync providers at least have one successful data sync. The status does not change from there on.

OpenTelemetry

flagd provides telemetry data out of the box. This telemetry data is compatible with OpenTelemetry.

By default, the Prometheus exporter is used for metrics which can be accessed via the /metrics endpoint. For example, with default startup flags, metrics are exposed at http://localhost:8014/metrics.

Given below is the current implementation overview of flagd telemetry internals,

flagd telemetry

Metrics

flagd exposes the following metrics:

  • http.server.duration
  • http.server.response.size
  • http.server.active_requests
  • feature_flag.flagd.impression
  • feature_flag.flagd.evaluation.reason

Please note that metric names may vary based on the consuming monitoring tool naming requirements. For example, the transformation of OTLP metrics to Prometheus is described here.

Traces

flagd creates the following spans as part of a trace:

  • flagEvaluationService(resolveX) - SpanKind server
  • jsonEvaluator(resolveX) - SpanKind internal
  • jsonEvaluator(setState) - SpanKind internal

Export to OTEL collector

flagd can be configured to connect to OTEL collector. This requires startup flag metrics-exporter to be otel and a valid otel-collector-uri. For example,

flagd start --uri file:/flags.json --metrics-exporter otel --otel-collector-uri localhost:4317

Configure local collector setup

To configure a local collector setup along with Jaeger and Prometheus, you can use following sample docker-compose file and configuration files.

Note - content is adopted from official OTEL collector example

docker-compose.yaml

services:
  # Jaeger
  jaeger-all-in-one:
    image: jaegertracing/all-in-one:latest
    restart: always
    ports:
      - "16686:16686"
      - "14268"
      - "14250"
  # Collector
  otel-collector:
    image: otel/opentelemetry-collector:latest
    restart: always
    command: [ "--config=/etc/otel-collector-config.yaml" ]
    volumes:
      - ./otel-collector-config.yaml:/etc/otel-collector-config.yaml
    ports:
      - "1888:1888"   # pprof extension
      - "8888:8888"   # Prometheus metrics exposed by the collector
      - "8889:8889"   # Prometheus exporter metrics
      - "13133:13133" # health_check extension
      - "4317:4317"   # OTLP gRPC receiver
      - "55679:55679" # zpages extension
    depends_on:
      - jaeger-all-in-one
  prometheus:
    container_name: prometheus
    image: prom/prometheus:latest
    restart: always
    volumes:
      - ./prometheus.yaml:/etc/prometheus/prometheus.yml
    ports:
      - "9090:9090"

otel-collector-config.yaml

receivers:
  otlp:
    protocols:
      grpc:
        endpoint: 0.0.0.0:4317
exporters:
  prometheus:
    endpoint: "0.0.0.0:8889"
    const_labels:
      label1: value1
  otlp/jaeger:
    endpoint: jaeger-all-in-one:4317
    tls:
      insecure: true
processors:
  batch:
service:
  pipelines:
    traces:
      receivers: [ otlp ]
      processors: [ batch ]
      exporters: [ otlp/jaeger ]
    metrics:
      receivers: [ otlp ]
      processors: [ batch ]
      exporters: [ prometheus ]

prometheus.yml

scrape_configs:
  - job_name: 'otel-collector'
    scrape_interval: 10s
    static_configs:
      - targets: [ 'otel-collector:8889' ]
      - targets: [ 'otel-collector:8888' ]

Once, configuration files are ready, use docker-compose up to start the local setup. With successful startup, you can access metrics through Prometheus & traces through Jaeger.