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,
- Liveness: http://localhost:8014/healthz
- Readiness: http://localhost:8014/readyz
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,
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 serverjsonEvaluator(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.