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What GoFr provides—and what you still need to operate
GoFr is an opinionated Go framework that bundles common service plumbing. Its quick start describes routing, structured logging, OpenTelemetry traces, Prometheus metrics, data-source clients, and graceful shutdown as framework features. That means less initial wiring, not a complete observability platform: GoFr does not by itself provide your collector deployment, telemetry retention, dashboards, or alert rules.
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The framework’s own Why GoFr? page puts the choice plainly: “Both approaches are valid; this page describes the situations where GoFr’s trade-off tends to fit.” A minimal router offers more freedom to choose each component, but your team must assemble and maintain logging, tracing, metrics, and integrations. GoFr suits teams that value integrated defaults; independently chosen components may suit teams with established standards or specialized requirements.
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Start a GoFr service
The official quick start lists Go 1.25 or above as a prerequisite and uses port 8000 as the default HTTP port. Check the current quick-start page for version requirements before adopting a newer release, since prerequisites can change.
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Initialize a module and add GoFr:
go mod init example.com/orders, thengo get gofr.dev. -
Create the application with
app := gofr.New(). -
Register an HTTP route on the application using GoFr’s routing API.
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Start serving requests with
app.Run().
See the GoFr quick start for the current imports and route-registration example. The important operational point is that instrumentation is part of the framework’s service baseline; it still needs deliberate destinations and deployment configuration.
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| Signal | Useful for | GoFr behavior and configuration |
|---|---|---|
| Logs | What event occurred, its outcome, and relevant request context. | Default level is INFO. Set LOG_LEVEL to DEBUG, INFO, NOTICE, WARN, ERROR, or FATAL. |
| Metrics | How the service behaves across requests and over time, including rates, durations, and resource use. | Prometheus-compatible endpoint at /metrics, served on port 2121 by default. |
| Traces | How a request travels through service and downstream operations, and where time is spent along that path. | GoFr documents automatic OpenTelemetry request and response traces, correlation propagation, and OTLP export configuration. |
Logging: inspect events without leaking data
GoFr’s documented logs can include a request correlation ID, status, request time, database activity, configuration reads, and missing-configuration events. A structured event might conceptually look like {"correlation_id":"…","status":200,"request_time":"…"}; use the actual GoFr output rather than assuming this illustrative shape is its exact schema. The correlation ID helps connect an event with a request, but a log line alone does not show a detailed latency breakdown across the request path.
INFO is the documented default. DEBUG can increase volume and create performance and security risks, so use it for development or controlled troubleshooting rather than enabling it indiscriminately in production. Treat log content as an explicit data-handling decision; do not put credentials, tokens, or sensitive request payloads into logs.
Metrics: expose measurements, then arrange collection
GoFr documents runtime and memory gauges; HTTP response histograms; SQL connection and query measures; Redis command timings; Pub/Sub operation counters; retry counts; circuit-breaker state; and GraphQL counts, errors, and durations. The endpoint uses Prometheus/OpenMetrics-compatible text format. Setting METRICS_PORT=0 disables the metrics server, so verify the setting and endpoint reachability when a collector reports missing data.
The documented default cardinality limit is 2,000 distinct label sets per instrument per collection cycle, inclusive of the overflow slot. Cardinality can grow unexpectedly when labels contain unbounded values such as user IDs or raw URLs. Keep labels bounded, and review GoFr’s observability configuration for the current configurable limit and behavior.
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Expose the endpoint only to the intended collection path. A running endpoint is not evidence that metrics are being retained or monitored: configure a compatible collector, dashboards, alert rules, and retention in the platform that operates them.
Traces: export context beyond the service
GoFr documents automatic OpenTelemetry traces for requests and responses. It generates an X-Correlation-ID, returns it in response headers, and propagates it to downstream requests. Its documentation also describes active trace-context propagation across supported Pub/Sub publish and subscribe boundaries.
The observability guide recommends OTLP and documents TRACE_EXPORTER, TRACER_URL, TRACER_RATIO, and optional TRACER_HEADERS. It discusses Jaeger and GoFr Tracer options; the Zipkin exporter is marked deprecated in favor of OTLP. Confirm the supported exporter values and endpoint details in the current GoFr observability guide before configuring a deployment.
Sampling controls the volume and cost of exported traces against the risk of missing useful events. GoFr documents a ratio from zero to one. Its Kubernetes guide offers TRACER_RATIO=0.1 as a sensible production starting example, not a universal optimum. Validate a ratio against actual traffic, backend capacity, retention, and incident-investigation needs.
Configure Kubernetes probes and graceful termination
GoFr’s Kubernetes guide assigns distinct purposes to its health endpoints. Use the liveness endpoint to identify a wedged process and readiness to decide whether an instance should receive traffic.
| Endpoint or mechanism | Operational purpose | Deployment guidance |
|---|---|---|
/.well-known/alive |
Liveness | Use to detect a process that is no longer functioning. Avoid coupling it to transient dependency availability. |
/.well-known/health |
Readiness | Use to determine whether the instance should receive traffic; register dependency checks as appropriate. |
/metrics on the metrics port |
Metrics scraping | Expose through a named metrics service port for a compatible collector. |
| SIGTERM and graceful shutdown | Safe termination | Allow in-flight requests to finish within the pod’s termination grace period. |
Making liveness depend on a database or other dependency can turn a temporary outage into a restart loop: the process may be healthy enough to recover, but Kubernetes repeatedly kills it because the dependency remains unavailable. Reserve dependency-sensitive checks for readiness unless the service has a specific reason to treat that dependency failure as a process failure.
Store non-secret environment configuration in a ConfigMap and credentials or API keys in a Secret. Give termination grace enough time for the service’s request durations and shutdown behavior. The GoFr guide’s 45-second grace period is a typical API example, not a universal value; its sample replica counts and optional HPA likewise need to be sized for actual warmup, load, and platform requirements.
Connect collectors and backends deliberately
GoFr names Prometheus, Grafana Alloy, OpenTelemetry Collector, VictoriaMetrics, and Datadog Agent as possible metric-collection paths. These are examples of compatible collector approaches, not collector configurations shipped by GoFr. For tracing, configure an OTLP destination that your chosen backend accepts.
Choose the collection and backend path against the needs of your service and organization:
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Protocol and signal coverage: confirm support for the OTLP or Prometheus/OpenMetrics path you intend to use, and verify which signals the destination accepts.
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Operations burden: decide who deploys, secures, upgrades, and monitors collectors and backends.
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Access and tenancy: check authentication, network boundaries, and how teams or environments are separated.
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Control of volume and retention: align sampling, metric cardinality, storage retention, and incident needs.
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Portability: account for existing organizational standards and the migration effort if a collector or backend changes.
Collectors and backends are platform choices; dashboards, alerting, retention, credentials, and endpoint exposure need their own configuration. Avoid exposing an unauthenticated metrics or telemetry endpoint beyond the network that requires it.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Production readiness checklist
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Confirm the current Go and GoFr versions and the documented exporter configuration for those versions.
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Set an explicit log level and review logged fields for sensitive information.
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Choose a trace sampling ratio based on traffic, cost, retention, and investigation needs.
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Keep metric labels bounded and choose an appropriate cardinality limit.
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Configure a collector to scrape the metrics endpoint and export traces to an OTLP destination.
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Verify collection, retention, dashboards, and alerts independently; framework instrumentation does not configure them.
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Keep readiness and liveness checks separate, and validate termination grace against real request and shutdown behavior.
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Limit telemetry endpoint access and place credentials in Kubernetes Secrets rather than ConfigMaps.
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