Monitor a NestJS app in layers: check whether it can serve traffic, collect useful and safe logs, then track latency, failures, traces, runtime behavior, and application-specific metrics. Health checks can reveal that a service or dependency is unhealthy; observability signals help explain what is failing and why.
Start with health checks that match your deployment
NestJS documents @nestjs/terminus for health checks covering databases, external services, and custom indicators. A platform or infrastructure component can call a health endpoint periodically and use its result when deciding whether to route traffic.
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Define the endpoint’s behavior around your deployment’s needs. Liveness asks whether the process should remain running; readiness asks whether it should receive work. A dependency failure may mean an instance cannot serve requests, but it does not automatically mean the process should be restarted. Decide which failures affect readiness, which affect liveness, and how the platform responds to each.
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- Keep health-check behavior aligned with the orchestration or hosting platform’s routing and restart rules.
- Filter inbound health checks from application instrumentation where appropriate, so routine probes do not obscure user traffic.
Make production logs useful and safe
Logs provide event context for investigating incidents. NestJS’s production guidance recommends recording useful error detail while avoiding passwords, tokens, and other secrets. In distributed systems, correlation IDs help connect events associated with the same request or operation.
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- Use severity levels consistently so operators can distinguish routine information from warnings and failures.
- Reduce debug and verbose logging in production unless a specific investigation calls for it.
- Centralize logs when services run across multiple processes or hosts, so incidents can be searched and analyzed across the system.
Add signals that explain performance and failures
Health status answers whether a service or dependency is healthy. Other signals answer different questions: metrics show trends, traces show where time was spent across operations, and error monitoring helps investigate failures.
| Signal | What it helps answer |
|---|---|
| Metrics | Are latency, traffic, failure rates, or resource levels changing or crossing a threshold? |
| Traces | Which operations or services contributed to a slow or failed request? |
| Error monitoring | Which failures are occurring, and how can they be investigated? |
| Logs | What event details and context were recorded around the behavior? |
Request performance is only part of the picture. NestJS Observe’s documentation describes monitoring for HTTP, GraphQL, gRPC, and microservice transports, as well as queue and cron jobs. The described signals include throughput, latency, failure rates, traces, and error details. Include background work in your monitoring plan if it is important to the service’s behavior.
Watch runtime behavior and instrument business signals
Runtime metrics
NestJS Observe’s SDK guide documents sampling for memory, CPU, garbage collection, and event-loop latency. These signals can help distinguish runtime or application pressure from a problem in an external dependency. The guide says runtime metrics are enabled by default with a default sampling interval of 60,000 milliseconds; check the current SDK instructions before relying on those defaults or changing configuration.
Application-specific metrics
Use custom metrics for values that generic request monitoring cannot explain. NestJS’s manual instrumentation documentation describes counters for totals, gauges for changing levels, and summaries for distributions. Custom metrics can also be reported outside an active request trace, including during startup or scheduled work.
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Choose an instrumentation approach that fits the app
NestJS presents NestJS Observe as an auto-instrumented APM and observability platform designed around Nest request-lifecycle components such as controllers and providers. Its documentation describes request and job monitoring, distributed tracing, error monitoring, runtime profiling, release versioning, and custom metrics.
The SDK guide lists minimum versions of @nestjs/core v11.1.4 and, for applications using GraphQL, @nestjs/graphql v13.4.4. Confirm current compatibility and setup instructions before adding the package. The overview lists these plan allowances, without stating a publication year on the live documentation page:
| Plan | Included events per month | Retention |
|---|---|---|
| Free | 300k | 3 days |
| Pro | 25M | 30 days |
Plan allowances, retention, and feature availability can change, so verify the current terms before choosing a plan. The SDK guide also describes telemetry-silence alerts as a lightweight heartbeat mechanism.
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Quick Recap
Build a practical monitoring workflow
- Establish health behavior. Add health checks for the dependencies required to serve work, and configure readiness and liveness according to how your deployment routes traffic and restarts processes.
- Set logging rules. Record actionable errors, use consistent severity levels and correlation IDs where needed, and keep secrets out of logs.
- Instrument requests and jobs. Track latency, throughput, failures, and traces for the transports and background work your app uses.
- Observe runtime and service-specific behavior. Add runtime signals and custom metrics that help explain incidents or operational thresholds.
- Define alerts and review them. Alert on actionable failures or sustained changes, and ensure each alert points to signals that help diagnose the cause.
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