To monitor a Node.js app, instrument it to produce telemetry, then export that data to a backend where you can inspect it. For a small app, begin with exception capture and a few useful metrics; add distributed traces when requests cross services. OpenTelemetry JavaScript provides APIs and SDKs for these signals, but its documented maturity differs: traces and metrics are stable, while logs remain in development (status checked October 11, 2026).
What monitoring means for a Node.js app
Monitoring is a workflow, not a package you install and forget. Your application needs instrumentation to record what it is doing, an export path to move that telemetry, and a backend to display or analyze it. OpenTelemetry JavaScript provides APIs and SDKs for metrics, logs, and traces; the official project documentation currently marks traces and metrics stable and logs in development. OpenTelemetry JavaScript documentation
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- Metrics summarize values over time, such as request counts or durations. Prometheus explains that applications need instrumentation through a language-matched client library to expose internal metrics, and lists Node.js among its client-library options. Prometheus client libraries
- Traces follow an operation through instrumented components and services, helping locate where a request spent time or failed.
- Logs record discrete events. OpenTelemetry’s Node.js logging library is still under development, so do not assume it has the same maturity as the project’s trace and metric support.
- Exceptions capture application errors for investigation. Error tracking can be a practical first step even before you adopt a broader observability setup.
Choose a useful starting point
For one small application
Start by capturing exceptions and recording a small set of metrics tied to questions you actually need to answer, such as whether requests are failing or slowing down. Keep the initial setup narrow enough that you can verify the data is arriving and useful. You do not need distributed tracing simply because it is available.
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Add traces when a request passes through multiple services, queues, or dependencies and you need to distinguish where time or failure occurs. Consistent resource attributes—metadata describing the process or deployment producing telemetry—can help narrow an observation to a container, pod, namespace, or deployment. OpenTelemetry JavaScript documentation
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For an immediate exception-tracking need
Sentry documents a Node SDK for exception capture and performance tracing. This is a distinct entry point from assembling an OpenTelemetry pipeline; the available documentation here does not establish how its current plans compare with alternatives. Sentry Node SDK documentation
Set up OpenTelemetry before application code
The order in which Node loads modules matters. Instrumentation must be initialized before application modules so supported libraries can be patched and generate telemetry. OpenTelemetry’s Node.js getting-started documentation states: “The instrumentation setup and configuration must be run before your application code.” OpenTelemetry Node.js getting-started documentation
- Check runtime and module format. The OpenTelemetry JavaScript documentation supports active and maintenance LTS versions of Node.js; it says older versions may work but are not tested. The getting-started guide includes CommonJS-oriented examples in relevant places, so check its current ESM instructions if your application uses ES modules. OpenTelemetry JavaScript documentation Node.js getting-started documentation
- Install the SDK and instrumentation that fit your app. The Node.js guide demonstrates the Node SDK and automatic instrumentation packages with an Express example. Automatic instrumentation can create spans for supported library activity; coverage depends on the libraries involved.
- Load the setup first. Arrange startup so the instrumentation setup runs before importing or requiring the application modules that it should observe. Copy the matching CommonJS or ESM setup rather than assuming the examples are interchangeable.
- Configure export. Instrumentation creates telemetry, but it does not by itself provide a place to inspect it. Configure an exporter or Collector and a receiving backend, then verify that data reaches the destination.
- Check the result in context. Confirm that the expected signal is arriving and that resource attributes identify the relevant service or deployment. If a library produces no spans, check whether it is supported and whether instrumentation loaded early enough.
Choose where telemetry goes
For production export, OpenTelemetry’s exporter guidance recommends using an OpenTelemetry Collector and describes OTLP exporters. The Collector provides an intermediary for receiving and routing telemetry; the backend is where people inspect it. Documented destination options include Jaeger, Zipkin, Prometheus, and vendor-specific backends. OpenTelemetry JavaScript exporters
For Prometheus metrics, the OpenTelemetry guidance describes two routes: use Prometheus’s OTLP receiver or use the Prometheus exporter. Prometheus also requires application instrumentation through a client library suited to the application language. These are alternative integration choices, not a claim that one is best for every deployment. OpenTelemetry JavaScript exporters Prometheus client libraries
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Self-managed components or a hosted backend?
Neither approach is a universal winner. The right fit depends on who will operate the telemetry pipeline, what signals are needed, and how the data must be handled. The documentation establishes technical capabilities, not current vendor prices, retention policies, privacy terms, or compliance suitability.
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| Decision area | Questions to answer |
|---|---|
| Operations | Who will run, upgrade, secure, and scale the Collector and backend? Self-management gives your team that work; a hosted service changes who operates the backend, but the exact division of responsibility depends on the service. |
| Destination and portability | Does the destination accept OpenTelemetry or OTLP, and can telemetry be routed elsewhere if your needs change? OpenTelemetry documents Collector and exporter paths to several kinds of destination. OpenTelemetry JavaScript exporters |
| Signals and maturity | Do you need exceptions, traces, metrics, or logs now? OpenTelemetry JavaScript documents traces and metrics as stable and logs as in development (checked October 11, 2026). OpenTelemetry JavaScript documentation |
| Application fit | Does the setup support your Node.js version, framework, and instrumented libraries? Does the initialization example match your CommonJS or ESM startup? |
| Cost, retention, privacy, and geography | Review current terms and deployment details for each candidate. The cited technical documentation does not establish vendor-by-vendor answers for these factors. |
Common setup problems to check
- No telemetry appears: confirm the exporter or Collector is configured and that the backend is receiving the signal; installing instrumentation alone is not the full pipeline.
- Spans are missing for a dependency: check whether that library is supported by the selected automatic instrumentation and whether setup ran before application modules loaded.
- The example does not fit the app: verify the Node.js support guidance and follow instructions for the app’s module system rather than copying a CommonJS example into an ESM setup without checking.
- Logs are not available as expected: OpenTelemetry’s Node.js logging library is documented as under development, unlike stable traces and metrics.
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