Recorder TypeScript

A runtime recorder for TypeScript apps that captures function timing, events, and optional stacks for debugging, profiling, and reliability analysis.

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About This Tool

This tool records runtime events from TypeScript applications to enable observable telemetry for debugging, profiling, and reliability analysis. It instruments code paths to emit structured events with timestamps, context, and optional stack traces. Conceptually, it wraps target functions or modules to log start/end times and computes durations, counts, and throughput across a run. Benefits include faster root-cause analysis, better understanding of hot paths, and the ability to correlate events across asynchronous tasks via correlation IDs. Core features include a consistent event schema, high-resolution timing, and export capability. Advanced capabilities allow sampling to reduce overhead, module filtering to target critical areas, and aggregation to produce latency histograms or per-endpoint metrics. Use cases span backend services, frontend components, and cross-service tracing scenarios where latency and error patterns matter. The tool emphasizes non-intrusive instrumentation, compatibility with Node.js and modern browsers, and straightforward JSON/NDJSON exports for downstream analytics. Core value lies in turning ad hoc observations into reproducible telemetry that teams can act on, without the overhead of a full profiler.

How to Use

  1. Prepare your TS project to include the instrumentation library and configure runtime settings.
  2. Set environment, max_events, and sampling_rate to balance detail and performance.
  3. Run the application with targeted modules wrapped for event emission.
  4. Export collected events to a file in JSON or JSON Lines at export_path.
  5. Import logs into analytics or visualization tooling to derive latency, throughput, and error insights.
How to use recorder typescript

Frequently Asked Questions

Find Quick Answers

What environments are supported?
Supports Node.js and modern browsers. Instrumentation can be applied to CommonJS/ESM modules and leverages source maps for stack traces when available. Compatibility depends on how modules are loaded in the runtime.
How do I control overhead?
Use the sampling_rate to record a subset of events and max_events to cap total tracking. For low-overhead scenarios, set a smaller sampling_rate and enable selective module filtering to focus on critical paths.
What formats are exported?
Exports can be JSON or JSON Lines (NDJSON). JSON provides a complete array, while NDJSON allows streaming and incremental ingestion by analytics pipelines.
Can it infer TypeScript types?
The tool records runtime events and contexts; it does not perform static type inference. Type information is captured only as context if available via instrumentation or source maps; otherwise, types are not deduced.

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