prometheus/client_js

Features

• Prometheus Client Libraries - Provides counters, gauges, histograms and summaries for instrumenting Node.js applications so a Prometheus server can scrape their metrics.
• Prometheus Metrics Exporters - Instruments Node.js applications with counters, gauges, histograms and summaries that a Prometheus server can scrape over HTTP.
• Node.js Resource Monitoring - Tracks event loop lag, heap and system memory, garbage collection and other process-level signals to catch resource problems early.
• Default Runtime Metrics Collectors - Gathers recommended process and runtime measurements such as event loop lag, active handles, garbage collection and version info on every scrape.
• Metrics Text Renderers - Renders all registered metrics as plain text in Prometheus or OpenMetrics format and supplies the matching content type for HTTP responses.
• Multi-Process Metric Aggregation - Combines measurements from cluster workers or worker threads into one scrape output so a multi-process service reports a single view.
• Monotonic Counter Metrics - Provides counters that only increase and reset on process restart, incremented per event so rates and totals can be scraped.
• Node.js Runtime Metrics Collectors - Collects default Node.js process and runtime measurements including event loop lag, heap and memory usage, active handles and garbage collection activity.
• Custom Metric Definitions - Lets applications define counters, gauges, histograms and summaries with names and help text, and refresh values through a collect function at scrape time.
• Value Distribution Histograms - Records observations into histograms with configurable buckets or summaries with sliding-window quantiles to analyse latency and size distributions.
• Streaming Quantile Summaries - Estimates summary quantiles over a sliding window using a streaming digest, so distributions are reported without storing every observation.
• Event Loop Lag Monitors - Measures event loop lag and busy time to reveal responsiveness problems in the running application.
• Gauge Metric Tracking - Provides gauges whose value can be set, raised or lowered freely, such as memory use or queue size, with the latest reading exposed for scraping.
• OpenMetrics Endpoints - Renders registered metrics in Prometheus text or OpenMetrics format with matching content types for HTTP response headers.
• Heap Memory Monitoring - Reports total and used heap size, heap breakdowns by memory space and system memory so growth and pressure can be watched.
• Pull-Based Metric Scraping - Renders current metric values on demand so a Prometheus server can pull them periodically over HTTP.
• Metric Exemplar Correlations - Attaches exemplars with trace and span identifiers to counter and histogram samples so OpenMetrics output links to distributed traces.
• Metric Label Dimensions - Lets users declare label names and attach values by object, chained call or position, including timers whose labels are completed after start.
• Cluster Worker Metric Merging - Combines metrics from all cluster workers or worker threads into one scrape result with a configurable aggregation method per metric.
• Multi-Process Metric Aggregators - Merges metrics from Node.js cluster workers and worker threads into one scrape result with a configurable aggregation method per metric.
• Pushgateway Clients - Includes a client that pushes, replaces or deletes metrics on a Pushgateway so short-lived and batch jobs can still report data.
• Metric Registries - Registers metrics into the global registry or separate custom registries so groups of metrics can be organised and served together from one endpoint.
• Push Gateways - Sends, overwrites or deletes metrics on a Pushgateway for short-lived jobs, with support for groupings, custom request options and gateways needing no job name.

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