How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.
Prometheus client_golang is the official Go client library for instrumenting applications with Prometheus metrics. It provides a metric registry that manages and exposes custom application metrics like counters, gauges, histograms, and summaries in Prometheus format for HTTP scraping by a Prometheus server. The library also includes a remote read client that sends PromQL queries to a Prometheus server over HTTP and retrieves time series data programmatically.
The main features of prometheus/client_golang are: Instrumentation Libraries, Label-Based Multi-Dimensionality, Safe Metric Accumulation, Custom Metric Registries, Application Metric Tracking, Go Instrumentation, Custom Metric Collectors, Prometheus-Formatted HTTP Endpoints.
Projects with overlapping indexed features include: prometheus/client_python — This is a Prometheus Python client library used for instrumenting Python applications. It provides the tools necessary… prometheus-community/windows_exporter — The Windows Exporter is a service that collects system, performance, and hardware metrics from Windows servers and… prometheus/blackbox_exporter — The Blackbox Exporter is a Prometheus-compatible probe that checks the availability and response correctness of… airtai/faststream — FastStream is an asynchronous Python framework designed for building event-driven microservices. It provides a unified… kubernetes/kube-state-metrics — kube-state-metrics is a Kubernetes metrics exporter that generates Prometheus-compatible metrics from the current… rcrowley/go-metrics — This library provides a toolkit for instrumenting Go applications with performance metrics, enabling the tracking of…
This is a Prometheus Python client library used for instrumenting Python applications. It provides the tools necessary to record counters, gauges, and histograms within a process to monitor application health and expose that data as a Prometheus exposition format provider. The library enables cloud native observability by allowing developers to define custom telemetry and track internal application events. It transforms internal application data into a standardized text format required by Prometheus scrapers for collection. The project covers a variety of monitoring and observability capabil
The Windows Exporter is a service that collects system, performance, and hardware metrics from Windows servers and exposes them via a text-based HTTP endpoint for Prometheus to scrape. It functions as a system metrics collector and service monitor designed to provide observability across Windows environments. The project utilizes a modular collector design that gathers data through Windows Management Instrumentation, native performance counters, and registry keys. It also includes a text-file metrics importer that allows user-defined or third-party business metrics to be read from local plain
The Blackbox Exporter is a Prometheus-compatible probe that checks the availability and response correctness of external services over HTTP, HTTPS, DNS, TCP, ICMP, and gRPC. It exposes probe results as Prometheus metrics, including a probe_success indicator for each endpoint checked, making it a dedicated tool for blackbox monitoring of network services. The exporter uses a probe-module configuration system where reusable settings such as protocol, method, and IP version are defined as named YAML modules. These modules are assigned to target groups through Prometheus relabeling rules, which m
FastStream is an asynchronous Python framework designed for building event-driven microservices. It provides a unified abstraction layer for interacting with various message brokers, enabling developers to manage event production and consumption through a consistent interface while maintaining access to native provider-specific features. The framework centers on a decorator-based routing model that binds application logic directly to broker topics, supported by a built-in dependency injection container that resolves resources at runtime. The framework distinguishes itself through its deep int