Open Source JavaScript Observability Tools

Grafana Open Source is a leading open-source visualization and observability platform that lets you query, visualize, alert on, and explore your data—regardless of where it’s stored. With support for 100+ data source plugins (such as Prometheus, Loki, Elasticsearch, InfluxDB, SQL/NoSQL databases, OpenTelemetry, and more), you can unify metrics, logs, traces, and other observability signals in one place. Grafana OSS empowers you to build dynamic, reusable dashboards with rich visualizations, template variables, interactive filtering, and cross-panel linking. Its Explore mode enables ad-hoc queries and side-by-side comparisons of time ranges, queries, and data sources. Grafana also includes built-in alerting, allowing you to define threshold-based rules and send notifications to external systems (e.g. Slack, PagerDuty, OpsGenie). Backed by a strong community and open governance, Grafana OSS is free to use, modify, and deploy under the AGPL-3.0 license.

Your one-stop shop for sending, monitoring, and testing RESTful, gRPC, GraphQL, Websocket, OpenAPI, WebRTC, Webhooks, and streaming API requests. Now with Stress testing and Mocking. Swell supports full HTTP2 multiplexing of requests and responses. HTTP requests to the same host will be sent over the same connection. Swell will attempt to initiate an HTTP2 connection for all HTTPS requests by default, but will revert to HTTP1.1 for legacy servers. Multiple concurrent streams are allowed for each connection.

Visualize distributed tracing with Jaeger. Distributed tracing observability platforms, such as Jaeger, are essential for modern software applications that are architected as microservices. Jaeger maps the flow of requests and data as they traverse a distributed system. These requests may make calls to multiple services, which may introduce their own delays or errors. Jaeger connects the dots between these disparate components, helping to identify performance bottlenecks, troubleshoot errors, and improve overall application reliability. Jaeger is 100% open source, cloud native, and infinitely scalable.

Artillery is cloud-native, open source, and integrates with your favorite monitoring and CI/CD stack. Load test anything, at any scale. The most advanced load-testing platform in the world. Get started and run a test in minutes from your local machine. Then scale it out effortlessly. Free & open-source. Artillery scales like no other. Run your tests from your own AWS account with no infra to set up or manage. Use Playwright to load test with real browsers. Test HTTP, WebSocket, Socket.io, gRPC, Kafka, HLS, and more. Write scenarios with multi-step interactions. Designed for testing transactional APIs and web apps. Use ready-made integrations or write custom logic in Node.js, using any of the thousands of useful npm modules. Artillery integrates with the software you know, love and rely on.

This is the official Node.js application performance monitoring (APM) agent for the Elastic Observability solution. It is a Node.js package that runs with your Node.js application to automatically capture errors, tracing data, and performance metrics. APM data is sent to your Elastic Observability deployment -- hosted in Elastic's cloud or in your own on-premises deployment -- where you can monitor your application, create alerts, and quick identify root causes of service issues. First, you will need an Elastic Stack deployment. This is a deployment of APM Server (which receives APM data from the APM agent running in your application), Elasticsearch (the database that stores all APM data), and Kibana (the application that provides the interface to visualize and analyze the data). If you do not already have an Elastic deployment to use, follow this APM Quick Start guide to create a free trial on Elastic's cloud.

All the greatest observability formats and integrations you love, at once - LGTM Drop-in compatible. Let's get Polyglot. qryn independently implements popular observability standards, protocols and query languages. Make sure you have sufficient memory and disk resources allocated for your node service and clickhouse server when dealing with large amounts of data and fingerprints. We suggest 8GB RAM or higher for most setups with 100k-1M fingerprints. Observe your daily and weekly data consumption to forecast your disk usage requirements. Compression codecs and other optimizations can be performed at the ClickHouse level.

This project is part of the landscape of Cloud Native Computing Foundation in the Observability and Analysis - Chaos Engineering section. Backed by the teams at platform engineering.it and devopstribe.it, which provides enterprise-grade features and certified resilience services for your Kubernetes infrastructure.

Swagger-stats is a middleware for monitoring REST APIs, offering real-time metrics, detailed performance analysis, and request tracking.