30 open-source projects similar to getsentry/sentry-java, ranked by shared indexed features. Tags may describe platforms or build tools rather than the same primary purpose. Check each project’s use case, license, and deployment requirements before treating it as a replacement.
Monitoring mixin for Django-prometheus. A set of Grafana dashboards and Prometheus rules for Django.
A self-hosted metrics and notifications platform for Laravel apps
Folsom is an Erlang based metrics system inspired by Coda Hale's metrics (https://github.com/codahale/metrics/). The metrics API's purpose is to collect realtime metrics from your Erlang applications and publish them via Erlang APIs and output plugins. folsom is not a persistent store. There are…
Spring Boot starter (on Maven Central) that adds an Actuator endpoint to detect used / unused / indeterminate starters at runtime, so you can trim dependency bloat.
Export Django monitoring metrics for Prometheus.io
Watch Working Demo on Cursor 📽️ https://youtube.com/shorts/jxjmGyXXz7A
HertzBeat is a real-time observability platform that provides agentless monitoring for servers, databases, and networks. It functions as an infrastructure alerting manager, an OpenTelemetry Protocol log aggregator, and a public status page generator. The platform integrates an analysis engine that uses large language models to process monitoring data and generate system insights. It utilizes a cloud-edge collaborative architecture and distributed collector clustering to scale data gathering across large-scale networks. The system covers a broad range of observability capabilities, including
This project is an application performance monitoring tool and JVM metrics library designed to measure workload behavior and export performance data to external monitoring databases. It serves as an instrumentation toolkit for tracking resource usage and internal runtime behavior within a Java execution environment. The system focuses on application performance measurement and JVM application monitoring, specifically tracking system health and runtime resource analysis to identify bottlenecks and stability issues. It provides a mechanism for external metrics export, sending captured data to t
JavaMelody : monitoring of JavaEE applications
Horizon is a background job orchestrator and worker manager for Redis queues. It provides a monitoring dashboard to track job throughput, wait times, and failure rates, alongside a system for managing job retries, execution timeouts, and worker distribution. The project distinguishes itself through a Redis-backed monitoring interface that identifies system bottlenecks and a queue alerting system that sends notifications when background job wait times exceed defined thresholds. Worker processes are managed via version-controlled configuration files to ensure consistent balancing and scaling ac
Uptime Kuma is a self-hosted monitoring platform designed to track the availability and performance of network services and websites. It functions as a centralized dashboard that executes asynchronous health checks on a scheduled interval, providing real-time visibility into infrastructure health and service uptime. The platform distinguishes itself through a dedicated notification engine that dispatches alerts across multiple third-party messaging services, alongside a public status page generator that allows users to communicate service health and historical metrics via custom domains. Its
This repository contains th Metoro MCP (Model Context Protocol) Server. This MCP Server allows you to interact with your Kubernetes cluster via the Claude Desktop App!
Micrometer is a dimensional metrics library and application metrics facade that provides a vendor-neutral interface for recording performance data. It decouples application instrumentation from specific observability backends, allowing the recording of counters, gauges, and timers using key-value tags for granular analysis. The project features a system of backend adapters that transform and route instrumented data to various external monitoring tools. This includes name normalization to ensure portability across different monitoring systems and the ability to map dimensional data to hierarch
Provides tracing abstractions over tracers and tracing system reporters.
Give your AI coding assistants access to Raygun so they can investigate, explain, and help resolve errors for you.
The Model Context Protocol is a standardized communication framework designed to connect language models to external data sources, functional tools, and interactive user interfaces. It provides a vendor-neutral interface layer that enables AI hosts to discover and execute capabilities across heterogeneous service environments, using a JSON-RPC based messaging standard to facilitate bidirectional communication between clients and servers. The protocol distinguishes itself through a robust capability-based handshake that negotiates feature sets during session initialization, ensuring compatibil