Awesome GitHub RepositoriesObservability Stacks

SigNoz is a full-stack observability platform designed to collect, store, and visualize metrics, logs, and distributed traces in a unified environment. It leverages OpenTelemetry-based data collection to ingest telemetry from diverse sources using vendor-neutral protocols, ensuring interoperability across complex microservices architectures. The platform utilizes a high-performance columnar storage engine to enable rapid aggregation and filtering, providing a centralized backend for monitoring application health and performance. What distinguishes the platform is its focus on automated instru

This project is a comprehensive template for building enterprise-grade applications using clean architecture principles. It provides a structured foundation that decouples core business logic from infrastructure concerns, ensuring that domain entities remain independent of specific frameworks or database implementations. By utilizing a mediator-based request dispatching pattern, the system separates state-mutating commands from read-only queries, promoting a clean separation of concerns across the entire codebase. The architecture is organized into vertical slices, grouping related logic and

Quarkus is a Kubernetes-native Java framework designed for building high-performance, memory-efficient applications. It utilizes ahead-of-time native compilation to transform Java code into standalone, optimized binaries that eliminate the need for a virtual machine, enabling rapid startup and reduced memory consumption. By performing code augmentation during the build phase, it shifts heavy processing tasks away from runtime, ensuring that applications are optimized for cloud-native environments. The framework distinguishes itself through a unified approach to reactive and imperative program

Keep is an open-source AIOps alert management platform that aggregates, deduplicates, and orchestrates the lifecycle of alerts from multiple monitoring tools. It functions as a multi-provider integration hub to centralize the flow of data between observability, ticketing, and communication tools. The platform distinguishes itself through incident workflow automation and AI-powered enrichment. It uses a declarative workflow engine to execute multi-step operational sequences and integrates large language models to summarize event data and correlate technical logs for faster incident resolution.

The Prometheus Operator is a Kubernetes monitoring orchestrator and controller that manages Prometheus clusters and observability components through declarative custom resources. It functions as a custom resource controller that translates high-level Kubernetes resource definitions into the configuration files required by the underlying monitoring software. The project automates the deployment, scaling, and lifecycle of an observability stack, including the integration of components like Thanos and Alertmanager. It distinguishes itself by syncing monitoring targets, alerting rules, and scrape

This project is a containerized error tracking platform and monitoring suite designed for self-hosted deployment on private infrastructure. It provides a collection of services for capturing and analyzing software crashes and exceptions, ensuring that sensitive application data remains within a controlled environment. The system includes specialized tooling for air-gapped deployment, allowing the software to be installed and operated on servers without internet access through the manual transfer of container images. It also supports corporate network integration via proxy configurations to ma

This project is a comprehensive educational resource and curriculum focused on site reliability engineering, distributed systems, and infrastructure operations. It provides technical guides, a systems engineering course, and instructional manuals designed to teach the principles of managing large-scale computing environments. The curriculum covers high-level architectural design for scalability and resilience, including fault-tolerant infrastructure, high-availability patterns, and microservices decomposition. It emphasizes the practical application of site reliability engineering through the

dockerlabs is a collection of educational labs and technical tutorials designed to teach the fundamentals of containerization and microservice architecture. It provides instructional material and hands-on exercises covering image optimization, security training, infrastructure setup, and cluster orchestration. The project features specific courses and guides focused on reducing image size through multi-stage builds, securing workloads via vulnerability scanning and encrypted networks, and deploying multi-node clusters with high availability using Swarm orchestration. The materials cover a br

This project is a production-ready enterprise boilerplate and starter for building high-performance web applications with Next.js. It provides a foundational architecture for large-scale application bootstrapping, combining a TypeScript web starter with a pre-configured project structure and professional toolset. The project distinguishes itself through an integrated suite of operational tools, including CI/CD deployment pipelines, infrastructure-as-code provisioning, and a component-driven UI development sandbox. It incorporates a utility-first styling architecture using Tailwind CSS and a l

This project is a reference implementation of a distributed system built using Spring Cloud Alibaba, Spring Boot, and JDK 17. It serves as a comprehensive model for implementing a microservices architecture. The system integrates a wide range of distributed patterns, including global transaction coordination for data consistency, OAuth2 and JWT for identity management, and Kubernetes-based container orchestration. It features a dedicated observability stack for distributed request tracing, log aggregation, and service health monitoring. The implementation covers several functional domains, i

Tye ist ein lokaler Entwicklungs-Orchestrator und Manager für verteilte Anwendungen, der für .NET-Microservices entwickelt wurde. Er koordiniert den Start und die Kommunikation mehrerer Dienste, einschließlich Frontends, Backends und Datenbanken, und ermöglicht es, diese mit einem einzigen Befehl als isolierte Container auf einem lokalen Host auszuführen. Das Tool zeichnet sich durch die Automatisierung von Service Discovery und Netzwerkadressauflösung aus, wodurch hartcodierte URLs zwischen Diensten überflüssig werden. Es unterstützt zudem den Übergang von der lokalen Entwicklung zur Produktion durch Containerisierung von Anwendungen und die Generierung der für Kubernetes-Deployments erforderlichen Manifeste. Zu den umfassenden Funktionen gehören das Mapping von Quellcode-Verzeichnissen auf Dienstdefinitionen, das Injizieren von Umgebungsvariablen zur Laufzeit sowie die Integration externer Infrastruktur-Abhängigkeiten wie Redis und MongoDB. Es unterstützt zudem das Management von Multi-Repository-Projekten und verbindet verteilte Anwendungen mit externen Observability-Stacks für Logging und Tracing.

Pigsty is a comprehensive database infrastructure orchestration platform designed to automate the full lifecycle of high-availability PostgreSQL clusters. It functions as an infrastructure-as-code framework that manages cluster coordination, node provisioning, and service discovery through idempotent playbooks. By integrating distributed consensus mechanisms, the platform ensures automated failover and consistent state enforcement across diverse environments, including bare metal and virtualized infrastructure. The platform distinguishes itself through a robust suite of operational capabiliti

Dieses Projekt ist eine Referenzimplementierung und ein architektonischer Bauplan für den Aufbau verteilter Systeme unter Verwendung des go-zero-Frameworks. Es bietet ein vollständiges Microservices-Boilerplate und ein standardisiertes Projektlayout, um API- und RPC-Services mit konsistenten Ordnerstrukturen zu bootstrappen. Die Implementierung zeichnet sich durch einen umfassenden Leitfaden und eine Codebasis für Service-Discovery, Rate-Limiting und Circuit-Breaking aus. Sie demonstriert eine Observability-Stack-Integration, die verteiltes Tracing, Metrikerfassung und zentralisiertes Logging über mehrere Microservices hinweg koordiniert. Das System deckt ein breites Spektrum verteilter Funktionen ab, einschließlich asynchronem Messaging via Publish-Subscribe-Modell, verteiltem Transaktionsmanagement für Datenkonsistenz und einem Gateway-Aggregation-Pattern zur Trennung externer Requests von interner Kommunikation. Es enthält zudem automatisierte Codegenerierung aus Definitionen und Continuous-Delivery-Pipelines für Container-Deployments.

Pigsty is a full-stack orchestration suite for deploying, monitoring, and managing high-availability PostgreSQL clusters and their supporting infrastructure. It functions as a cluster management platform and high-availability suite that automates failover, manages virtual IPs, and ensures data consistency through distributed consensus. The project distinguishes itself by providing a comprehensive database infrastructure-as-code framework and a dedicated observability stack. It incorporates a backup and recovery manager supporting point-in-time recovery via S3-compatible object storage, alongs

DeepOps ist eine Full-Stack-Observability-Plattform und ein Tool zur Überwachung der Anwendungsleistung. Es dient als verteilte Service-Observability-Suite, die Antwortzeiten, Ressourcennutzung und Service-Gesundheit über verschiedene Infrastrukturschichten hinweg verfolgt. Die Plattform fungiert als Cross-Stack-Telemetrie-Aggregator, der Metriken und Logs in einem einzigen Datenstrom vereint. Sie enthält ein heuristisches Anomalieerkennungssystem, das Leistungs-Baselines analysiert, um statistische Ausreißer zu identifizieren und Betriebsausfälle vorherzusagen. Das System deckt ein breites Spektrum an Überwachungsfunktionen ab, darunter Latenzüberwachung in Echtzeit, Korrelation verteilter Traces und Cross-Layer-Ressourcenprofiling. Es nutzt mehrdimensionale Datenindizierung, um Systemmetriken über komplexe Technologie-Stacks hinweg zu filtern und zu analysieren.

This project is a containerized local AI infrastructure stack designed to deploy large language models and vector databases on private hardware. It functions as an orchestration platform that combines AI runners, knowledge graphs, and a visual workflow builder for creating agentic chatflows and automating tasks via tool integration. The platform distinguishes itself through a low-code approach to agent orchestration, utilizing a visual interface to design complex sequences and connect agents to external tools and search engines. It includes a dedicated local observability stack to track promp