Projects sharing features with Client Js

Uptrace is an OpenTelemetry-based observability platform designed to collect, store, and analyze distributed traces, metrics, and logs. It functions as a centralized logging backend, a distributed tracing system, and a metrics engine to monitor application performance and system health. The platform is distinguished by AI-powered operational capabilities, allowing users to query telemetry data and manage monitoring dashboards using natural language. It specifically includes specialized monitoring for generative AI pipelines, tracking token usage and response quality for LLM interactions and r

Vector is a high-performance observability data pipeline designed to collect, transform, and route logs, metrics, and traces across distributed infrastructure. It functions as a modular engine that decouples data ingestion from processing and transmission, utilizing a component-based architecture to connect diverse sources to multiple destinations. The project distinguishes itself through a focus on reliability and flow control. It implements backpressure-aware data movement to prevent data loss during traffic spikes and utilizes disk-backed event buffering to ensure durability during network

The NGINX Ingress Controller is a Kubernetes-native traffic manager that handles external requests and routes them to internal services. It translates Kubernetes API objects and annotations into proxy configurations to manage incoming HTTP, TCP, and UDP traffic. The controller distinguishes itself through advanced traffic steering and security integration. It supports blue-green and canary traffic splitting, as well as content-based and regex path routing. Security is handled at the edge via a web application firewall, denial-of-service protection, and a variety of authentication methods incl

Cerbos is an open-source authorization service that provides a centralized, language-agnostic engine for managing access control. It functions as a policy-as-code platform, allowing teams to define, test, and distribute authorization rules using declarative YAML or JSON configurations. By decoupling access logic from application code, it enables consistent permission enforcement across diverse service stacks. The project distinguishes itself through its ability to translate high-level authorization policies into native database query filters. This capability allows applications to enforce sec

Flagger is a Kubernetes operator designed to automate the lifecycle of application deployments through progressive delivery. It functions as a controller that monitors custom resource definitions to orchestrate complex release strategies, including canary, blue/green, and A/B testing. By continuously reconciling the desired cluster state with the actual environment, it ensures that deployments adhere to defined specifications while managing the underlying infrastructure required for traffic routing. The project distinguishes itself through a sophisticated metric-driven analysis loop that eval

RabbitMQ is a multi-protocol messaging broker that functions as an AMQP message broker, a clustered message queue, and a distributed message stream. It provides a server for translating and bridging communication between diverse messaging standards to connect heterogeneous systems. The system distinguishes itself through distributed broker clustering and federation, using shoveling mechanisms to synchronize data across geographically separate sites. It supports high-throughput, append-only logs for persisting and reading large sequences of messages for real-time processing. The broker covers

VictoriaMetrics is a high-performance, scalable time series database and observability platform designed for long-term storage and analysis of metric, log, and trace data. It functions as a unified backend for monitoring ecosystems, offering full compatibility with industry-standard protocols and query languages. The system is built to handle massive data volumes through a distributed architecture that supports horizontal scaling and efficient data lifecycle management. The platform distinguishes itself through a storage engine that utilizes consistent hashing for data sharding and log-struct

Below is a system metrics recorder and replayer for Linux. It captures live hardware utilization, cgroup hierarchy data, and pressure stall information, saving everything into a single replayable snapshot file. This decouples collection from analysis, allowing you to inspect system state offline as if viewing it in real time. The tool continuously streams metrics to disk during recording, supporting interruption and later replay without data loss. It exports the same internal data in multiple formats—OpenMetrics for direct Prometheus and Grafana ingestion, as well as JSON and CSV for script-b

kube-prometheus is a monitoring stack deployment and orchestration framework. It uses an operator pattern to automate the installation and lifecycle management of Prometheus and Alertmanager via custom resource definitions. The project focuses on scaling data collection through hash-based target sharding and topology-aware distribution to reduce cross-zone traffic. It implements a sidecar-based configuration reloading mechanism and utilizes consistent hashing to distribute scrape targets across multiple instances. The system covers broad observability capabilities including metric data colle

Descheduler is a Kubernetes workload rebalancer and pod eviction manager designed to optimize resource distribution and maintain cluster stability. It identifies and removes pods that no longer satisfy scheduling constraints or health requirements, allowing the cluster to relocate them to more suitable nodes. The project provides specialized capabilities for balancing node resource utilization, enforcing topology spread constraints, and removing duplicate pods to improve distribution. It also functions as an autoscaler helper by compacting workloads onto fewer nodes to facilitate the downscal

Kvrocks is a distributed key-value store and Redis-compatible NoSQL database. It utilizes a RocksDB storage engine to provide disk-based persistence, allowing for high-capacity data storage with reduced memory costs compared to in-memory systems. The system functions as a vector database and full-text search engine, supporting nearest-neighbor searches on vector embeddings and complex document queries via text matching. It employs a proxyless cluster architecture with slot-based routing to distribute data and scale capacity across multiple nodes. The platform covers a wide range of data mana

nodejs-dashboard is a command-line observability tool and performance monitor for Node.js applications. It functions as a terminal-based diagnostic dashboard that tracks real-time resource usage, event loop latency, and process health. The tool uses process injection to capture telemetry and monitor running processes without requiring manual instrumentation of the application source code. It employs a grid-based layout engine to visualize this data, allowing the separation of standard output and error streams into distinct panels for log debugging. Users can define the visual arrangement of

This project is a PyTorch model serving framework designed to deploy and scale machine learning models in production via scalable network endpoints. It functions as a high-performance inference server, optimizer, and model lifecycle manager that handles model loading, request batching, and hardware acceleration. The system distinguishes itself through advanced orchestration and optimization capabilities, such as chaining multiple models into sequential workflows using execution graphs and employing dynamic batching to improve throughput and latency. It provides specialized support for generat

This project is a Go process supervisor designed to start and monitor multiple background programs with automatic restarts and lifecycle management. It functions as a system for coordinating daemon execution, ensuring continuous operation through a central configuration. The supervisor distinguishes itself with multiple remote administration interfaces, including a process management REST API, an XML-RPC controller, and a built-in web dashboard for monitoring and controlling processes. It features a Prometheus monitoring exporter that serves real-time performance metrics via a dedicated HTTP

Hazelcast is a distributed data platform that combines an in-memory data grid with a stream processing engine to support real-time analytics and event-driven applications. It functions as a partitioned, distributed key-value store that replicates data across cluster nodes to provide low-latency access and high availability. The platform also serves as a distributed SQL query engine, allowing users to execute standard SQL statements against both in-memory datasets and external data sources. What distinguishes Hazelcast is its use of a distributed consensus subsystem to maintain strongly consis

Beehive is a self-hosted integration platform and event automation engine. It functions as a plugin-based workflow orchestrator that links independent service plugins to automate data movement between external APIs and hardware. The system acts as an IoT hardware controller for managing network-enabled sockets, smart lighting, and serial port devices via TTY or COM. It also serves as an HTTP webhook gateway, receiving incoming requests to trigger internal workflows and external notifications. Capability areas include event-driven workflow automation with filter-based routing and template-bas

Tetragon is an eBPF-based runtime security and observability toolset designed for Linux and Kubernetes environments. It functions as a security policy manager, observability agent, and enforcement engine that hooks into kernel functions and tracepoints to detect privilege escalation, container escapes, and unauthorized system activity. The project distinguishes itself through its ability to perform real-time, in-kernel enforcement, allowing it to synchronously terminate malicious processes or modify function return values before a system call completes. It provides deep Kubernetes integration

Mox is a self-hosted email server that runs as a single compiled Go binary, handling the full lifecycle of sending and receiving email through SMTP, IMAP4rev2, and a built-in webmail application. It is designed to be operated without external dependencies or runtime plugins, with all mail services — including spam filtering, queue management, and web interfaces for administration and account management — contained in one executable. The server distinguishes itself through automated TLS certificate management via ACME, DNS-based autoconfiguration for email clients, and file-based configuration

KServe is an open platform for deploying and serving generative and predictive AI models on Kubernetes. It defines inference services as custom resources with declarative YAML specifications, enabling a Kubernetes-native approach to model deployment and lifecycle management. The platform leverages Knative-based serverless scaling for automatic scale-to-zero and revision management, and supports a pluggable serving runtime architecture that maps model formats to containerized execution environments. KServe distinguishes itself through model-aware autoscaling that scales replicas based on token

Reth is a modular, high-performance Ethereum execution layer client written in Rust. It serves as a full Ethereum node that syncs, validates, and serves blockchain data, functioning as an archive node implementation, a high-throughput RPC node server, and a snapshot sync tool. The project is built around a modular component architecture that allows assembling custom node behavior by swapping independent Rust crates for consensus, execution, mempool, and networking. The client distinguishes itself through a staged sync pipeline that downloads headers and bodies online before processing the res

proxy.py is a lightweight, dependency-free HTTP and reverse proxy framework built in Python that handles network traffic through asynchronous event loops and multi-core connection distribution. It acts as a customizable proxy server and embedded web server, allowing developers to inspect, route, and modify web traffic programmatically or via command-line execution wrappers. The platform provides in-flight TLS interception and traffic decryption using generated root certificates, alongside modular extension hooks that support custom dashboard interfaces, request handling plugins, and REST API

This is a health monitoring tool for ASP.NET Core applications designed to verify the availability of infrastructure and external dependencies. It provides a system for tracking the status of services and dependencies within an application to maintain distributed system observability. The project distinguishes itself through cluster service discovery, which identifies active health check endpoints by querying cluster APIs, such as those in Kubernetes. It also includes a health status dashboard for visualizing stability trends and a mechanism to connect real-time health status to deployment pi

Giropops-monitoring is an integrated observability platform designed to monitor the health and performance of containerized infrastructure. It provides a containerized suite that orchestrates the deployment of monitoring services, enabling the collection, storage, and visualization of system metrics across distributed environments. The platform utilizes a pull-based approach to scrape performance data from target nodes, storing these metrics in a specialized time-series database for long-term analysis. Users can inspect this data through interactive, web-based dashboards that render real-time

Node-clinic is a performance profiling suite for Node.js designed to diagnose CPU bottlenecks, memory leaks, and asynchronous event loop issues. It provides specialized diagnostic tools for visualizing asynchronous flows, generating CPU flame graphs, and analyzing heap memory allocation. The suite includes a CPU flame graph tool to identify functions consuming the most processing time, a heap memory analyzer to track object allocation and leaks, and an asynchronous I/O profiler to map operation flows and find event loop bottlenecks. These tools cover broader capabilities in CPU execution pro

dockprom is a monitoring stack based on Prometheus and Grafana designed to track the performance of Docker containers and their underlying hosts. It functions as a complete solution for gathering real-time metrics and displaying them through a self-hosted dashboard. The project includes a suite of tools for collecting container and host metrics, as well as a discovery tool specifically for automatically identifying and adding tagged EC2 instances to the monitoring configuration. The system covers several observability areas, including time-series data storage and the creation of performance

vjtools is a comprehensive Java development toolset and runtime monitor designed for optimizing application performance and ensuring codebase consistency. It provides a suite of JVM diagnostics tools, a performance profiler, and a static analysis system for enforcing coding standards. The project distinguishes itself through specialized runtime observability, including the ability to attach to processes via process ID and inject dynamic probes to monitor method calls without restarting the system. It features container-aware resource detection that reads control group files to report actual C

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