Open Source Windows Observability Tools - Page 2
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Observability Tools for Windows
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KubeVela
The Modern Application Platform
KubeVela is a modern software delivery platform that makes deploying and operating applications across today's hybrid, multi-cloud environments easier, faster and more reliable. KubeVela is infrastructure agnostic, programmable, yet most importantly, application-centric. It allows you to build powerful software, and deliver them anywhere. Declare your deployment plan as workflow, run it automatically with any CI/CD or GitOps system, extend or re-program the workflow steps with CUE. Glue and orchestrate all your infrastructure capabilities as reusable modules and share the large growing community addons. No ad-hoc scripts, no dirty glue code, just deploy. The deployment workflow in KubeVela is powered by Open Application Model. -
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ODD Platform
First open-source data discovery and observability platform
Unlock the power of big data with OpenDataDiscovery Platform. Experience seamless end-to-end insights, powered by unprecedented observability and trust - from ingestion to production - while building your ideal tech stack! Democratize data and accelerate insights. Find data that fits your use case and discover hints left by your peers to leverage existing knowledge. Explore tags, ownership details, links to other sources and other information to shorten and simplify data discovery phase. Forget unnerved stakeholders and wasting too much time on digging the root cause of data issues when it fails. With ODD’s automatic company-wide ingestion-to-product lineage you’ll have answers in just seconds and stakeholders won’t need to wait. Sleep well, knowing all your data is in check. Forget manual testing, days of debugging, and weeks of worrying. Know the impact of each code change with automatic testing. Enjoy lineage and alerts powered with data quality information. -
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OpenObserve
Elasticsearch/Splunk/Datadog alternative for (logs, metrics, traces)
OpenObserve is a cloud-native observability platform built specifically for logs, metrics, traces, and analytics designed to work at a petabyte scale. It is very simple and easy to operate as opposed to Elasticsearch which requires a couple of dozen knobs to understand and tune which you can get up and running in under 2 minutes. It is a drop-in replacement for Elasticsearch if you are just ingesting data using APIs and searching using Kibana (Kibana is not supported nor required with OpenObserve. OpenObserve provides its own UI which does not require separate installation unlike Kibana). You can reduce your log storage costs by ~140x compared to Elasticsearch by using OpenObserve. Below are the results when we pushed logs from our production Kubernetes cluster to Elasticsearch and OpenObserve using fluent bit. OpenObserve stored data in Amazon s3 and Elasticsearch stored data on Amazon EBS volumes. -
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PacketStreamer
Distributed tcpdump for cloud native environments
Deepfence PacketStreamer is a high-performance remote packet capture and collection tool. It is used by Deepfence's ThreatStryker security observability platform to gather network traffic on demand from cloud workloads for forensic analysis. PacketStreamer sensors are started on the target servers. Sensors capture traffic, apply filters, and then stream the traffic to a central receiver. Traffic streams may be compressed and/or encrypted using TLS. The PacketStreamer receiver accepts PacketStreamer streams from multiple remote sensors and writes the packets to a local pcap capture file. PacketStreamer sensors collect raw network packets on remote hosts. It selects packets to capture using a BPF filter, and forwards them to a central receiver process where they are written in pcap format. Sensors are very lightweight and impose little performance impact on the remote hosts. PacketStreamer sensors can be run on bare-metal servers, on Docker hosts, and on Kubernetes nodes. -
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Robusta
Kubernetes observability and automation
Keep your Kubernetes microservices up and running. Connect your existing Prometheus, gain 360° observability. Robusta is both an automation engine for Kubernetes and a multi-cluster observability platform. Robusta is commonly used alongside Prometheus, but other tools are supported too. By listening to all the events in your cluster, Robusta can tell you why alerts fired, what happened at the same time, and what you can do about it. Robusta can either improve your existing alerts or be used to define new alerts triggered by APIServer changes. -
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Tetragon
eBPF-based Security Observability and Runtime Enforcement
Tetragon is a flexible Kubernetes-aware security observability and runtime enforcement tool that applies policy and filtering directly with eBPF, allowing for reduced observation overhead, tracking of any process, and real-time enforcement of policies. Observe the complete lifecycle of every process on your machine with Kubernetes context awareness. Translate high-level policies for file monitoring, network observability, container security, and more into low-overhead eBPF programs. Synchronous monitoring, filtering, and enforcement completely in the kernel with eBPF. -
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Vector
A high-performance observability data pipeline
Vector is a Rust‑based, high‑performance observability data pipeline tool (agent + aggregator) designed to collect, transform, and route logs and metrics at scale. Created by Datadog, it aims to be the only tool needed from ingestion to vendor output, providing cost-efficient, safe, and flexible telemetry processing. -
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SysGauge
Comprehensive system monitor: real‑time performance, network, disk
SysGauge is a powerful system monitoring and performance analysis tool for Windows that delivers deep insights into your computer’s operation. It provides real‑time visualization of key metrics across multiple domains: CPU and memory usage, disk I/O, network traffic, and active processes. The application features a customizable dashboard with live graphs, gauges, and tables, letting you track trends and spot bottlenecks at a glance. SysGauge supports historical data logging for post‑analysis and capacity planning, and offers alerting for critical conditions (e.g., high CPU load, low disk space). It includes advanced process monitoring with detailed resource breakdowns, service status checks, and network connection tracking. -
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LibreDiagnostics
A desktop utility for real-time hardware monitoring and diagnostics.
Monitoring for your hardware components - CPU - GPU - RAM - Drives - Network - Fans Various customization options, such as - display the app as an app bar (Windows) - autostart after you initially logged in (Windows) - docking location[s] on different screens - adjust application font size & width - tailor update interval to your needs - various color options for you to modify - enable or disable specific monitors, hardware or sensors - and more ! S.M.A.R.T. data of your drives You can show various S.M.A.R.T. attributes of your drives, such as health, temperature, power-on hours and more, by simply clicking on the drives name in the drives monitor. Please check out Github for more details and up-to-date new releases / versions ! https://github.com/Blacktempel/LibreDiagnostics -
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Python Control Systems Library
Feedback control system analysis and design
The Python Control Systems Library, python-control, is a python module that implements basic operations for analysis and design of feedback control systems. This homepage for this project is at http://python-control.org and the code base in maintained at https://github.com/python-control/python-control. Information on this page is out of date, but left here for posterity. -
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SpiceDB
SpiceDB is the open source, Zanzibar-inspired authorization system
Open Source, Google Zanzibar-inspired permissions database to enable fine-grained access control for customer applications. Get started with the SpiceDB playground: https://play.authzed.com/ -
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Apache APISIX for Kubernetes
APISIX Ingress Controller for Kubernetes
Apache APISIX provides rich traffic management features like Load Balancing, Dynamic Upstream, Canary Release, Circuit Breaking, Authentication, Observability, etc. Apache APISIX provides open source API Gateway to help you manage microservices, delivering the ultimate performance, security, and scalable platform for all your APIs and microservices. Apache APISIX is the first open-source API Gateway that includes a built-in low-code Dashboard, which offers a powerful and flexible UI for developers to use. The Apache APISIX Dashboard is designed to make it as easy as possible for users to operate Apache APISIX through a frontend interface. It’s opensource and ever-evolving, feel free to contribute. -
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Apache SkyWalking Rocketbot UI
SkyWalking RocketBot UI
Application performance monitor tool for distributed systems, specially designed for microservices, cloud-native, and container-based (Kubernetes) architectures. End-to-end distributed tracing. Service topology analysis, service-centric observability and API dashboards. Java, .Net Core, PHP, NodeJS, Golang, LUA, Rust, C++, Client JavaScript and Python agents with active development and maintenance. Rover agent works as a metrics collector and profiler powered by eBPF to diagnose CPU and network performance. 100+ billion telemetry data could be collected and analyzed from one SkyWalking cluster. Metrics, Traces, and Logs from mature ecosystems are supported, e.g. Zipkin, OpenTelemetry, Prometheus, Zabbix, Fluentd. BanyanDB, an observability database, created in 2022, aims to ingest, analyze and store telemetry/observability data. -
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Artillery
Cloud-scale load testing. Fully serverless, test any stack
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. -
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Devtron
Tool integration platform for Kubernetes
Devtron deeply integrates with products across the lifecycle of microservices,i.e., CI, CD, security, cost, debugging, and observability via an intuitive web interface. Devtron is designed to be modular, and its functionality can be easily extended with the help of integrations. Devtron CI/CD with GitOps integration is used to automate the builds and deployments and enables the software development teams to focus on meeting the business requirements, code quality, and security. Devtron leverages Kubernetes auto-scaling and centralized caching to give you unlimited cost-efficient CI workers. Supports pre-CI and post-CI integrations for code quality monitoring. Provides deployment metrics like; deployment frequency, lead time, change failure rate, and mean-time recovery. Seamlessly integrates with Grafana for continuous application metrics like CPU and memory usage, status code, throughput, and latency on the dashboard. -
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EaseAgent
An agent component for the Java system
A lightweight & opening Java Agent for Cloud-Native and APM system. EaseAgent is the underlying component that provides non-intrusive extensions to applications of the Java ecosystem. EaseAgent can collect distributed application tracing, metrics, and logs, which could be used in the APM system and improve the observability of a distributed system. for the tracing, EaseAgent follows the Google Dapper paper. EaseAgent also can work with Cloud-Native architecture. For example, it can help Service Mesh (especially for EaseMesh ) to do some control panel work. EaseAgent supports plugin mechanism development, which is easy to extend or add new functionality. -
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Elastic APM Node.js Agent
Elastic APM Node.js Agent
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. -
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Eye
Process monitoring tool. Inspired from Bluepill and God
Process monitoring tool. Inspired from Bluepill and God. Requires Ruby(MRI) >= 1.9.3-p194. Uses Celluloid and Celluloid::IO. Eye is an image processing and analysis library for quickly analyzing image patterns and features, often used in computer vision tasks. -
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Fluid
Fluid, elastic data abstraction and acceleration for BigData/AI apps
Fluid, elastic data abstraction and acceleration for BigData/AI applications in the cloud. Provide DataSet abstraction for underlying heterogeneous data sources with multidimensional management in a cloud environment. Enable dataset warmup and acceleration for data-intensive applications by using a distributed cache in Kubernetes with observability, portability, and scalability. Taking characteristics of application and data into consideration for cloud application/dataset scheduling to improve the performance. -
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Go gRPC Middleware
Golang gRPC Middlewares: interceptor chaining, auth, logging, retries
gRPC Go has support for "interceptors", i.e. middleware that is executed either on the gRPC Server before the request is passed onto the user's application logic, or on the gRPC client either around the user call. It is a perfect way to implement common patterns: auth, logging, tracing, metrics, validation, retries, rate limiting, and more, which can be great generic building blocks that make it easy to build multiple microservices. Especially for observability signals (logging, tracing, metrics) interceptors offer semi-auto-instrumentation that improves the consistency of your observability and allows great correlation techniques (e.g. exemplars and trace ID in logs). Demo-ed in examples. This repository offers ready-to-use middleware that implements gRPC interceptors with examples. In some cases, dedicated projects offer great interceptors, so this repository skips those, and we link them in the interceptors list. -
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Grafana Pyroscope
Continuous Profiling Platform. Debug performance issues
Find and debug your most painful performance issues across code, infrastructure and CI/CD pipelines. Let you tag your data on the dimensions important for your organization. Allows you to store large volumes of high cardinality profiling data cheaply and efficiently. FlameQL enables custom queries to select and aggregate profiles quickly and efficiently for easy analysis. Analyze application performance profiles using our suite of profiling tools. Understand usage of CPU and memory resources at any point in time and identify performance issue before your customer do. Collect, store, and analyze profiles from various external profiling tools in one central location. Link to your Open Telemetry tracing data and get request-specific or span-specific profiles to enhance other observability data like traces and logs. -
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Helicone
Open source LLM-Observability Platform for Developers
Open source LLM-Observability Platform for Developers. One-line integration for monitoring, metrics, evals, agent tracing, prompt management, playground, etc. Supports OpenAI SDK, Vercel AI SDK, Anthropic SDK, LiteLLM, LLamaIndex, LangChain, and more. -
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Hubble
Network, Service & Security Observability for Kubernetes using eBPF
Hubble is a fully distributed networking and security observability platform for cloud native workloads. It is built on top of Cilium and eBPF to enable deep visibility into the communication and behavior of services as well as the networking infrastructure in a completely transparent manner. The Linux kernel technology eBPF is enabling visibility into systems and applications at a granularity and efficiency that was not possible before. It does so in a completely transparent way, without requiring the application to change or for the application to hide information. By building on top of Cilium, Hubble can leverage eBPF for visibility. By leveraging eBPF, all visibility is programmable and allows for a dynamic approach that minimizes overhead while providing deep and detailed insight where required. Hubble has been created and specifically designed to make best use of these new eBPF powers. -
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Jaeger
Monitor and troubleshoot transactions in complex distributed systems
As on-the-ground microservice practitioners are quickly realizing, the majority of operational problems that arise when moving to a distributed architecture are ultimately grounded in two areas: networking and observability. It is simply an orders of magnitude larger problem to network and debug a set of intertwined distributed services versus a single monolithic application. Jaeger, inspired by Dapper and OpenZipkin, is a distributed tracing system released as open source by Uber Technologies. It is used for monitoring and troubleshooting microservices-based distributed systems. OpenTracing compatible data model and instrumentation libraries include Go, Java, Node, Python, C++ and C#. Jaeger uses consistent upfront sampling with individual per service/endpoint probabilities and it has multiple storage backends: Cassandra, Elasticsearch, memory. -
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Jaeger UI
Web UI for Jaeger
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.
