Open Source Windows Observability Tools
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Observability Tools for Windows
View 43 business solutionsBrowse free open source Observability tools and projects for Windows below. Use the toggles on the left to filter open source Observability tools by OS, license, language, programming language, and project status.
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Full-stack observability with actually useful AI | Grafana CloudBuilt on open standards like Prometheus and OpenTelemetry, Grafana Cloud includes Kubernetes Monitoring, Application Observability, Incident Response, plus the AI-powered Grafana Assistant. Get started with our generous free tier today.
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Go From AI Idea to AI App FastAccess Gemini 3 and 200+ models. Build chatbots, agents, or custom models with built-in monitoring and scaling.
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Grafana
Leading open-source visualization and observability platform
Grafana OSS is the leading open-source platform for visualization and observability. It enables teams to query, visualize, alert on, and explore telemetry data from multiple sources in a single interface. With support for 100+ data source plugins—including Prometheus, Loki, Elasticsearch, InfluxDB, SQL/NoSQL databases, and OpenTelemetry—Grafana helps teams correlate metrics, logs, and traces across applications and infrastructure. Users can build interactive dashboards with rich visualizations, template variables, and reusable panels to monitor systems and troubleshoot issues in real time. Grafana includes capabilities such as ad hoc data exploration, alerting, annotations, and flexible query support. Its extensible plugin ecosystem integrates with cloud platforms, databases, and developer tools—allowing teams to build observability workflows without vendor lock-in. The easiest way to get started with Grafana is with Grafana Cloud, our fully managed, full-stack observability platform. -
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OneUptime
OneUptime is the complete open-source observability platform
OneUptime is a comprehensive solution for monitoring and managing your online services. Whether you need to check the availability of your website, dashboard, API, or any other online resource, OneUptime can alert your team when downtime happens and keep your customers informed with a status page. OneUptime also helps you handle incidents, set up on-call rotations, run tests, secure your services, analyze logs, track performance, and debug errors. -
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QuestDB
An open source SQL database designed to process time series data
QuestDB is a high-performance, open-source SQL database for applications in financial services, IoT, machine learning, DevOps and observability. It includes endpoints for PostgreSQL wire protocol, high-throughput schema-agnostic ingestion using InfluxDB Line Protocol, and a REST API for queries, bulk imports, and exports. QuestDB implements ANSI SQL with native extensions for time-oriented language features. These extensions make it simple to correlate data from multiple sources using relational and time series joins. QuestDB achieves high performance from a column-oriented storage model, massively-parallelized vector execution, SIMD instructions, and various low-latency techniques. The entire codebase was built from the ground up in Java and C++, with no dependencies, and is 100% free from garbage collection. We provide a live demo provisioned with the latest QuestDB release and sample datasets. -
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Coroot
Open-source observability for microservices
Collecting metrics, logs, and traces alone doesn't make your applications observable. Coroot turns that data into actionable insights for you. Enable system observability in minutes, no code changes required. Each release is automatically compared with the previous one, so you'll never miss even the slightest performance degradation. With integrated Cost Monitoring, developers can track how each change affects their cloud bill. Understand your cloud costs down to any given application. Doesn't require access to your cloud account or any other configurations. Analyze any unexpected spike in CPU or memory usage down to the precise line of code. Don't make assumptions, know exactly what the resources were spent on. Easily investigate any anomaly by comparing it to the system's baseline behavior. -
$300 in Free Credit Towards Top Cloud ServicesStart your project in minutes. After credits run out, 20+ products include free monthly usage. Only pay when you're ready to scale.
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Arize Phoenix
Uncover insights, surface problems, monitor, and fine tune your LLM
Phoenix provides ML insights at lightning speed with zero-config observability for model drift, performance, and data quality. Phoenix is an Open Source ML Observability library designed for the Notebook. The toolset is designed to ingest model inference data for LLMs, CV, NLP and tabular datasets. It allows Data Scientists to quickly visualize their model data, monitor performance, track down issues & insights, and easily export to improve. Deep Learning Models (CV, LLM, and Generative) are an amazing technology that will power many of future ML use cases. A large set of these technologies are being deployed into businesses (the real world) in what we consider a production setting. -
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OpenClaw Opik Observability Plugin
Official plugin for OpenClaw that exports agent traces to Opik
OpenClaw Opik Observability Plugin is an open-source plugin designed to add observability and monitoring capabilities to OpenClaw autonomous AI agents by exporting operational traces to the Opik observability platform. The project integrates directly with OpenClaw’s plugin architecture so that developers can capture detailed runtime information about how their agents behave while executing tasks. Each time an AI agent performs an action—such as calling a large language model, invoking a tool, accessing memory, or delegating to a sub-agent—the plugin records the full interaction and sends it to Opik for analysis and visualization. This allows developers to inspect inputs, outputs, token usage, latency, and execution flow across complex multi-step agent workflows. The goal of the project is to provide transparency into the internal reasoning and operational pipeline of agent systems so developers can diagnose failures, control costs, and improve reliability. -
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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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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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LINKERD
Ultralight, security-first service mesh for Kubernetes
Enterprise power without enterprise complexity. Linkerd adds security, observability, and reliability to any Kubernetes cluster. 100% open source, CNCF graduated, and written in Rust. Instantly add latency-aware load balancing, request retries, timeouts, and blue-green deploys to keep your applications resilient. Incredibly small and blazing fast Linkerd2-proxy micro-proxy written in Rust for security and performance. Self-contained control plane, incrementally deployable data plane, and lots and lots of diagnostics and debugging tools. Transparently add mutual TLS to any on-cluster TCP communication with no configuration. Designed by engineers, for engineers. -
AI-powered service management for IT and enterprise teamsGive your IT, operations, and business teams the ability to deliver exceptional services—without the complexity. Maximize operational efficiency with refreshingly simple, AI-powered Freshservice.
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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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SigNoz
SigNoz is an open-source APM. It helps developers monitor their apps
Monitor your applications and troubleshoot problems in your deployed applications, an open-source alternative to DataDog, New Relic, etc. SigNoz helps developers monitor applications and troubleshoot problems in their deployed applications. SigNoz uses distributed tracing to gain visibility into your software stack. Visualise Metrics, Traces and Logs in a single pane of glass. You can see metrics like p99 latency, error rates for your services, external API calls and individual end points. You can find the root cause of the problem by going to the exact traces which are causing the problem and see detailed flamegraphs of individual request traces. Run aggregates on trace data to get business relevant metrics. Filter and query logs, build dashboards and alerts based on attributes in logs. -
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Alibaba iLogtail
Fast and Lightweight Observability Data Collector
iLogtail was born for observable scenarios and has many production-level features such as lightweight, high performance, and automated configuration, which are widely used internally by Alibaba Group and tens of thousands of external Alibaba Cloud customers. You can deploy it in physical machines, Kubernetes and other environments to collect telemetry data, such as logs, traces and metrics. Supports a variety of Logs, Traces, and Metrics data collection, and is friendly to container and Kubernetes environment support. The resource cost of data collection is quite low, 5-20 times better than similar telemetry data collection Agent performance. High stability, used in the production of Alibaba and tens of thousands of Alibaba Cloud customers, and collecting dozens of petabytes of observable data every day with nearly tens of millions deployments. -
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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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Conduit
Conduit streams data between data stores. Kafka Connect replacement
Conduit is a data streaming tool written in Go. It aims to provide the best user experience for building and running real-time data pipelines. Conduit comes with batteries included, it provides a UI, common connectors, processors and observability data out of the box. Sync data between your production systems using an extensible, event-first experience with minimal dependencies that fit within your existing workflow. Eliminate the multi-step process you go through today. Just download the binary and start building. Conduit connectors give you the ability to pull and push data to any production datastore you need. If a datastore is missing, the simple SDK allows you to extend Conduit where you need it. Conduit pipelines listen for changes to a database, data warehouse, etc., and allows your data applications to act upon those changes in real-time. Run it in a way that works for you; use it as a standalone service or orchestrate it within your infrastructure. -
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Dagster
An orchestration platform for the development, production
Dagster is an orchestration platform for the development, production, and observation of data assets. Dagster as a productivity platform: With Dagster, you can focus on running tasks, or you can identify the key assets you need to create using a declarative approach. Embrace CI/CD best practices from the get-go: build reusable components, spot data quality issues, and flag bugs early. Dagster as a robust orchestration engine: Put your pipelines into production with a robust multi-tenant, multi-tool engine that scales technically and organizationally. Dagster as a unified control plane: The ‘single plane of glass’ data teams love to use. Rein in the chaos and maintain control over your data as the complexity scales. Centralize your metadata in one tool with built-in observability, diagnostics, cataloging, and lineage. Spot any issues and identify performance improvement opportunities. -
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DeepFlow
Application Observability using eBPF
DeepFlow provides a universal map with Zero Code by eBPF for production environments, including your services in any language, third-party services without code and all cloud-native infrastructure services. In addition to analyzing common protocols, Wasm plugins are supported for your private protocols. Full-stack golden signals of applications and infrastructures are calculated, pinpointing performance bottlenecks at ease. Zero Code distributed tracing powered by eBPF supports applications in any language and infrastructures including gateways, service meshes, databases, message queues, DNS, and NICs, leaving no blind spots. Full-stack network performance metrics and file I/O events are automatically collected for each Span. Distributed tracing enters a new era, Zero Instrumentation. DeepFlow collects profiling data at a cost of below 1% with Zero Code, plots OnCPU/OffCPU function call stack flame graphs, and locates Full Stack performance bottleneck in the application. -
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Envoy
Cloud-native high-performance edge/middle/service proxy
Envoy is an open source, high-performance edge/middle/service proxy designed for cloud-native applications. It was built by Lyft to solve the common problem of networking and observability when moving to a distributed architecture. Envoy is a proxy designed for single services and applications. Aside from that it is also a communication bus and “universal data plane” designed for large microservice “service mesh” architectures. It runs right along with every application, and abstracts the network by providing common features in a platform-agnostic manner. With Envoy, visualizing problem areas becomes a lot easier thanks to consistent observability. It also helps with overall performance tuning, and easily adding substrate features in one place. -
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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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Loggie
A lightweight, cloud-native data transfer agent and aggregator
Loggie is a lightweight, high-performance, cloud-native agent and aggregator based on Golang. Loggie includes LogConfig/ClusterLogConfig/Interceptor/Sink CRDs, allowing for the creation of data collection, transfer, processing, and sending pipelines through simple YAML file creation. Supports deployment as an independent intermediate machine, which can receive aggregated data sent by Loggie Agent and can also be used to consume and process various data sources. Configure Filebeat and Loggie to collect logs, and send them to a Kafka topic without using client compression, with the Kafka topic partition configured as 3. With sufficient resources for the Agent specification, modify the number of files collected, the concurrency of the sending client (configure Filebeat worker and Loggie parallelism), and observe their respective CPU, memory, and pod network card transmission rates. -
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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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Apache APISIX
The cloud-native API gateway
Provides rich traffic management features such as load balancing, dynamic upstream, canary release, circuit breaking, authentication, observability, and more. Based on the Nginx library and etcd. Cloud-native microservices API gateway, delivering the ultimate performance, security, open source and scalable platform for all your APIs and microservices. Apache APISIX is based on Nginx and etcd. Compared with traditional API gateways, APISIX has dynamic routing and plug-in hot loading, which is especially suitable for API management under micro-service system. You can use Apache APISIX as a traffic entrance to process all business data, including dynamic routing, dynamic upstream, dynamic certificates, A/B testing, canary release, blue-green deployment, limit rate, defense against malicious attacks, metrics, monitoring alarms, service observability, service governance, etc. -
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BFE
A modern layer 7 load balancer from baidu
BFE (Beyond Front End) is a modern layer 7 load balancer from baidu. BFE has a builtin plugin framework that makes it possible to develop new features rapidly by writing plugins. BFE is designed to provide every tenant a dedicated share of the instance. Each tenant’s configuration is isolated and remains invisible to other tenants. BFE supports HTTP, HTTPS, SPDY, HTTP2, gRPC, WebSocket, TLS, FastCGI, etc. Future support is planned for HTTP/3. BFE provides an advanced domain-specific language to describe routing rules which are easy to understand and maintain. BFE supports global load balancing and distributed load balancing for zone aware balancing, zone level failure resilience, overload protection etc. BFE provides a rich set of plugins for traffic management, security, observability, etc. BFE includes detailed built-in metrics for all subsystems. BFE writes various logs for trouble shooting, data analysis and visualization. BFE also supports distributed tracing. -
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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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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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KubeSphere
The container platform tailored for Kubernetes multi-cloud, datacenter
KubeSphere is a distributed operating system for cloud-native application management, using Kubernetes as its kernel. It provides a plug-and-play architecture, allowing third-party applications to be seamlessly integrated into its ecosystem. KubeSphere is also a multi-tenant container platform with full-stack automated IT operation and streamlined DevOps workflows. It provides developer-friendly wizard web UI, helping enterprises to build out a more robust and feature-rich platform, which includes most common functionalities needed for enterprise Kubernetes strategy, see Feature List for details. KubeSphere Lite provides you with free, stable, and out-of-the-box managed cluster service. After registration and login, you can easily create a K8s cluster with KubeSphere installed in only 5 seconds and experience feature-rich KubeSphere.
