Observability Tools for Linux

View 44 business solutions

Browse free open source Observability tools and projects for Linux 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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  • 1
    qryn

    qryn

    All-in-one Polyglot Observability stack with ClickHouse storage

    All the greatest observability formats and integrations you love, at once - LGTM Drop-in compatible. Let's get Polyglot. qryn independently implements popular observability standards, protocols and query languages. Make sure you have sufficient memory and disk resources allocated for your node service and clickhouse server when dealing with large amounts of data and fingerprints. We suggest 8GB RAM or higher for most setups with 100k-1M fingerprints. Observe your daily and weekly data consumption to forecast your disk usage requirements. Compression codecs and other optimizations can be performed at the ClickHouse level.
    Downloads: 42 This Week
    Last Update:
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  • 2
    Alibaba iLogtail

    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.
    Downloads: 27 This Week
    Last Update:
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  • 3
    DeepFlow

    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.
    Downloads: 23 This Week
    Last Update:
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  • 4
    Grafana

    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.
    Downloads: 20 This Week
    Last Update:
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  • 5
    Grafana Pyroscope

    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.
    Downloads: 20 This Week
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  • 6
    Vector

    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.
    Downloads: 18 This Week
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  • 7
    Jaeger UI

    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.
    Downloads: 16 This Week
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  • 8
    OneUptime

    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.
    Downloads: 16 This Week
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  • 9
    Jaeger

    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.
    Downloads: 15 This Week
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    MongoDB Atlas runs apps anywhere

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  • 10
    Elastic APM Node.js Agent

    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.
    Downloads: 13 This Week
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  • 11
    OpenObserve

    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.
    Downloads: 10 This Week
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  • 12
    Tetragon

    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.
    Downloads: 10 This Week
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  • 13
    Deckhouse

    Deckhouse

    Kubernetes platform from Flant

    Deckhouse is a Kubernetes platform that allows you to create homogeneous K8s clusters on any infrastructure. It manages clusters comprehensively and “automagically” and provides all necessary modules and add-ons for autoscaling, observability, security, and service mesh implementation. Deckhouse has vanilla Kubernetes under the hood and integrates a balanced set of Open Source tools that have become the industry standard. Out-of-the-box secure configuration of the Kubernetes cluster, least component privileges, pre-configured role model, end-to-end object identity in the audit system, and integration with external directory services. Built-in implementation of Pod Security Standards and a ready-to-use, extensible set of recommended policies. Deckhouse automates many routine deployment, scaling, and infrastructure management operations out of the box. It manages system software on the nodes (kernel, CRI, kubelet), basic Kubernetes components (control plane, etc, certificates, etc.).
    Downloads: 9 This Week
    Last Update:
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  • 14
    ThreatMapper

    ThreatMapper

    Open source cloud native security observability platform

    Thousands of companies trust Deepfence to secure their most critical cloud workloads and applications with a unified platform. Experience rapid threat detection and remediation, while significantly reducing non-critical security alerts by 90%. Deepfence ThreatMapper hunts for threats in your production platforms, and ranks these threats based on their risk of exploit. It uncovers vulnerable software components, exposed secrets, and deviations from good security practices. ThreatMapper uses a combination of agent-based inspection and agent-less monitoring to provide the widest possible coverage to detect threats. ThreatMapper carries on the good 'shift left' security practices that you already employ in your development pipelines. It continues to monitor running applications against emerging software vulnerabilities and monitors the host and cloud configuration against industry-expert benchmarks.
    Downloads: 9 This Week
    Last Update:
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  • 15
    Conduit

    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.
    Downloads: 8 This Week
    Last Update:
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  • 16
    Eye

    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.
    Downloads: 8 This Week
    Last Update:
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  • 17
    Hubble

    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.
    Downloads: 8 This Week
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  • 18
    Kamon Telemetry

    Kamon Telemetry

    Distributed Tracing, Metrics and Context Propagation for applications

    Kamon Telemetry is a set of libraries for instrumenting applications running on the JVM. With Kamon Telemetry you can collect metrics, propagate context across threads and services, and get distributed traces automatically. The best way to get started is by following our installation guides and taking it from there. Have fun with Kamon. Monitor your backend applications, fix performance issues, and get alerted when problems happen. All without being a monitoring expert. Everybody starts monitoring with logs because they are there by default. Just connect to your server and start tailing. But logs have a hard time showing you the overall response times for your application, or whether certain calls to the database are happening in sequence or parallel (among a million other things).
    Downloads: 8 This Week
    Last Update:
    See Project
  • 19
    KubeVela

    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.
    Downloads: 8 This Week
    Last Update:
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  • 20
    Lunary

    Lunary

    The production toolkit for LLMs. Observability, prompt management

    Lunary helps developers of LLM Chatbots develop and improve them.
    Downloads: 8 This Week
    Last Update:
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  • 21
    OpenTelemetry

    OpenTelemetry

    OpenTelemetry Go API and SDK

    OpenTelemetry-Go is the Go implementation of OpenTelemetry. It provides a set of APIs to directly measure the performance and behavior of your software and send this data to observability platforms. High-quality, ubiquitous, and portable telemetry to enable effective observability. OpenTelemetry is a collection of APIs, SDKs, and tools. Use it to instrument, generate, collect, and export telemetry data (metrics, logs, and traces) to help you analyze your software’s performance and behavior.
    Downloads: 8 This Week
    Last Update:
    See Project
  • 22
    Fluid

    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.
    Downloads: 7 This Week
    Last Update:
    See Project
  • 23
    KubeSphere

    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.
    Downloads: 7 This Week
    Last Update:
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  • 24
    LangKit

    LangKit

    An open-source toolkit for monitoring Language Learning Models (LLMs)

    LangKit is an open-source text metrics toolkit for monitoring language models. It offers an array of methods for extracting relevant signals from the input and/or output text, which are compatible with the open-source data logging library whylogs. Productionizing language models, including LLMs, comes with a range of risks due to the infinite amount of input combinations, which can elicit an infinite amount of outputs. The unstructured nature of text poses a challenge in the ML observability space - a challenge worth solving, since the lack of visibility on the model's behavior can have serious consequences.
    Downloads: 7 This Week
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    See Project
  • 25
    OpenClaw Opik Observability Plugin

    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.
    Downloads: 7 This Week
    Last Update:
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