Open Source Linux Observability Tools - Page 2
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Observability Tools for Linux
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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. -
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Perses
The CNCF sandbox for observability visualisation
Perses is an open-source project for creating and managing time-series dashboards, focused on flexibility and user customization. -
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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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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. -
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memphis
Next-Generation Event Processing Platform
Memphis enables building modern queue-based applications that require large volumes of streamed and enriched data, modern protocols, zero ops, up to x9 faster development, up to x46 fewer costs, and significantly lower dev time for data-oriented developers and data engineers. Queues and brokers are a mission-critical component in the modern application architecture and should be highly available and stable as possible. Provide great performance while maintaining efficient resource consumption. Increase observability, integrations with 3rd-party monitoring tools, real-time notifications, stream lineage, and therefore troubleshooting time reduction. Enable rapid development and ultra-short time-to-production. -
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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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Cilium
eBPF-based networking, security, and observability
Cilium is open-source software for providing, securing and observing network connectivity between container workloads, cloud-native, and fueled by the revolutionary Kernel technology eBPF. Kubernetes doesn't come with an implementation of Load Balancing. This is usually left as an exercise for your cloud provider or in private cloud environments an exercise for your networking team. Cilium can attract this traffic with BGP and accelerate leveraging XDP and eBPF. Together these technologies provide a very robust and secure implementation of Load Balancing. Cilium and eBPF operate at the kernel layer. With this level of context we can make intelligent decisions about how to connect different workloads whether on the same node or between clusters. With eBPF and XDP Cilium enables significant improvements in latency and performance and eliminates the need for kube-proxy entirely. -
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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. -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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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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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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LangCheck
Simple, Pythonic building blocks to evaluate LLM applications
Simple, Pythonic building blocks to evaluate LLM applications. -
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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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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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OpenLLMetry
Open-source observability for your LLM application
The repo contains standard OpenTelemetry instrumentations for LLM providers and Vector DBs, as well as a Traceloop SDK that makes it easy to get started with OpenLLMetry, while still outputting standard OpenTelemetry data that can be connected to your observability stack. If you already have OpenTelemetry instrumented, you can just add any of our instrumentations directly. -
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kubernetes-event-exporter
Export Kubernetes events to multiple destinations with routing
This tool allows exporting the often missed Kubernetes events to various outputs so that they can be used for observability or alerting purposes. You won't believe what you are missing. Configuration is done via a YAML file, when run in Kubernetes, ConfigMap. The tool watches all the events and the user has to option to filter out some events, according to their properties. Critical events can be routed to alerting tools such as Opsgenie, or all events can be dumped to an Elasticsearch instance. You can use namespaces, and labels on the related object to route some Pod-related events to owners via Slack. The final routing is a tree which allows flexibility. -
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perf-tools
Performance analysis tools based on Linux perf_events and ftrace
A miscellaneous collection of in-development and unsupported performance analysis tools for Linux ftrace and perf_events (aka the "perf" command). Both ftrace and perf are core Linux tracing tools, included in the kernel source. Your system probably has ftrace already, and perf is often just a package add. These tools are designed to be easy to install (fewest dependencies), provide advanced performance observability, and be simple to use: do one thing and do it well. This collection was created by Brendan Gregg (author of the DTraceToolkit). Many of these tools employ workarounds so that functionality is possible on existing Linux kernels. Because of this, many tools have caveats (see man pages), and their implementation should be considered a placeholder until future kernel features, or new tracing subsystems, are added. -
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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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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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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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CDviz
View software deployment's events & states
cdviz is a developer-focused visualization and analysis tool designed to help engineers understand, monitor, and optimize codebases by providing insights into structure, performance, and execution patterns. It likely focuses on transforming complex code relationships into visual representations that improve comprehension and debugging efficiency. The system may include static analysis capabilities, enabling it to detect inefficiencies, dependencies, or architectural issues within a project. Its architecture suggests an emphasis on developer experience, providing clear and actionable insights rather than raw data. It is particularly useful for large or complex systems where understanding code interactions is critical. The tool may also integrate with development workflows, allowing continuous analysis and feedback. Overall, cdviz serves as a bridge between code complexity and human understanding through visualization. -
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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. -
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Micrometer
App observability facade for the most popular observability tools
Micrometer provides a simple facade over the instrumentation clients for the most popular observability systems, allowing you to instrument your JVM-based application code without vendor lock-in. Think SLF4J, but for observability. Micrometer provides vendor-neutral interfaces for timers, gauges, counters, distribution summaries, and long task timers with a dimensional data model that, when paired with a dimensional monitoring system, allows for efficient access to a particular named metric with the ability to drill down across its dimensions. Out-of-the-box instrumentation of caches, the class loader, garbage collection, processor utilization, thread pools, and more tailored to actionable insight. Micrometer is the instrumentation library powering the delivery of application observability from Spring Boot applications. -
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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.