Open Source Linux Observability Tools - Page 3

Observability Tools for Linux

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  • 1
    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.
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  • 2
    OpenTelemetry Collector

    OpenTelemetry Collector

    OpenTelemetry Collector

    The OpenTelemetry Collector offers a vendor-agnostic implementation on how to receive, process, and export telemetry data. In addition, it removes the need to run, operate, and maintain multiple agents/collectors in order to support open-source telemetry data formats (e.g. Jaeger, Prometheus, etc.) to multiple open-source or commercial back-ends.
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  • 3
    Pipeline

    Pipeline

    Banzai Cloud Pipeline is a solution-oriented application platform

    Banzai Cloud Pipeline is a solution-oriented application platform which allows enterprises to develop, deploy and securely scale container-based applications in multi- and hybrid-cloud environments. Banzai Pipeline, or simply Pipeline is a tabletop reef break located in Hawaii, Oahu's North Shore. The most famous and infamous reef in the universe is the benchmark by which all other waves are measured. Banzai Cloud Pipeline is a solution-oriented application platform which allows enterprises to develop, deploy and securely scale container-based applications in multi- and hybrid-cloud environments. Provisioning: Provision highly available Kubernetes clusters on cloud providers, on-premise or hybrid configurations. Multi and Hybrid clouds: Avoid lock in and move between providers and build hybrid clouds in four different ways.
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  • 4
    Pixie

    Pixie

    Instant Kubernetes-Native Application Observability

    Pixie is an open-source observability tool for Kubernetes applications. Use Pixie to view the high-level state of your cluster (service maps, cluster resources, application traffic) and also drill down into more detailed views (pod state, flame graphs, individual full-body application requests). Pixie uses eBPF to automatically collect telemetry data such as full-body requests, resource and network metrics, application profiles, and more. Pixie collects, stores and queries all telemetry data locally in the cluster. Pixie uses less than 5% of cluster CPU and in most cases less than 2%. PxL, Pixie’s flexible Pythonic query language, can be used across Pixie’s UI, CLI, and client APIs.
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  • 5
    Robusta

    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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  • 6
    SpiceDB

    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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  • 7
    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.
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  • 8
    Tracee

    Tracee

    Linux Runtime Security and Forensics using eBPF

    Tracee is a runtime security and observability tool that helps you understand how your system and applications behave. It is using eBPF technology to tap into your system and expose that information as events that you can consume. Events range from factual system activity events to sophisticated security events that detect suspicious behavioral patterns.
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  • 9
    coroot

    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.
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  • 10
    kubeinvaders

    kubeinvaders

    Gamified Chaos Engineering Tool for Kubernetes

    This project is part of the landscape of Cloud Native Computing Foundation in the Observability and Analysis - Chaos Engineering section. Backed by the teams at platform engineering.it and devopstribe.it, which provides enterprise-grade features and certified resilience services for your Kubernetes infrastructure.
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  • 11
    kubernetes-event-exporter

    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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  • 12
    memphis

    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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  • 13
    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.
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  • 14
    tapir

    tapir

    Declarative, type-safe web endpoints library

    Declarative, type-safe web endpoints library. With tapir, you can describe HTTP API endpoints as immutable Scala values. Each endpoint can contain a number of input and output parameters. Compile-time guarantees, develop-time completions, read-time information. Separate the shape of the endpoint (the "what"), from the server logic (the "how"). Generate documentation from endpoint descriptions. Leverage the metadata to report rich metrics and tracing information. Re-use common endpoint definitions, as well as individual inputs/outputs. Library, not a framework, integrates with your stack. Is your company already using tapir? We're continually expanding the "adopters" section in the documentation; the more the merrier! It would be great to feature your company's logo, but in order to do that, we'll need to write permission to avoid any legal misunderstandings.
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  • 15
    twemproxy

    twemproxy

    A fast, light-weight proxy for memcached and redis

    twemproxy (pronounced "two-em-proxy"), aka nutcracker is a fast and lightweight proxy for memcached and redis protocol. It was built primarily to reduce the number of connections to the caching servers on the backend. This, together with protocol pipelining and sharding enables you to horizontally scale your distributed caching architecture. Fast and lightweight. Maintains persistent server connections. Keeps connection count on the backend caching servers low. Enables pipelining of requests and responses. Supports proxying to multiple servers. Supports multiple server pools simultaneously. Shard data automatically across multiple servers. Implements the complete memcached ascii and redis protocol. Easy configuration of server pools through a YAML file. Supports multiple hashing modes including consistent hashing and distribution. Can be configured to disable nodes on failures.
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