Open Source Mac Observability Tools
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Observability Tools for Mac
View 33 business solutionsBrowse free open source Observability tools and projects for Mac 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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Easily build robust connections between Salesforce and any platformLike having Postman inside Salesforce! Declarative Webhooks allows users to quickly and easily configure bi-directional integrations between Salesforce and external systems using a point-and-click interface. No coding is required, making it a fast and efficient and as a native solution, Declarative Webhooks seamlessly integrates with Salesforce platform features such as Flow, Process Builder, and Apex. You can also leverage the AI Integration Agent feature to automatically build your integration templates by providing it with links to API documentation.
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Powerful Business Process AutomationWhen a message is received ThinkAutomation automatically executes one or more Automations. Automations are created using an easy to use drag-and-drop interface to run simple or complex tasks. Automations can perform many business process Actions, including: updating company databases, CRM systems and cloud services, sending outgoing emails, Teams & SMS messages, document processing, custom scripting, integration and much more. Over 100 built-in actions are included, plus ThinkAutomation is extensible with Custom Actions.
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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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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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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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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. -
Dynamic Work and Complex Project Management Platform | QuickbaseOur no-code platform lets you easily create, connect, and customize enterprise applications that fix visibility and workflow gaps without replacing a single system.
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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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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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fluentbit
Fast and Lightweight Logs and Metrics processor for Linux, BSD, OSX
Fluent Bit is a super-fast, lightweight, and highly scalable logging and metrics processor and forwarder. It is the preferred choice for cloud and containerized environments. A robust, lightweight, and portable architecture for high throughput with low CPU and memory usage from any data source to any destination. Proven across distributed cloud and container environments. Highly available with I/O handlers to store data for disaster recovery. Granular management of data parsing and routing. Filtering and enrichment to optimize security and minimize cost. The lightweight, asynchronous design optimizes resource usage: CPU, memory, disk I/O, network. No more OOM errors! Integration with all your technology, cloud-native services, containers, streaming processors, and data backends. Fully event-driven design leverages the operating system API for performance and reliability. All operations to collect and deliver data are asynchronous. -
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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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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. -
Award-winning proxy networks, AI-powered web scrapers, and business-ready datasets for download.Bright Data is a leading data collection platform, enabling businesses to collect crucial structured and unstructured data from millions of websites through our proprietary technology. Our proxy networks give you access to sophisticated target sites using precise geo-targeting. You can also use our tools to unblock tough target sites, accomplish SERP-specific data collection tasks, manage and optimize your proxy performance as well as automating all of your data collection needs.
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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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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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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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Opik
Debug, evaluate, and monitor your LLMapps, RAG systems, and agentic AI
Confidently evaluate, test, and monitor LLM applications. Opik is an open-source platform for evaluating, testing, and monitoring LLM applications. Built by Comet. Record, sort, search, and understand each step your LLM app takes to generate a response. Manually annotate, view, and compare LLM responses in a user-friendly table. Log traces during development and in production. Run experiments with different prompts and evaluate against a test set. Choose and run pre-configured evaluation metrics or define your own with our convenient SDK library. Consult built-in LLM judges for complex issues like hallucination detection, factuality, and moderation. -
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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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HyperDX
An open source observability platform unifying session replays & logs
HyperDX helps engineers figure out why production is broken faster by centralizing and correlating logs, metrics, traces, exceptions and session replays in one place. An open-source and developer-friendly alternative to Datadog and New Relic. The HyperDX stack ingests, stores, and searches/graphs your telemetry data. After standing up the Docker Compose stack, you'll want to instrument your app to send data over to HyperDX. -
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Kyma
Kyma is an opinionated set of Kubernetes-based modular building blocks
Kyma is an opinionated set of Kubernetes-based modular building blocks, including all necessary capabilities to develop and run enterprise-grade cloud-native applications. It is the open path to the SAP ecosystem supporting business scenarios end-to-end. Kyma is an actively maintained open-source project supported by SAP. The Kyma project is also a foundation of SAP BTP, Kyma runtime which is a part of SAP Business Technology Platform (BTP). You can use Kyma modules in your own Kubernetes cluster, or try the managed version from SAP BTP with a ready-to-use Kubernetes cluster powered by Gardener. Kyma is built upon leading cloud-native, open-source projects and open standards, such as Istio, NATS, Cloud Events, and Open Telemetry. We created an opinionated set of modules you can easily enable in your Kubernetes cluster to speed up cloud application development and operations. With Kyma, you save the time to pick the right tools and the effort to keep them secure and up to date. -
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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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Open Service Mesh
Cloud native service mesh to uniformly manage environments
Open Service Mesh (OSM) is a lightweight, extensible, cloud-native service mesh that allows users to uniformly manage, secure, and get out-of-the-box observability features for highly dynamic microservice environments. The OSM project builds on the ideas and implementations of many cloud-native ecosystem projects including Linkerd, Istio, Consul, Envoy, Kuma, Helm, and the SMI specification. OSM runs an Envoy based control plane on Kubernetes, can be configured with SMI APIs, and works by injecting an Envoy proxy as a sidecar container next to each instance of your application. The proxy contains and executes rules around access control policies, implements routing configuration, and captures metrics. The control plane continually configures proxies to ensure policies and routing rules are up to date and ensures proxies are healthy. -
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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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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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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. -
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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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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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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.
