Open Source Mac Observability Tools
Sort By:
Observability Tools for Mac
View 31 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.
-
Our Free Plans just got better! | Auth0You asked, we delivered! Auth0 is excited to expand our Free and Paid plans to include more options so you can focus on building, deploying, and scaling applications without having to worry about your security. Auth0 now, thank yourself later.
-
All-in-one security tool helps you prevent ransomware and breaches.Blumira’s detection and response platform enables faster resolution of threats to help you stop ransomware attacks and prevent data breaches. We surface real threats, providing meaningful findings so you know what to prioritize. With our 3-step rapid response, you can automatically block known threats, use our playbooks for easy remediation, or contact our security team for additional guidance. Our responsive security team helps with onboarding, triage and ongoing consultations to continuously help your organization improve your security coverage.
-
1
Grafana
Leading open-source visualization and observability platform
Grafana OSS is a leading open-source visualization and observability platform that lets you query, visualize, alert on, and explore your data—regardless of where it’s stored. With support for 100+ data source plugins (such as Prometheus, Loki, Elasticsearch, InfluxDB, SQL/NoSQL databases, OTel, and more), you can unify metrics, logs, traces, and other observability signals in one place. Grafana OSS empowers you to build dynamic, reusable dashboards with rich visualizations, template variables, interactive filtering, and cross-panel linking. Its Explore mode enables ad-hoc queries and side-by-side comparisons of time ranges, queries, and data sources. Grafana also includes built-in alerting, allowing you to define threshold-based rules and send notifications to external systems (e.g. Slack, PagerDuty, OpsGenie). Backed by a strong community (https://grafana.com/community/) and open governance, Grafana OSS is free to use, modify, and deploy under the AGPL-3.0 license. -
2
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. -
3
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. -
4
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. -
DAT Freight and Analytics - DATDAT Freight & Analytics operates DAT One, North America’s largest truckload freight marketplace; DAT iQ, the industry’s leading freight data analytics service; and Trucker Tools, the leader in load visibility. Shippers, transportation brokers, carriers, news organizations, and industry analysts rely on DAT for market trends and data insights, informed by nearly 700,000 daily load posts and a database exceeding $1 trillion in freight market transactions. Founded in 1978, DAT is a business unit of Roper Technologies (Nasdaq: ROP), a constituent of the Nasdaq 100, S&P 500, and Fortune 1000. Headquartered in Beaverton, Ore., DAT continues to set the standard for innovation in the trucking and logistics industry.
-
5
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. -
6
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. -
7
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. -
8
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. -
9
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. -
Create and run cloud-based virtual machines.Computing infrastructure in predefined or custom machine sizes to accelerate your cloud transformation. General purpose (E2, N1, N2, N2D) machines provide a good balance of price and performance. Compute optimized (C2) machines offer high-end vCPU performance for compute-intensive workloads. Memory optimized (M2) machines offer the highest memory and are great for in-memory databases. Accelerator optimized (A2) machines are based on the A100 GPU, for very demanding applications.
-
10
Lunary
The production toolkit for LLMs. Observability, prompt management
Lunary helps developers of LLM Chatbots develop and improve them. -
11
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. -
12
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. -
13
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. -
14
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. -
15
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. -
16
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. -
17
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.). -
18
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. -
19
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. -
20
Kuma
The multi-zone service mesh for containers, Kubernetes and VMs
Kuma is a modern Envoy-based service mesh that can run on every cloud, in a single or multi-zone capacity, across both Kubernetes and VMs. Thanks to its broad universal workload support, combined with native support for Envoy as its data plane proxy technology (but with no Envoy expertise required), Kuma provides modern L4-L7 service connectivity, discovery, security, observability, routing, and more across any service on any platform, databases included. Easy to use, with built-in service mesh policies for security, traffic control, discovery, observability, and more, Kuma ships with advanced multi-zone and multi-mesh support that automatically enables cross-zone communication across different clusters and clouds, and automatically propagates service mesh policies across the infrastructure. Kuma is currently being adopted by enterprise organizations around the world to support distributed service meshes across the application teams, on both Kubernetes and VMs. -
21
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. -
22
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. -
23
Elementary
Open-source data observability for analytics engineers
Elementary is an open-source data observability solution for data & analytics engineers. Monitor your dbt project and data in minutes, and be the first to know of data issues. Gain immediate visibility, detect data issues, send actionable alerts, and understand the impact and root cause. Generate a data observability report, host it or share with your team. Monitoring of data quality metrics, freshness, volume and schema changes, including anomaly detection. Elementary data monitors are configured and executed like native tests in dbt your project. Uploading and modeling of dbt artifacts, run and test results to tables as part of your runs. Get informative notifications on data issues, schema changes, models and tests failures. Inspect upstream and downstream dependencies to understand impact and root cause of data issues. -
24
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. -
25
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.
