Open-source New Relic alternatives

Netdata is a real-time infrastructure monitoring platform. You install an agent on servers, containers or Kubernetes nodes and it starts collecting metrics every second, showing them on dashboards without lengthy setup. Its origin story is a frustration with monitoring tools that offered few metrics at low resolution and cost too much to run.

The project highlights zero-configuration deployment, machine-learning-based anomaly detection and automated analysis, and an efficient agent that uses few resources. Data stays distributed on the monitored machines instead of being shipped to one central store. Integrations cover databases such as MySQL, PostgreSQL and MongoDB, plus Docker and Kubernetes, and the topics list mentions export paths to Prometheus, Grafana and InfluxDB. Netdata also advertises AI-assisted troubleshooting and an MCP interface.

The agent is GPL-3.0 licensed and written largely in Go, and Netdata Cloud offers a hosted layer for viewing many nodes together. It suits operations teams and lean engineering groups that want deep visibility quickly rather than building a metrics stack from several separate tools.

Grafana is a visualization and observability platform that lets you query, chart and alert on data wherever it is stored. It does not hold your data itself; it connects to sources such as Prometheus, Loki, Elasticsearch, InfluxDB, MySQL and PostgreSQL and brings their results together in shared dashboards.

Dashboards can be made reusable with template variables that appear as dropdowns, and a single graph may mix queries against different data sources. Explore views support ad-hoc queries, side-by-side comparison of time ranges and a jump from metrics to logs while keeping label filters. Alert rules are defined visually, and notifications go to systems like Slack, PagerDuty, VictorOps and OpsGenie. Panel plugins add further visualization types.

Grafana is AGPL-3.0 licensed, written in Go and TypeScript, and can be installed on your own servers; Grafana Labs also runs a hosted offering. It is common in DevOps and SRE teams as the dashboard layer on top of Prometheus-style monitoring, and a public demo site lets you try it first.

Prometheus is a systems and service monitoring tool and time series database, and a project of the Cloud Native Computing Foundation. It collects metrics from configured targets at set intervals, evaluates rule expressions, shows the results and can fire alerts when conditions are met.

Its data model is multi-dimensional: a time series is identified by a metric name plus key and value labels, and PromQL is the query language built to exploit that structure. Collection uses an HTTP pull model, with a gateway available for pushing metrics from short-lived batch jobs, and targets are found through service discovery or static configuration. Single server nodes are autonomous with no dependence on distributed storage, and hierarchical and horizontal federation is supported.

Prometheus is written in Go under the Apache-2.0 license and ships as precompiled binaries and Docker images on Quay.io and Docker Hub, or can be built from source. It has no hosted service of its own and is typically run next to exporters and a dashboarding tool such as Grafana, which suits cloud-native and Kubernetes environments.

SigNoz is an observability platform, open source and built on OpenTelemetry. It aims to replace a fragmented monitoring stack with a single place for logs, metrics, traces, alerts, exceptions and dashboards, and it presents itself as useful for both engineering teams and their AI agents.

The APM view follows how each service performs, covering latency, error rate, throughput, Apdex, the busiest endpoints, and calls to databases and external services. Log management supports ingesting, searching and correlating logs with traces and metrics through a visual query builder. Dashboards can be built with a query builder, PromQL or ClickHouse SQL, infrastructure monitoring covers Kubernetes clusters, pods, nodes and host resources, and LLM and AI observability traces prompts, tool calls, tokens, latency and cost.

You can choose how to run it. SigNoz Cloud is fully managed, with a 30-day free trial and usage-based pricing that starts at $49. Enterprise options cover cloud, bring-your-own-cloud and self-hosted deployments with extra support and controls. The free Community edition runs in your own infrastructure via Docker, Kubernetes or Linux. The repository license is listed as 'Other' on GitHub.

Jaeger is a tracing system for distributed applications, created at Uber Technologies and donated to the Cloud Native Computing Foundation, where it graduated in October 2019. It records how requests flow through services so teams can monitor and troubleshoot distributed systems. It is written in Go and released under the Apache-2.0 license. The README announces Jaeger v2.

A Docker-based quick start gets a local instance running in seconds, while the documentation covers production deployments and operations. Because Jaeger reuses many components from the OpenTelemetry Collector, the project works to keep configuration compatible between releases and publishes deprecation guidelines for when options change. It is an open project with open governance, welcoming contributions that do not always require code. The repository topics include distributed tracing, observability and OpenTelemetry, and community support runs on Slack.

OpenObserve, often shortened to O2, is open-source observability software spanning logs, metrics, traces and analytics, real user monitoring on web, Android and iOS, session replay, pipelines, SLOs and AI and LLM observability. It is pitched as a lower-cost option next to Datadog, Splunk and Elasticsearch for teams that want complete observability without the complexity or price.

Its architecture uses Parquet columnar storage and an S3-native design, which the project says can cut storage costs by up to 140 times compared with Elasticsearch, with petabyte-scale capacity. Topics reference OpenTelemetry, Prometheus, Jaeger and Kibana, showing the standards and tools it interoperates with. The README has sections on architecture, comparisons, production readiness, security and compliance, and an enterprise edition.

OpenObserve is AGPL-3.0 licensed, with a hosted cloud option and a self-hosted deployment, and documentation and a Slack community are provided. It suits engineering teams looking to consolidate logging, metrics and tracing in one tool while keeping storage costs under control.

Kibana is the user interface that sits on top of Elasticsearch. It lets people query, analyze, visualize and manage the data stored there, turning indexes into charts, metrics views and dashboards. It is part of the Elastic Stack and is commonly used for log analysis, observability and general analytics work.

Teams build visualizations and assemble them into shared dashboards, explore documents with search, and use the interface to manage parts of an Elasticsearch deployment. The project advises running Kibana and Elasticsearch at the same version, with major versions required to match, because mismatches can cause problems and support may ask for an upgrade first.

The code is written in TypeScript. The repository lists its license as 'Other' rather than a standard SPDX identifier, so the license files should be read for the exact terms. Kibana can be downloaded and run on your own infrastructure, and Elastic also offers a hosted version through its Cloud service.

Pinpoint is an APM tool, short for application performance management, built for large-scale distributed systems. Inspired by Google's Dapper, it traces transactions as they move across the components of a distributed application so teams can see how the system is structured and where problems or bottlenecks arise.

Its ServerMap visualizes application topology and how components connect, while real-time monitoring and code-level visibility into each transaction help diagnose slow or failing requests. Agents can be installed without changing application code, and the project says their overhead on resource usage is low. Agents are available for Java, PHP and Python applications.

Pinpoint is written in Java and licensed under Apache-2.0. You deploy and operate the Pinpoint components yourself, with a quick-start guide, an installation guide and a Kubernetes deployment option provided, and a live demo is available online for a first look.

HyperDX is an open-source observability platform for working out why production is broken. It brings logs, metrics, traces, errors and session replays into one place, and works as a search and visualization layer on top of ClickHouse and OpenTelemetry, which the authors compare to Kibana for ClickHouse. It is a core component of ClickStack.

It is schema agnostic and can sit on top of an existing ClickHouse schema. Searching uses full-text and property syntax such as level:err, with SQL as an option, events can be compared with event deltas, high-cardinality events can be charted on dashboards, and alerts can be set up in a few clicks. Live tail shows the newest logs and traces, JSON strings can be queried natively, OpenTelemetry works out of the box, and APM views cover HTTP requests down to database queries.

One deployment option is ClickStack, a bundle of ClickHouse, HyperDX, an OpenTelemetry Collector and MongoDB, and HyperDX can instead be pointed at your own ClickHouse instance. It can also be used with ClickHouse Cloud. The project is MIT licensed and written in TypeScript.

Highlight, at highlight.io, is an open-source monitoring platform for developers. Its aim is to give teams one cohesive tool covering the front end and back end, instead of separate products for errors, logs and user sessions.

The core features are session replay, error monitoring and logging, with tracing and metrics also in scope. Console logs from the front end can be analyzed, and errors are embedded alongside the session in which they happened, so you can see what the user was doing beforehand. Session comments let teams discuss user frustration or bugs, there are integrations with other tools, and client SDKs install with a few lines of code.

You can sign up for the free-to-start hosted version at app.highlight.io, or deploy a hobby instance on Linux with Docker, sized at roughly 8 GB of memory, four CPUs and 64 GB of storage. The code is written in TypeScript and Go, and the repository lists the license as Other, so check the licence file for terms.