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Guide

Best open-source observability tools in 2026

OpenTelemetry-native traces, logs, and metrics you can self-host, ranked, with pros, cons, licenses, and what each tool is best for.

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We build Maple, so it sits at #1. Factor that bias in; the rest of the list is played straight. Every tool here is open source or source-available: you can read the code and self-host all of them, and we note each one's license. We weighed how directly each one takes OpenTelemetry, whether it keeps traces, logs, and metrics in one place, and how much operational work a small team takes on to run it. Rank is a starting point. The “Best for” tag matters more: pick the one that matches how your team works.

Last updated: June 2026

At a glance
1

Maple

Best for: OpenTelemetry-native teams who want AI-agent workflows and per-GB pricing

Source-available (FSL-1.1 → Apache 2.0)

Maple is an OpenTelemetry-native observability platform covering traces, logs, metrics, and browser session replay in one app. It ships a hosted MCP server so AI agents can search traces, find errors, and propose fixes, and it prices on usage with no per-host or per-seat fees. Its source is available under FSL-1.1 (which converts to Apache 2.0), so you can read it, fork it, and self-host.

Strengths

  • +OpenTelemetry-native, with no proprietary agent
  • +Hosted MCP server for AI agents
  • +Session replay linked to the backend traces behind each session
  • +Usage-based pricing with published rates; self-hostable

Trade-offs

  • –Younger project with a smaller ecosystem than the incumbents
  • –Fewer turnkey integrations than the Grafana stack today
Visit Maple ↗
2

Grafana (LGTM stack)

Best for: Teams that want maximum flexibility and don't mind assembling components

AGPLv3

The Grafana stack pairs Grafana dashboards with Loki (logs), Tempo (traces), and Mimir (metrics). It is the most widely deployed open-source option and the most configurable, but you assemble and operate several systems yourself.

Strengths

  • +Large ecosystem, plugin catalog, and community
  • +The most widely used dashboarding tool
  • +Mix and match Loki / Tempo / Mimir as needed

Trade-offs

  • –You run and tune multiple separate systems
  • –Operational overhead grows with scale
  • –OpenTelemetry arrives through Alloy or the Collector and fans out to each component
Visit Grafana (LGTM stack) ↗ Maple vs Grafana
3

SigNoz

Best for: Teams wanting an all-in-one OpenTelemetry-native APM

MIT core, commercial ee/ directory

SigNoz is an OpenTelemetry-native, ClickHouse-backed APM that keeps traces, logs, and metrics in a single application, and the closest peer to Maple on this list. It is a strong default if you want one open-source app instead of a stack to assemble.

Strengths

  • +OpenTelemetry-native from the ground up
  • +Traces, logs, and metrics in one app
  • +ClickHouse storage for fast queries

Trade-offs

  • –Self-hosting still means operating ClickHouse
  • –Younger than the Grafana ecosystem
Visit SigNoz ↗
4

HyperDX

Best for: Full-stack debugging with session replay alongside logs and traces

MIT

HyperDX is an open-source, OpenTelemetry + ClickHouse platform that correlates session replay with logs, traces, and metrics, so you can jump from a user's broken session to the span behind it. Good fit for product and full-stack teams.

Strengths

  • +Session replay correlated with traces and logs
  • +OpenTelemetry-native, ClickHouse-backed
  • +Clean search-first UX

Trade-offs

  • –Younger project, smaller community
  • –Fewer prebuilt integrations than incumbents
Visit HyperDX ↗
5

OpenObserve

Best for: Cost-sensitive teams with very high log volume

AGPLv3

OpenObserve is a Rust-based observability platform designed for cheap, S3-backed storage at high volume. It shines for logs and is simple to run, with traces and metrics support that's maturing.

Strengths

  • +Very low storage cost (object storage / S3)
  • +Fast and simple to operate
  • +Strong logs experience

Trade-offs

  • –Tracing and metrics less mature than logs
  • –Smaller community than Grafana or SigNoz
Visit OpenObserve ↗
6

Uptrace

Best for: A lightweight OpenTelemetry APM on a budget

Source-available (BSL → Apache 2.0)

Uptrace is a lightweight, OpenTelemetry-native APM backed by ClickHouse, covering traces, logs, and metrics. It's easy to stand up for smaller deployments that want OTel support without much operational weight.

Strengths

  • +OpenTelemetry-native, ClickHouse-backed
  • +Lightweight and quick to deploy
  • +Unified traces, logs, and metrics

Trade-offs

  • –Source-available (BSL), not OSI open source
  • –Smaller ecosystem and team than larger projects
Visit Uptrace ↗
7

Jaeger + Prometheus

Best for: CNCF-native teams that want proven tracing and metrics

Apache 2.0 (CNCF)

Jaeger (tracing) and Prometheus (metrics) are CNCF-graduated, widely deployed, and free. Together they are a proven foundation, but they are two separate tools with no logs, so you build and operate the glue yourself.

Strengths

  • +CNCF-graduated, in production for years
  • +Ubiquitous in Kubernetes environments
  • +Completely free and vendor-neutral

Trade-offs

  • –Two+ separate tools, no unified logs
  • –You assemble dashboards and storage (Cassandra/Elasticsearch, etc.)
  • –No built-in correlation across signals
Visit Jaeger + Prometheus ↗

How to choose

Start with how your team already works. If you've standardized on OpenTelemetry, an OTel-native platform avoids re-instrumentation later. New to the category? Read what observability is and why OpenTelemetry matters first, then come back to this list.

FAQ

Common questions

What is the best open-source observability tool in 2026?
There is no single winner; it depends on how your team works. Maple is the strongest fit for OpenTelemetry-native teams that want AI-agent (MCP) workflows and usage-based pricing. Grafana's LGTM stack fits teams that want maximum configurability and don't mind operating several components. SigNoz is a solid all-in-one OTel-native APM. Match the tool to the “Best for” line rather than the rank.
Are open-source observability platforms production-ready?
Yes. Several are CNCF-graduated (Jaeger, Prometheus) and others run large production workloads today. Open source here means you can self-host, audit the code, and switch backends without re-instrumenting. It does not mean the tools are experimental.
Why does OpenTelemetry matter when choosing an observability tool?
OpenTelemetry is the vendor-neutral standard for traces, logs, and metrics. Instrumenting with OpenTelemetry means you can switch backends without re-instrumenting your code, so OTel-native tools like Maple, SigNoz, and Uptrace avoid the lock-in of proprietary agents.
Can I self-host all of these tools?
Yes. Every tool in this roundup can be self-hosted. SigNoz, HyperDX, and Uptrace run on ClickHouse; the Grafana stack uses Loki, Tempo, and Mimir; Jaeger and Prometheus are CNCF projects. Several, Maple included, also offer a managed cloud option if you would rather not run the infrastructure.
Is open-source observability cheaper than SaaS tools like Datadog?
Often, yes, especially at scale, where per-host and per-seat pricing compounds. Self-hosting trades software fees for infrastructure and operational time. If you would rather not operate it, the hosted editions of these tools (Maple, SigNoz, OpenObserve) price on usage, so the bill tracks volume rather than hosts or seats.
Which open-source tool is best for AI agents?
Maple ships a hosted MCP (Model Context Protocol) server, so compatible AI agents can list services, search traces, find errors, and propose fixes against your telemetry from one backend. Grafana also offers an official MCP server for its stack; with the LGTM setup the agent works across separate data stores.

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