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Guide

Best open-source observability tools in 2026

OpenTelemetry-native traces, logs, and metrics you can self-host — ranked honestly, with what each tool is genuinely best for.

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We build Maple, so we list it first — but this is an honest roundup, not a sales page. 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 natively each one speaks OpenTelemetry, whether it unifies 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 honest pricing

Source-available (FSL-1.1 → Apache 2.0)

Maple is an OpenTelemetry-native observability platform built on ClickHouse, covering traces, logs, metrics, and browser session replay in one app. It ships a first-class MCP server so AI agents can search traces, find errors, and propose fixes, and it prices on usage instead of per-host or per-seat. 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 — no proprietary agents or lock-in
  • +ClickHouse-grade query speed over billions of rows
  • +First-class MCP server for AI agents
  • +Session replay linked to your traces via a shared session id
  • +Transparent usage-based pricing; 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's the most widely deployed open-source option and endlessly flexible, but you assemble and operate several systems yourself.

Strengths

  • +Huge ecosystem, plugins, and community
  • +Best-in-class dashboarding
  • +Mix and match Loki / Tempo / Mimir as needed

Trade-offs

  • –You run and tune multiple separate systems
  • –Operational overhead grows with scale
  • –OpenTelemetry support is good but bolted onto each component
Visit Grafana (LGTM stack) ↗ Maple vs Grafana
3

SigNoz

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

MIT (with paid enterprise tier)

SigNoz is an OpenTelemetry-native, ClickHouse-backed APM that unifies traces, logs, and metrics in a single application — a close peer to Maple. It's 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 battle-tested tracing and metrics

Apache 2.0 (CNCF)

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

Strengths

  • +CNCF-graduated and battle-tested
  • +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

Frequently asked questions

What is the best open-source observability tool in 2026?
There's 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 is best when you want maximum flexibility and don't mind operating several components; SigNoz is a great 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 avoid vendor lock-in — not that 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. Maple, SigNoz, HyperDX, and Uptrace are ClickHouse-backed; the Grafana stack uses Loki/Tempo/Mimir; Jaeger and Prometheus are CNCF projects. Several also offer a managed cloud option if you'd rather not run the infrastructure.
Is open-source observability cheaper than SaaS tools like Datadog?
Often, yes — especially at scale, where SaaS per-host and per-GB pricing compounds. Self-hosting trades software fees for infrastructure and operational time. Tools with usage-based pricing or cheap object storage (Maple, OpenObserve) keep costs predictable without you operating everything yourself.
Which open-source tool is best for AI agents?
Maple ships a first-class MCP (Model Context Protocol) server, so compatible AI agents can list services, search traces, find errors, and propose fixes directly against your telemetry — the most complete AI-agent story among the tools here.

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