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Rank #6 of 6 in Observability & Monitoring

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SigNoz

Open SourceYC W21

SigNoz, Inc.

signoz.io ↗Try it →
PA Score23/100AGENT-READY35/100BUILT-IN AI24/100API0/100
MCP✓CLI—API~
★ 32.1k▲ 5.6k/yr
ArenasObservability & Monitoring#6/6

Access

Open app ↗API docs ↗MCP docs ↗

Install

dockergit clone -b main https://github.com/SigNoz/signoz.git && cd signoz/deploy/docker && docker compose up -d --remove-orphans
skillsnpx skills add SigNoz/agent-skills

Compare head-to-head

Datadog logovs DatadogGrafana logovs GrafanaSentry logovs SentryNew Relic logovs New RelicHoneycomb logovs Honeycomb

Alternatives to SigNoz →

Try itExperimental

See what an agent can do with SigNoz before you ever sign up. Pick a story: recorded sessions replay real probe-harness transcripts; commands tagged live-capable can re-run against the real endpoint from our edge, right now (▶ run live — the exact same request, live and recorded lines always labeled); sandboxed self-drive sessions are designed and gated (docs/TRY-IT.md).

$curl -s https://signoz.io/llms.txt | head -6recorded session — replayed, not live
recorded 2026-09-15 · exit 0 · captured verbatim by our probe harness, secrets redacted · pure-HTTP probe — ▶ run live re-runs it from our edge

Verified integrations

No integration evidence found in our corpus for this product yet — that means none was found, never that it doesn’t integrate.

By theme — the product's score on each story themeBy theme

Agenticness — how well agents can access and operate the productAgenticnessevidence →

How well agents can access and operate the product

26.1/100

Ai assist — stories about ai assist in this arenaAi assistevidence →

Stories about ai assist in this arena

55.0/100

Alerting slos — stories about alerting slos in this arenaAlerting slosevidence →

Stories about alerting slos in this arena

6.7/100

Automation depth — how much of the product can run unattendedAutomation depthevidence →

How much of the product can run unattended

18.0/100

Cost sampling — stories about cost sampling in this arenaCost samplingevidence →

Stories about cost sampling in this arena

0.0/100

Dashboards as code — stories about dashboards as code in this arenaDashboards as codeevidence →

Stories about dashboards as code in this arena

53.6/100

Deployment openness — stories about deployment openness in this arenaDeployment opennessevidence →

Stories about deployment openness in this arena

32.0/100

Incident response — stories about incident response in this arenaIncident responseevidence →

Stories about incident response in this arena

12.0/100

Openness — open source, data portability, and self-hosting storiesOpennessevidence →

Open source, data portability, and self-hosting stories

29.4/100

Otel standards — stories about otel standards in this arenaOtel standardsevidence →

Stories about otel standards in this arena

62.4/100

Privacy posture — data-handling and privacy storiesPrivacy postureevidence →

Data-handling and privacy stories

12.0/100

Query analytics — stories about query analytics in this arenaQuery analyticsevidence →

Stories about query analytics in this arena

34.3/100

Telemetry unified — stories about telemetry unified in this arenaTelemetry unifiedevidence →

Stories about telemetry unified in this arena

49.7/100

Story verdicts — every judged story with its evidenceStory verdicts

?

Sorted by importance (agentic first) (high → low) · 54/54 stories · click a row’s chevron for the rationale and evidence

Connect an agent via an official MCP server G

Agent access

ai-native userAgenticness — how well agents can access and operate the productAgenticness3full9/10T

Drive the product through a documented public API G

Agent access

ai-native userAgenticness — how well agents can access and operate the productAgenticness3partial4/10T

Delegate tasks to a built-in AI assistant inside the product G

Agentic features

ai-native userAgenticness — how well agents can access and operate the productAgenticness3none0/10

Plug MCP servers into this product so it can use their tools G

Agent access

ai-native userAgenticness — how well agents can access and operate the productAgenticness3none0/10

Point an agent at llms.txt or agent-oriented docs G

Agent access

ai-native userAgenticness — how well agents can access and operate the productAgenticness2full9/10T

Operate the product with natural-language commands G

Agentic features

ai-native userAgenticness — how well agents can access and operate the productAgenticness2full7/10T

Build against official SDKs G

Agent access

ai-native userAgenticness — how well agents can access and operate the productAgenticness2partial6/10C

Get AI-generated insights and suggestions from my data inside the product G

Agentic features

ai-native userAgenticness — how well agents can access and operate the productAgenticness2partial6/10T

Issue scoped/least-privilege API credentials for an agent G

Agent access

ai-native userAgenticness — how well agents can access and operate the productAgenticness2partial6/10C

Run the product headlessly / in CI for automation G

Agent access

ai-native userAgenticness — how well agents can access and operate the productAgenticness2partial5/10C

Download a machine-readable API spec (OpenAPI or equivalent) G

Api quality

ai-native userAgenticness — how well agents can access and operate the productAgenticness2none0/10

Explore an interactive API reference with runnable examples G

Api quality

ai-native userAgenticness — how well agents can access and operate the productAgenticness2none0/10

Rely on versioned APIs with a documented deprecation policy G

Api quality

ai-native userAgenticness — how well agents can access and operate the productAgenticness2none0/10

Set up automations that run autonomously in the background G

Agentic features

ai-native userAgenticness — how well agents can access and operate the productAgenticness2none0/10

Subscribe to events via webhooks G

Agent access

ai-native userAgenticness — how well agents can access and operate the productAgenticness2noneuntestednone yet

Use an official CLI G

Agent access

ai-native userAgenticness — how well agents can access and operate the productAgenticness2noneuntestednone yet

Test against a sandbox environment without touching production data G

Api quality

ai-native userAgenticness — how well agents can access and operate the productAgenticness1n/auntestednone yet

Collect metrics, logs, and traces in one platform and pivot between them with shared context C

Signals

sreTelemetry unified — stories about telemetry unified in this arenaTelemetry unified3full8/10T

Have an external agent query metrics, logs, and traces through documented APIs to debug production C

Agent integration

ai-native userAi assist — stories about ai assist in this arenaAi assist3full8/10T

Send telemetry directly over OTLP with first-class OpenTelemetry support C

Otel

developerOtel standards — stories about otel standards in this arenaOtel standards3full8/10T

Analyze telemetry ad hoc with a documented query language C

Query language

developerQuery analytics — stories about query analytics in this arenaQuery analytics3full7/10C

Define dashboards and alerts as code (JSON models, Terraform, or API) and provision them repeatably C

As code

developerDashboards as code — stories about dashboards as code in this arenaDashboards as code3partial6/10T

Export all of my data in open formats and leave G

ai-native userOpenness — open source, data portability, and self-hosting storiesOpenness3partial6/10X

Self-host the core product G

ai-native userOpenness — open source, data portability, and self-hosting storiesOpenness3partial6/10X

Have the platform's AI investigate an alert or error and propose a probable root cause C

Ai investigation

ai-native userAi assist — stories about ai assist in this arenaAi assist3partial5/10T

Define rules that trigger actions automatically on events G

ai-native userAutomation depth — how much of the product can run unattendedAutomation depth3partial4/10C

Alert on any telemetry signal with routing, grouping, and silencing of notifications C

Alerting

sreAlerting slos — stories about alerting slos in this arenaAlerting slos3partial3/10C

See what my observability spend is, attribute it to teams or services, and catch usage spikes before the bill C

Cost

sreCost sampling — stories about cost sampling in this arenaCost sampling3none0/10

Prevent my data from being used to train AI models G

ai-native userPrivacy posture — data-handling and privacy storiesPrivacy posture3n/auntestednone yet

Ask questions of my telemetry in natural language and get a real query or chart back C

Ai querying

ai-native userAi assist — stories about ai assist in this arenaAi assist2full8/10T

Build shareable dashboards with rich visualization types and template variables C

Dashboards

sreDashboards as code — stories about dashboards as code in this arenaDashboards as code2full8/10C

Choose where my data is stored (region/residency) G

ai-native userPrivacy posture — data-handling and privacy storiesPrivacy posture2partial6/10T

Instrument once with open standards and switch backends without re-instrumenting my code C

Otel

sreOtel standards — stories about otel standards in this arenaOtel standards2partial6/10C

Get AI-generated summaries of incidents and alert context for responders C

Ai investigation

ai-native userAi assist — stories about ai assist in this arenaAi assist2partial5/10T

Group and filter by high-cardinality fields (user id, request id) without pre-aggregating or defining indexes first C

Analysis

developerQuery analytics — stories about query analytics in this arenaQuery analytics2disputed5/10D

Instrument hosts, containers, Kubernetes, and cloud services through vendor-maintained agents and integrations C

Instrumentation

sreTelemetry unified — stories about telemetry unified in this arenaTelemetry unified2partial5/10X

Read the product's source under an open license G

ai-native userOpenness — open source, data portability, and self-hosting storiesOpenness2disputed5/10D

Run the full observability stack self-hosted in production with documented architecture and upgrade path G

Self host

sreDeployment openness — stories about deployment openness in this arenaDeployment openness2partial5/10X

Correlate regressions with deploys and configuration changes via release or change tracking C

Change tracking

developerIncident response — stories about incident response in this arenaIncident response2partial4/10C

Do everything through the API that I can do in the UI G

ai-native userOpenness — open source, data portability, and self-hosting storiesOpenness2partial4/10T

Jump from a trace span to its correlated logs and metrics to debug a request end to end C

Correlation

developerTelemetry unified — stories about telemetry unified in this arenaTelemetry unified2partial4/10C

Perform bulk operations across many items at once G

ai-native userAutomation depth — how much of the product can run unattendedAutomation depth2partial3/10T

Control data retention and deletion G

ai-native userPrivacy posture — data-handling and privacy storiesPrivacy posture2none0/10

Define SLOs with error budgets and burn-rate alerts C

Slos

sreAlerting slos — stories about alerting slos in this arenaAlerting slos2none0/10

Control trace/log sampling and retention tiers to manage data volume deliberately C

Sampling

developerCost sampling — stories about cost sampling in this arenaCost sampling2noneuntestednone yet

Declare and track incidents with timelines, on-call schedules, and escalation policies C

Incidents

sreIncident response — stories about incident response in this arenaIncident response2noneuntestednone yet

Opt out of telemetry and usage tracking G

ai-native userPrivacy posture — data-handling and privacy storiesPrivacy posture2noneuntestednone yet

Point alert notifications at webhooks that trigger automated remediation or agents G

Alert automation

ai-native userAlerting slos — stories about alerting slos in this arenaAlerting slos2noneuntestednone yet

Schedule recurring jobs or workflows G

ai-native userAutomation depth — how much of the product can run unattendedAutomation depth2n/auntestednone yet

See application errors grouped into issues with stack traces, release tracking, and regression detection C

Errors

developerQuery analytics — stories about query analytics in this arenaQuery analytics2noneuntestednone yet

Spin up a local or dev instance of the platform to test instrumentation and dashboards C

Local dev

developerDeployment openness — stories about deployment openness in this arenaDeployment openness1partial6/10X

Predict costs from transparent published per-signal pricing without talking to sales G

Cost

sreCost sampling — stories about cost sampling in this arenaCost sampling1none0/10

Enable anomaly or outlier detection that surfaces problems without hand-written thresholds C

Alerting

sreAlerting slos — stories about alerting slos in this arenaAlerting slos1noneuntestednone yet

Version, review, and roll back my automations G

ai-native userAutomation depth — how much of the product can run unattendedAutomation depth1noneuntestednone yet

Opportunities — the stories that would move this product's scores, from its own judged verdictsOpportunitiestop 8 of 40 stories with headroom

What would move SigNoz’s scores — derived from its own judged verdicts, biggest headroom first. Each line quotes what the judge found missing; shipping it (or evidencing it publicly) is the fix.

  1. Agenticness — how well agents can access and operate the productDelegate tasks to a built-in AI assistant inside the product

    nonemoves Built-in AIimpact 45

    SigNoz's AI-related evidence describes an MCP server that lets external AI assistants (Claude, Cursor, Copilot) query SigNoz data — this is SigNoz acting as a tool for outside agents, not a built-in assistant embedded in the product itself that a user could delegate tasks to.

  2. Agenticness — how well agents can access and operate the productPlug MCP servers into this product so it can use their tools

    nonemoves agent-readyimpact 45

    All AI/MCP evidence shows SigNoz exposing its own MCP server so external agents (Claude, Cursor, Copilot) can call SigNoz's tools — the reverse of the story, which asks whether SigNoz itself can consume external MCP servers' tools.

  3. Cost sampling — stories about cost sampling in this arenaSee what my observability spend is, attribute it to teams or services, and catch usage spikes before the bill

    nonemoves PA Scoreimpact 30

    The evidence pack contains extensive documentation on traces, logs, metrics, dashboards, and alerting, but nothing about cost/spend visibility, per-team or per-service cost attribution, ingestion volume tracking, or spike/budget alerting on observability usage itself.

  4. Agenticness — how well agents can access and operate the productSet up automations that run autonomously in the background

    nonemoves Built-in AIimpact 30

    Missing: evidence of autonomous/scheduled background automation execution, agent-triggered workflows without human prompting, any autonomous remediation or monitoring loop.

  5. Agenticness — how well agents can access and operate the productUse an official CLI

    nonemoves agent-readyimpact 30

    The evidence pack documents MCP server support, Agent Skills, and dashboards-as-code, but no official SigNoz CLI is mentioned anywhere in the docs or GitHub materials.

  6. Agenticness — how well agents can access and operate the productSubscribe to events via webhooks

    nonemoves agent-readyimpact 30

    The evidence pack describes alerting on logs/metrics and API access via service accounts, but never mentions webhook-based event subscriptions or outbound webhook notifications for alerts or other events.

  7. Agenticness — how well agents can access and operate the productExplore an interactive API reference with runnable examples

    nonemoves API qualityimpact 30

    No evidence of an interactive API reference with runnable examples; the OpenAPI probe explicitly found all candidate spec paths returning 404, and no docs mention a Swagger/Redoc-style interactive playground.

  8. Agenticness — how well agents can access and operate the productDownload a machine-readable API spec (OpenAPI or equivalent)

    nonemoves API qualityimpact 30

    A direct probe for OpenAPI/Swagger spec endpoints returned 404 across all candidate paths, and no evidence pack item references a downloadable machine-readable API spec despite mentions of programmatic API access via service accounts.

Showing the top 8 of 40 — every none/partial verdict in the story verdicts table is headroom.

Think a verdict is wrong? Every verdicts-table row has a Flag link — see the methodology.

Coverage map — which docs area, API section, or community source covers which judged storiesCoverage map6 surfaces · 32 covered stories

Where the cited evidence behind each covered verdict came from — the same citations the verdicts table shows, no extra judging.

docs28 stories

GitHub README8 stories

Hacker News7 stories

Skill docs6 stories

OpenAPI spec5 stories

llms.txt4 stories

Probe proofs — replayable recordings from the probe harnessProbe proofs

Replayable recordings from our probe harness — see the Prove-It protocol to submit one.

$curl -s https://signoz.io/llms.txt | head -6reproduced
$ curl -s https://signoz.io/llms.txt | head -6
# SigNoz

> SigNoz Cloud brings your traces, metrics, and logs into one OpenTelemetry-native platform. Simple usage-based pricing, and the freedom to run on your infrastructure with Self-Hosted SigNoz.

Markdown versions of every page are available: append ".md" to any signoz.io page URL — docs (https://signoz.io/docs/introduction.md), blog posts (https://signoz.io/blog/<slug>.md), comparisons, guides, and product pages like https://signoz.io/pricing.md — or request any page with "Accept: text/markdown".
proves: Point an agent at llms.txt or agent-oriented docsrecorded 2026-09-15
$curl -si -X POST https://mcp.us.signoz.cloud/mcp -H 'Content-Type: application/json' -d '<jsonrpc initialize>'reproduced
$ curl -si -X POST https://mcp.us.signoz.cloud/mcp -H 'Content-Type: application/json' -d '<jsonrpc initialize>'
HTTP/2 401

date: Tue, 15 Sep 2026 17:36:38 GMT

content-type: text/plain; charset=utf-8

content-length: 48

www-authenticate: Bearer resource_metadata="https://mcp.us.signoz.cloud/.well-known/oauth-protected-resource"

x-content-type-options: nosniff

strict-transport-security: max-age=31536000; includeSubDomains

server: signoz.edge

Authorization or SIGNOZ-API-[redacted] header required
proves: Connect an agent via an official MCP serverrecorded 2026-09-15
$curl -sL https://signoz.io/api/api-reference-openapi/latest/ | head -5reproduced
$ curl -sL https://signoz.io/api/api-reference-openapi/latest/ | head -5
components:
  schemas:
    AlertmanagertypesChannel:
      properties:
        createdAt:
proves: Download a machine-readable API spec (OpenAPI or equivalent)proves: Drive the product through a documented public APIrecorded 2026-09-15

Claims vs evidence — vendor claims reconciled against independent verdictsClaims vs evidence

9 of 17 testable claims verified · 2 contradicted → integrity 29/100

30 distinct capability claims found in SigNoz’s own claimed-docs/GitHub materials, reconciled against our judge’s independent verdicts.

9

Verified

6

Unverified

2

Contradicted

15

Undersold

Verified (15)
Unverified (12)
Contradicted (2)
Undersold (15)
Claims outside our story set (7)

Real capability claims found in SigNoz’s own materials, but no story in this arena’s taxonomy covers them yet — that’s feedback on the taxonomy, not a mark against the product.

  • “Provides a flamegraph/trace view showing every span, duration, and parent-child relationships across services”

    source ↗

  • “Analyzes request flow through a sequence of services to find drop-off points (funnel analysis)”

    source ↗

  • “Parses, transforms, and enriches logs before storage via a functional pipeline builder”

    source ↗

  • “Provides a complete guide for migrating metrics, traces/APM, logs, dashboards, and alerts from Datadog”

    source ↗

  • “Migration from another platform can be done incrementally, one signal type at a time, running both platforms in parallel”

    source ↗

  • “Offers a Datadog Receiver as a bridge solution for ingesting Datadog-format telemetry”

    source ↗

  • “Role-based access control where roles group transactions/permissions assigned to principals”

    source ↗
Suggest a story for these →

Business model

open-sourcefree-tierusage-basedenterprise-custom

MIT-licensed core you can self-host free; SigNoz Cloud is usage-based per GB of ingested telemetry with a free trial, plus enterprise self-hosted support plans.

pricing ↗

Score trend

How this product’s scores have moved as evidence and verdicts are re-derived — a point per change, not per day.

PA Scoretracked since Sep 15 '26 — no movement recorded yet
Agent-readytracked since Sep 15 '26 — no movement recorded yet

Try Experimental

Run it in the microterminal →

Recorded agent sessions — and a live MCP handshake where the vendor ships one.

Flag

⚑ Flag a verdict

Think a verdict is wrong? Opens a prefilled GitHub issue — or use the ⚑ next to any verdict above.

Badge

Embed this product's score badge →

Hotlinked SVG — always shows the live current score.

For agents

This page as markdown/llms.txt

Data

Evidence (JSON)Verdicts (JSON)