SigNoz

Unternehmensdaten

Einheitentyp

COMPANY

Marktrolle

B2B SaaS Provider

Offizielle Website

signoz.io

Was SigNoz macht

SigNoz operiert nach einem klassischen Open-Core-Geschäftsmodell. Die frei zugängliche, selbstgehostete Community Edition dient als primärer Akquisitionskanal (Bottom-up-Adoption) in der Developer- und SRE-Community. Die Monetarisierung erfolgt über verbrauchsadäquate Nutzungsgebühren (Usage-based Pricing) basierend auf dem Volumen des Telemetrie-Ingests in der SigNoz Cloud sowie über kostenpflichtige Enterprise-Lizenzen für selbstverwaltete Deployments. Diese Enterprise-Tarife beinhalten Advanced-Features wie feingranulare rollenbasierte Zugriffskontrollen (RBAC), Single Sign-On (SSO), erweiterte Compliance-Audits sowie dedizierten Enterprise-Support mit garantierten SLAs. Dadurch löst SigNoz das Problem unvorhersehbarer, sitzplatzbasierter Lizenzkosten etablierter Wettbewerber und bietet stattdessen ein transparentes TCO-Modell für datenintensive Multi-Cloud-Umgebungen.

Strategische Einordnung

KI-gestützte Einordnung aus der bestehenden Unternehmensrecherche; Interpretation und belegte Fakten sind zu unterscheiden.

SigNoz positioniert sich als leistungsstarke, OpenTelemetry-native Open-Source-Alternative zu proprietären SaaS-Silos wie Datadog oder Dynatrace. Die Plattform konsolidiert Logs, Metriken und Traces (die drei Säulen der Observability) nativ in einer einheitlichen Applikationsperformance-Monitoring-Architektur (APM). Durch die direkte Integration von OpenTelemetry als Kernstandard eliminiert SigNoz teure, proprietäre Agenten-Deployments und ermöglicht SRE-, DevOps- und Platform-Engineering-Teams eine nahtlose Datenhoheit sowie präzise Ursachenanalyse (Root Cause Analysis) direkt in ihrer Infrastruktur. Die strategische Differenzierung basiert auf maximaler Flexibilität beim Deployment: Unternehmen können SigNoz sowohl als vollverwalteten Cloud-Service (SaaS) als auch als selbstgehostete, hochsichere Instanz innerhalb von VPCs betreiben. Dies adressiert insbesondere regulierte Industrien mit strengen Anforderungen an Data Governance, Datenschutz und Latenzminimierung, während gleichzeitig die typischen Skalierungseffekte moderner Cloud-Native-Architekturen voll ausgeschöpft werden.

Geschäftsmodell und Monetarisierung

SigNoz monetises through a hybrid open-core and usage-based SaaS model. The Community Edition is free and self-hosted. Revenue comes primarily from SigNoz Cloud, which is priced on telemetry ingestion volume rather than seats or hosts, and from enterprise-managed deployments operated inside customer infrastructure. Additional monetisation comes from premium support, managed operations and professional services tied to enterprise adoption.

SigNoz Cloud

Usage-based SaaS subscription

Managed on-prem enterprise deployments

Service Fee

Enterprise support and premium support plans

Service Fee

Professional services and implementation support

Service Fee

Produkte und Fähigkeiten

Für diese Ansicht liegen keine Produkte mit zugeordneten Quellen vor.

Produkte und Marktkategorien

Zuletzt erfasste Signale

Datumsangaben beziehen sich auf die Quellenveröffentlichung. Ältere Einträge sind historischer Kontext, kein Beleg für ein neues Ereignis.

• Deploying SigNoz with ClickHouse v25 and OTel Gotchas

  2026-08-19dev.to

  Application Performance Monitoring · Erfasster Impact-Score: 1/5

  A developer describes troubleshooting and deployment patterns for self-hosting SigNoz in 2026, focusing on ClickHouse v25 configuration changes, OpenTelemetry Collector incompatibilities, and Docker network isolation. Key recommendations include using config.d/users.d for ClickHouse overrides (instead of replacing the main config), enforcing a deterministic docker-compose boot sequence with one-shot migrator containers (signoz_init_clickhouse and signoz_telemetrystore_migrator), updating exporter names and image tags for the OTel collector (use signozclickhousemetrics and include the 'v' prefix), and relying on internal Docker network isolation rather than per-component passwords to simplify connectivity. The post emphasizes that maintaining self-hosted observability infrastructure requires ongoing engineering effort.

  • Author self-hosted SigNoz for Verne Software to control telemetry data.
  • ClickHouse v25+ changes require using config.d/ and users.d/ for overrides instead of replacing the main config file.

• SigNoz Hackathon: AI Agent with Failover and Diagnostics

  2026-07-26dev.to

  Application Performance Monitoring (APM) · Erfasster Impact-Score: 1/5

  A developer published a DEV.to post describing a hackathon project that implements an AI agent system which automatically fails over to a backup model when the primary model fails. The implementation sends observability data to SigNoz to track requests, monitor performance, and detect failures. The author also created a diagnostic agent that reads the monitoring data and explains failure reasons in plain language. During testing the system detected a real AI provider outage and automatically identified the root cause. The post was published on DEV on 2026-07-26.

  • Author built an AI agent system that automatically switches to a backup AI model if the main one fails.
  • All steps of the agent system were connected to SigNoz to track requests, monitor performance, and detect failures.

• Instrumenting MERN E‑Commerce with SigNoz

  2026-07-26dev.to

  Application Performance Monitoring (APM) · Erfasster Impact-Score: 2/5

  A developer case study describing how the author instrumented a MERN-stack e-commerce application called Ram Store with SigNoz and OpenTelemetry during the Agents of SigNoz Hackathon 2026. The project used a self-hosted SigNoz instance (Docker) and the OpenTelemetry Node SDK with automatic instrumentation for Express, HTTP, and MongoDB, exporting via OTLP gRPC. The instrumentation enabled distributed traces, runtime metrics, and structured logs (Winston) correlated inside SigNoz. The post covers setup steps, observed telemetry (traces, metrics, logs), challenges (Docker networking, configuration), lessons learned, and planned improvements like custom dashboards and alerting. Project source code and a demo video are linked.

  • Author integrated SigNoz into a MERN e-commerce application named Ram Store as part of the Agents of SigNoz Hackathon 2026.
  • SigNoz was self-hosted locally using Docker to provide observability dashboards.

• Observable AI Market-Research Agent Built with SigNoz

  2026-07-26dev.to

  Application Performance Monitoring (APM) · Erfasster Impact-Score: 2/5

  A Dev.to post (Jul 26, 2026) by Tanmay Kumar Pradhan describes an AI market-research agent instrumented for observability using OpenTelemetry and SigNoz. The implementation uses an openinference instrumentation package for Google ADK to capture distributed traces, token usage and latency (including Gemini 2.0 Flash generation), and error tracking. The article includes step-by-step local run instructions (SigNoz running, pip install, OTLP endpoint export, setting GOOGLE_API_KEY, and running via the ADK CLI) and frames the project as a SigNoz hackathon submission and demo for observable AI agents.

  • Tanmay Kumar Pradhan published a Dev.to article on 2026-07-26 titled "Building an Observable AI Market Research Agent with SigNoz".
  • The agent is instrumented with OpenTelemetry to export telemetry data to SigNoz for observability.

• Observability Reveals Why Sites 'Go Down'

  2026-07-26dev.to

  Application Performance Monitoring (APM) · Erfasster Impact-Score: 2/5

  The author built a fake exam-results site as a hackathon project to intentionally inject outages and observe them with the open-source observability tool SigNoz. By triggering four failure modes—database latency, cache (Redis) failure, a bad deploy that throws 500s, and traffic spikes—the author demonstrates that “server down” is not a single failure but distinct fingerprints visible in traces and metrics (fat slow spans, flatlined cache-hit rates, error-rate cliffs, rising RPS with latency). The project includes a Mission Control panel with toggles to inject incidents and a load generator, plus instructions to install SigNoz via a Foundry installer. The piece argues that pre-wired telemetry and alerts produce fast, specific diagnoses during incidents rather than vague “try later” responses.

  • The author created a fake exam-results portal to simulate production incidents during a hackathon.
  • The observability tool SigNoz was used to record traces, spans, and metrics while injecting failures.

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