OpenObserve

OpenObserve is an AGPL-3.0 open-source observability platform, written in Rust, that unifies logs, metrics, traces, real user monitoring and LLM observability in a single binary backed by object storage. It is built for platform and SRE teams who want Datadog-class coverage at self-hosted cost, without operating an Elasticsearch or Cassandra cluster underneath it.

OpenObserve is an open-source observability platform written in Rust that unifies logs, metrics, traces, real user monitoring, session replay, error tracking, ingest pipelines and LLM observability behind a single binary. Rather than running an Elasticsearch or Cassandra cluster, it writes Parquet columnar files straight to object storage — S3, GCS or Azure Blob — which is the basis of its claim of up to 140x lower storage cost than index-based alternatives, and it removes the database tier that normally dominates observability operations. It ingests OpenTelemetry natively, accepts Prometheus remote write, deploys through a single Helm chart or a Kubernetes operator, and prices cloud usage on ingested volume rather than per node or per host. The AGPL-3.0 open-source edition passed 20,000 GitHub stars in July 2026 — 20.6k at the time of writing, against 547 open issues and roughly 6,800 commits on main — and the vendor reports more than 7,000 organisations running it. In April 2026 OpenObserve raised a $10M Series A led by Nexus Venture Partners and Dell Technologies Capital, both returning from seed, and shipped what it calls Observability 3.0: an AI SRE that reads logs, metrics, traces and GitHub, Kubernetes, AWS, GCP and Azure signals in real time to identify root causes and recommend corrective actions; anomaly detection that surfaces degradation before an incident; and LLM observability covering prompt monitoring, evaluation tracking, token and cost accounting, latency percentiles, error rates, agent graphs and session traces. The O2 AI Assistant writes SQL, VRL and PromQL for users and walks them through incidents. Founded in 2022 by Prabhat Sharma and based in Menlo Park, California, the company holds SOC 2 Type II and ISO 27001 certification, supports SAML, OIDC, OAuth, LDAP and Active Directory, and offers its self-hosted Enterprise edition free up to 50 GB of daily ingestion.

Category

Infrastructure & Cloud

Pricing

Free, Usage-based, Subscription, Contact for pricing

Target Market

CTOs, VPs of Engineering, SRE and Platform Teams, DevOps Engineers, Enterprise Developers

Deployment

Open-source, Self-hosted, Cloud-first, Hybrid

Founded

2022

Headquarters

Menlo Park, California, USA

Customers

7,000+ organisations running the platform (vendor-reported, April 2026); an independent report cited 6,000+ at the time of the Series A

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  Single-binary Rust deployment on object storage

  Runs as one binary writing Parquet to S3, GCS or Azure Blob with no separate database cluster to size, tune or operate.

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  Unified logs, metrics, traces, RUM and session replay

  One platform covers backend telemetry and frontend monitoring including error tracking, removing the need for separate vendors per signal.

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  LLM observability

  Tracks cost, tokens, latency percentiles and error rates across models with agent graphs, session traces and evaluation quality scoring.

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  AI SRE autonomous incident layer

  Analyses telemetry plus GitHub, Kubernetes, AWS, GCP and Azure signals in real time to identify root causes and recommend fixes.

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  O2 AI Assistant

  Writes SQL, VRL and PromQL on the user's behalf and walks engineers through logs, traces, metrics and incidents conversationally.

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  Ingest pipelines with redaction

  Redacts or hashes sensitive fields at ingest time so regulated data never lands in the observability store in the clear.

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  Kubernetes operator and Helm chart

  Deploys natively into clusters with OpenTelemetry ingestion, Prometheus remote write and per-namespace or per-cluster tenancy routing.

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  Replacing an indexed logging stack to cut storage cost

  Teams migrate off Elasticsearch or Datadog onto Parquet-on-object-storage, which the vendor benchmarks at up to 140x lower storage cost.

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  Kubernetes cluster observability from a single Helm chart

  Platform engineers ingest cluster logs and metrics via OpenTelemetry and Prometheus remote write without per-node licensing.

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  Monitoring a generative-AI application in production

  Engineers watch prompt behaviour, token spend, model latency and evaluation scores next to the service telemetry from the same app.

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  Autonomous first-pass incident triage

  The AI SRE correlates telemetry with infrastructure and GitHub signals to propose a root cause before an on-call engineer opens the console.

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  Self-hosted observability under data-sovereignty constraints

  Organisations run the Enterprise edition inside their own VPC so telemetry never leaves a jurisdiction they control.

Metering is by ingested and queried volume, never per host or per node, which is the whole point of the pitch. The AGPL-3.0 open-source edition is free forever and self-hostable; the Self-Hosted Enterprise edition is free up to 50 GB of daily ingestion and needs a sales conversation above that. Cloud Professional publishes list pricing at $0.50/GB ingested and $0.01/GB queried, with a 30% annual-commitment discount, 15-month metrics retention, 30-day non-metrics retention and $0.02/GB per additional 30-day retention period; a 14-day trial needs no card. SSO, RBAC, audit trail, federated search, sensitive-data redaction, incident management and the AI SRE agent are all Enterprise-gated, and the AI features are free during preview with a 20-credit allowance.

This page was written from 6 sources, 3 on domains other than openobserve.ai.

1. 1.openobserve.ai — pricingvendor
2. 2.openobserve.ai — series a announcementvendor
3. 3.openobserve.ai — security compliancevendor
4. 4.github.com — openobserve
5. 5.itbrief.news — openobserve raises usd 10 million for observability 3 0
6. 6.hn.algolia.com — hn.algolia.com