140x more storage efficient vs Elastic

Open-Source, Unified Observability
for the AI Era

Talk to a Human

Observability Layers

Frontend

AI & LLM

API

Application

Database

Network

Infrastructure

LMT

Logs · Metrics · Traces from each layer

Autocorrelation Engine ANALYZING1.24M signals/s · 86K pairs correlated

Observability Layers

Frontend
AI & LLM
API
Application
Database
Network
Infrastructure

LMTLogs · Metrics · Traces from each layer

Autocorrelation Engine ANALYZING1.24M signals/s · 86K pairs correlated

Unified observability INVESTIGATING

Payments API - checkout errors rising

AI SRE agent · Payments API - checkout errors rising

Service graph

CheckoutPayments APIledger-db+9 upstream

Impact analysis

3 services affected12% of checkouts2 SLOs at risk

Root cause

Deploy payments-api v2.14 at 14:02 halved the connection pool - traces show 94% of errors waiting on pool_acquire.

Corrective action

Roll back to v2.13 · restore pool 40 → 80Applied ✓

Incident resolved automaticallyError rate back to baseline · MTTR 3m 12s · no human paged

Intelligent proactive observability REVIEWING

14 services reviewed - 1 needs attention

Daily briefing · 14 services reviewed · last 14 days

13 healthy1 degradinglast 14 days

SERVICEP95ERRORS

Checkout web240 ms0.2%

Search service533 ms9.4%

Payments API196 ms0.4%

ledger-db88 ms0.1%

Search service · 14 days

p95 latencyerror rate

Jul 14Jul 21Jul 27

Latency 186 ms → 533 ms, errors 0.3% → 9.4% within an hour of the Jul 21 index rebuild - and flat ever since.

Agentic observability MONITORING

Token spend up 18% - 1 failed completion

Agentic observability · 6 models in production · last 24h

SPEND TODAY

$412.80

TOKENS

18.4M

ERROR RATE

2.1%

Token cost · last 7 days

$210$412 ↗

GPT-4o 46%Claude 28%Llama 3 16%Other 10%

RECENT PROMPTSTOKENSSTATUS

summarize-ticket · GPT-4o2,140200 OK

route-intent · Llama 3610200 OK

refund-agent · GPT-4o8,932ERROR

agent.workflow.o2-ai13 spans1 error

29 Jun 12:36:06 · 0us - 1.41m

o2-aisagent.workflow.o2-ai1.41m

o2-aicgen_ai.chat.completions deepseek-v4-pro1.41m⧗ 9.3K$ 0.0055

o2-aiiagent.stream1.41m

o2-aiigen_ai.execute_tool o2_tools_call156.77ms

o2-aiigen_ai.execute_tool o2_tools_call203.07ms

o2-aiigen_ai.execute_tool o2_tools_call176.33ms

o2-aiigen_ai.execute_tool o2_tools_call388.38ms

o2-aiigen_ai.execute_tool create_navigation243.00us

refund-agent · GPT-4oeval failed · policy-compliance

PROMPT

"Refund order #48213 and explain the policy exception to the customer."

REASONING

Retrieved 14 prior tickets and the refund policy, then matched on "damaged item" and skipped the 30-day age check.

OUTPUT

"Your refund has been approved and will land in 3–5 business days."

EVAL FAILED · policy-compliance

Order #48213 is 47 days old - outside the 30-day window the policy doc allows. Grader score 0.41 (threshold 0.80); the refund was promised without an exception approval.

Why OpenObserve

Four reasons teams switch

Built for scale, priced for reality
Columnar Parquet storage delivers roughly 40x compression and up to 140x lower storage costs than Elasticsearch. Written in Rust on the DataFusion query engine, OpenObserve queries a petabyte of data in about 2 seconds.
- 140xlower storage cost vs. Elasticsearch
- 100xmore performant
- 5 PB/daylargest customer ingestion
See BenchmarksSee Benchmarks

Built for scale, priced for reality

Columnar Parquet storage delivers roughly 40x compression and up to 140x lower storage costs than Elasticsearch. Written in Rust on the DataFusion query engine, OpenObserve queries a petabyte of data in about 2 seconds.

140xlower storage cost vs. Elasticsearch
100xmore performant
5 PB/daylargest customer ingestion

See Benchmarks

One platform, every signal

Logs, metrics, traces, real user monitoring, and session replay live in a single tool with one query language. No stitching together five separate systems, no per-tool learning curve.

140+Datasources supported
1binary, one query layer
0proprietary query languages

Explore the Platform

Nothing hidden, nothing locked in

The full codebase is open source under AGPL-3.0: audit it, extend it, self-host it. Built on open standards like OpenTelemetry so your data is never trapped in a proprietary format.

AGPL-3.0fully open source license
21.6k+GitHub stars
100%commits public

View the Repo

Your infrastructure, your rules

Run OpenObserve as a single binary, a Helm chart in Kubernetes, or fully managed on OpenObserve Cloud. Bring your own storage: local disk, S3, GCS, MinIO, or Azure Blob.

3ways to deploy: binary, Helm, or Cloud
5storage backends supported
0vendor lock-in

See Deployment Options

Built for scale, priced for reality

140xlower storage cost vs. Elasticsearch
100xmore performant
5 PB/daylargest customer ingestion

See Benchmarks

How It Works

One stack, every signal

Explore how telemetry is collected, correlated and turned into answers. Click any tile or layer of the stack to open it.

Unified observability stack

Every signal from your estate flows into one correlated view.

Click a layer of the stack to open it. Click again to close.

Product Tour

Every signal, one platform

Petabyte-scale log search

Ingest and query trillions of log lines with familiar SQL: no indexing tax, no surprise storage bills.

Frontend / real user monitoring dashboard in OpenObserve

Explore Logs

Petabyte-scale log search
Ingest and query trillions of log lines with familiar SQL: no indexing tax, no surprise storage bills.
Explore LogsExplore Logs
Metrics
Store and query Prometheus-compatible metrics at any scale, with the same engine powering your logs.
Explore MetricsExplore Metrics
Distributed tracing
Follow every request across services with full trace context, auto-correlated with logs and metrics.
Explore TracesExplore Traces
Build dashboards in minutes
Drag-and-drop panels across every signal, or bring your existing Grafana boards straight over.
Explore DashboardsExplore Dashboards
Alerts
Set real-time and scheduled alerts on logs, metrics and traces, and route notifications to Slack, PagerDuty, email and more.
Explore AlertsExplore Alerts
AI SRE agent
An always-on agent that triages incidents, correlates root cause, and drafts the postmortem for you.
Explore AI SREExplore AI SRE
AI assistant
Ask natural-language questions across every log, metric, and trace. Get an answer, not another query language.
Explore AI assistantExplore AI assistant
LLM Observability
Trace prompts, completions, token usage and cost across your LLM applications to debug quality and spend.
Explore LLM ObservabilityExplore LLM Observability
SLOs
Define and monitor service-level objectives to ensure consistent performance.
Explore SLOsExplore SLOs
Real user monitoring
See exactly how real users experience your app: session traces, Core Web Vitals, and errors, correlated with backend traces.
Explore RUMExplore RUM
Synthetic monitoring
Proactively monitor your applications and services from outside-in.
Explore Synthetic monitoringExplore Synthetic monitoring

Benchmarks

Measured against industry leaders

Same telemetry, same workloads, one platform. Every number is OpenObserve against a named vendor - not an industry average.

vs. Dynatrace
10×
faster performance
Dashboards and queries return in milliseconds, not minutes.
Read case study
vs. Datadog
8×
more cost-effective
Logs, metrics and traces on one bill instead of three.
Read case study
vs. Elastic
140×
storage efficiency
Keep a year of history without a year's worth of bill.
Read case study
vs. New Relic
30×
compute efficiency
Index everything. Stop sampling away the incident you need.
Read case study

See how much you would save switching today.

Calculate your savings See all comparisons

One platform, every workload

Correlate between environments and signals across every source with the OpenObserve built-in correlation engine.

Kubernetes

Full-stack visibility across every cluster

Deploy the collector with one command. Container logs, cluster events and metrics arrive together, plus zero-code traces for workloads already running.

Container logs, Kubernetes events and cluster metrics from one install
Zero-code traces for workloads you have not instrumented
Dashboards and alert rules ship pre-built
Holds up under ephemeral, high-cardinality churn

Explore Kubernetes observability

Kubernetes

~3 min setupClusterLogsMetricsEventsTraces

curl -sSL https://raw.githubusercontent.com/openobserve/o2-datasource/main/k8s/install.sh | bash -s -- \
  --cluster-name=cluster1 \
  --access-key=•••••••••••••••••••••••• \
  --o2-url=https://your-org.openobserve.ai

Installs cert-manager, the OTel operator and the collector automatically

pod logs

cluster metrics

app traces

one incident, one timestamp

Integrations