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Getting Started with OpenObserve

August 27, 2026
11:00 AM ET
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140x more storage efficient vs Elastic

Open-Source High-Performance Unified Observability

For the AI Era

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

1
Service graph
CheckoutPayments APIledger-db+9 upstream
2
Impact analysis
3 services affected12% of checkouts2 SLOs at risk
3
Root cause
Deploy payments-api v2.14 at 14:02 halved the connection pool — traces show 94% of errors waiting on pool_acquire.
4
Corrective action
Roll back to v2.13 · restore pool 40 → 80Applied ✓
Incident resolved automaticallyError rate back to baseline · MTTR 3m 12s · no human paged
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, up to
    • 2.5 PB/daylargest customer ingestion
    See BenchmarksSee 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
Benchmarks

Measured against the platforms you are already paying for

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.

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 observabilityExplore 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

Plug into your stack

Real User Monitoring (RUM)OpenTelemetryCurlElasticSearchPrometheusVectorFluent BitFluentdFilebeatTelegrafKinesis FirehoseSyslogOpenAI (Python)Anthropic (Python)Google GeminiAmazon BedrockMistralOllamaDeepSeekOpenAI (JS/TS)OpenAI AssistantsAnthropic (JS/TS)CohereGroqHugging FacevLLMTogether AIFireworks AIxAI GrokCerebrasNovitaCometAPIBytePlusLangChainLlamaIndexCrewAIAutoGenSemantic KernelHaystackPydantic AIVercel AI SDKSpring AIDSPySmolagentsInstructorOpenAI AgentsLangGraphMastraTemporalAgnoVoltagentStrands AgentsGoogle ADKAmazon Bedrock AgentCoreAmazon Bedrock AgentsBeeAIClaude Agent SDKDeepAgentsLangServeLiteLLMLiveKitLlamaIndex WorkflowsMicrosoft Agent FrameworkMirascopePipecatQuarkus LangChain4jRagasRestateSwiftideKoogLiteLLM ProxyPortkeyOpenRouterKong GatewayVercel AI GatewayAnannasn8nFlowiseLangflowVapiLobeChatCodename GooseOpen WebUIPromptfooReal User Monitoring (RUM)OpenTelemetryCurlElasticSearchPrometheusVectorFluent BitFluentdFilebeatTelegrafKinesis FirehoseSyslogOpenAI (Python)Anthropic (Python)Google GeminiAmazon BedrockMistralOllamaDeepSeekOpenAI (JS/TS)OpenAI AssistantsAnthropic (JS/TS)CohereGroqHugging FacevLLMTogether AIFireworks AIxAI GrokCerebrasNovitaCometAPIBytePlusLangChainLlamaIndexCrewAIAutoGenSemantic KernelHaystackPydantic AIVercel AI SDKSpring AIDSPySmolagentsInstructorOpenAI AgentsLangGraphMastraTemporalAgnoVoltagentStrands AgentsGoogle ADKAmazon Bedrock AgentCoreAmazon Bedrock AgentsBeeAIClaude Agent SDKDeepAgentsLangServeLiteLLMLiveKitLlamaIndex WorkflowsMicrosoft Agent FrameworkMirascopePipecatQuarkus LangChain4jRagasRestateSwiftideKoogLiteLLM ProxyPortkeyOpenRouterKong GatewayVercel AI GatewayAnannasn8nFlowiseLangflowVapiLobeChatCodename GooseOpen WebUIPromptfoo
MilvusPostHogZapierClaude CodeCogneeExaFirecrawlGradioLibreChatMCP UseMixpanelParallelTrubricsCursorOpencodeOpenAI CodexMCP ServerMCP ClaudeLLM ApplicationsAWSAmazon EC2Application Load BalancerAmazon VPC Flow LogsAmazon CognitoAWS Network FirewallAWS CloudWatch LogsAWS CloudWatch MetricsAmazon RDSAWS LambdaAmazon ECSAWS Route 53AWS WAFAWS API GatewayAmazon CloudFrontAmazon EventBridgeGCP LogsGoogle Cloud RunMicrosoft AzureAzure Activity LogsCloudflareVercelHerokuKubernetesLinuxWindowsNGINXIISOracle WebLogicPostgreSQLMySQLOracle DatabaseSQL ServerMongoDBAmazon DynamoDBCassandraAerospikeRedisSnowflakeApache ZooKeeperDatabricksGitHub ActionsJenkinsAnsibleTerraformApache KafkaRabbitMQNATSApache AirflowCriblMuleSoftMicrosoft 365OktaJumpcloudOpenVPNGoogle WorkspaceFalcoOSQueryNetflowSNPMPythonGo.NET TracingNode.js.NET LogsMilvusPostHogZapierClaude CodeCogneeExaFirecrawlGradioLibreChatMCP UseMixpanelParallelTrubricsCursorOpencodeOpenAI CodexMCP ServerMCP ClaudeLLM ApplicationsAWSAmazon EC2Application Load BalancerAmazon VPC Flow LogsAmazon CognitoAWS Network FirewallAWS CloudWatch LogsAWS CloudWatch MetricsAmazon RDSAWS LambdaAmazon ECSAWS Route 53AWS WAFAWS API GatewayAmazon CloudFrontAmazon EventBridgeGCP LogsGoogle Cloud RunMicrosoft AzureAzure Activity LogsCloudflareVercelHerokuKubernetesLinuxWindowsNGINXIISOracle WebLogicPostgreSQLMySQLOracle DatabaseSQL ServerMongoDBAmazon DynamoDBCassandraAerospikeRedisSnowflakeApache ZooKeeperDatabricksGitHub ActionsJenkinsAnsibleTerraformApache KafkaRabbitMQNATSApache AirflowCriblMuleSoftMicrosoft 365OktaJumpcloudOpenVPNGoogle WorkspaceFalcoOSQueryNetflowSNPMPythonGo.NET TracingNode.js.NET Logs
Testimonials

What teams say running OpenObserve

Correlate between the environments and signals across various sources with OpenObserve built-in correlation engine.

Ajith Natarajan

“[OpenObserve is] super fast, definitely very lightweight, and you can get started with an initial POC in two to three minutes to be honest.”

2–3 min

To first POC

Lightweight

Minimal footprint

AI vision

Retail analytics platform

Ajith Natarajan

Ajith Natarajan

Lead Software Engineer, Radius.ai

Ready to get started?

Try OpenObserve today for more efficient and performant observability.

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