# Monitor every layer you run, without a tool for each one

> Monitoring solutions for Kubernetes, AWS, Azure, GCP, databases, applications, networks, and AI workloads, unified in one open-source observability tool.

Source: https://openobserve.ai/solutions/

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Kubernetes, AWS, Azure, GCP, databases, applications, networks and AI agents, each with its own turnkey setup, all landing in one Rust-built engine, correlated on a single timeline and billed per GB ingested.

## Start where your workloads run

Eight turnkey solutions, each with its own setup path, prebuilt dashboards and alerts. Adopt one today; the others are already in the same deployment when you need them.

### Kubernetes Monitoring

Complete Kubernetes visibility, from cluster to pod, in minutes. One install brings container logs, cluster events, metrics and zero-code traces.

- Unified Kubernetes monitoring
- Multi-cluster visibility
- Resource optimization
- Uptime & incident management

[Learn more](/kubernetes-monitoring/)

### AWS Monitoring

Comprehensive visibility into your AWS infrastructure performance, health and resource utilization, with one CloudFormation stack for every service you select.

- Real-time visibility & insights
- Efficient data processing
- Service coverage & integration
- Cost-effective monitoring

[Learn more](/aws-monitoring/)

### Azure Monitoring

Comprehensive visibility into your Azure infrastructure performance, health and resource utilization, with Activity and diagnostic logs routed through Event Hub.

- Automated Azure setup
- Unified log routing
- Cost-predictable ingestion
- SQL and PromQL querying

[Learn more](/azure-monitoring/)

### GCP Monitoring

Comprehensive visibility into your Google Cloud estate (Compute Engine, Cloud Run, Cloud Functions and Cloud SQL), exported agentlessly through Cloud Logging.

- Data collection and analysis
- Service monitoring
- Log processing
- Resource management

[Learn more](/gcp-monitoring/)

### Application Monitoring

Point any OpenTelemetry exporter at OpenObserve, over HTTP or gRPC. Your instrumentation stays vendor-neutral, and logs, metrics and traces share one resource model.

- Vendor-neutral instrumentation
- Unified correlation
- Open standards
- Low switching cost

[Learn more](/application-monitoring/)

### Database Monitoring

Optimize database operations with real-time insights that reduce costs and ensure peak performance, across every engine you run, in a single pane.

- Performance monitoring
- Proactive error detection & resolution
- Data-driven decisions
- Holistic monitoring & alerts

[Learn more](/database-monitoring/)

### Network Monitoring

Unify NetFlow, IPFIX, sFlow, VPC Flow Logs and SNMP with the rest of your stack's metrics, logs and traces, in the same backend you already query.

- Flow level traffic analysis
- Cloud and VPC flow visibility
- Device and interface monitoring
- Topology, alerts and incidents

[Learn more](/network-monitoring/)

### AI & LLM Monitoring

Trace every agent, tool call and model request, and attribute cost to the token, in the same platform that runs the rest of your stack. Priced per GB, not per span.

- Trace & map agents
- Debug sessions end-to-end
- Evaluate in production
- Deploy anywhere

[Learn more](/ai-llm-monitoring/)

- [Not listed? Browse every OpenTelemetry-native integration](/integrations/)

## Adopt one. The rest is already there.

Every solution above is the same Rust-built engine, with the same query layer, the same dashboards and the same bill. Adding the next layer of your stack is a new data source, not a new tool, a new contract or a new team to train.

### Launch in minutes, not weeks

Spin up observability instantly without complex setups or manual configuration. Each solution ships with its own install path and prebuilt dashboards.

### Cut observability costs

Reduce telemetry storage spend using OpenObserve's ultra-efficient compression and smart retention, for up to 140x lower storage cost than index-heavy tools.

### Consolidate for clarity

Correlate metrics, logs and traces from every layer in a single platform, so root cause analysis crosses the cloud, cluster, database and network in one query.

- [See the platform](/platform/)

## Frequently asked questions

Which OpenObserve solution fits your stack, and how they fit together.

### Which OpenObserve solution fits my stack?

Start from where your workloads run. Kubernetes monitoring covers clusters, pods, and events; AWS, Azure, and GCP monitoring pull in cloud-native services; database monitoring and application monitoring cover the data and service layers; network monitoring handles flows and devices; and AI & LLM monitoring traces agents and LLM calls. All of them land in the same platform, so you can adopt one and expand later.

### Do I need separate tools for logs, metrics, and traces?

No. Every solution ingests logs, metrics, and traces into one OpenObserve deployment with one query layer (SQL and PromQL), one set of dashboards, and one alerting engine. There is no separate stack per signal to run or pay for.

### Can I run these solutions self-hosted?

Yes. Every solution works on OpenObserve Cloud or on the self-hosted editions, including the Self-Hosted Enterprise plan that is free up to 50 GB/day. Data stays in your own object storage (S3, GCS, Azure Blob, or MinIO).

### How do these compare to Datadog or Grafana solutions?

Datadog offers similar coverage but bills per host, per custom metric, and per user; Grafana requires assembling Loki, Mimir, and Tempo. OpenObserve delivers the same coverage from a single open-source binary priced per GB ingested. See the comparison hub for vendor-by-vendor detail.

## Ready to get started?

Try OpenObserve today for more efficient and performant observability.

- Get Started For Free
- [Schedule Demo](/demo/)