Set up docs MCPClickHouse offers unmatched speed, scale, and cost-efficiency for observability. This guide provides two paths depending on your needs:
ClickStack - the ClickHouse observability stack
The ClickHouse Observability Stack is our recommended approach for most users.
ClickStack is a production-grade observability platform built on ClickHouse and OpenTelemetry (OTel), unifying logs, traces, metrics and session in a single high-performance scalable solution that works from single-node deployments to multi-petabyte scale.
| Section | Description |
|---|---|
| Overview | Introduction to ClickStack and its key features |
| Getting Started | Quick start guide and basic setup instructions |
| Example Datasets | Sample datasets and use cases |
| Architecture | System architecture and components overview |
| Deployment | Deployment guides and options |
| Configuration | Detailed configuration options and settings |
| Ingesting Data | Guidelines for ingesting data to ClickStack |
| Search | How to search and query your observability data |
| Production | Best practices for production deployment |
Build-your-own stack
For users with custom requirements — such as highly specialized ingestion pipelines, schema designs, or extreme scaling needs — we provide guidance to build a custom observability stack with ClickHouse as the core database.
| Page | Description |
|---|---|
| Introduction | This guide is designed for if you’re looking to build your own observability solution using ClickHouse, focusing on logs and traces. |
| Schema design | Learn why users are recommended to create their own schema for logs and traces, along with some best practices for doing so. |
| Managing data | Deployments of ClickHouse for observability invariably involve large datasets, which need to be managed. ClickHouse offers features to assist with data management. |
| Integrating OpenTelemetry | Collecting and exporting logs and traces using OpenTelemetry with ClickHouse. |
| Using Visualization Tools | Learn how to use observability visualization tools for ClickHouse, including HyperDX and Grafana. |
| Demo Application | Explore the OpenTelemetry demo application forked to work with ClickHouse for logs and traces. |
Prometheus metrics
Not supported in ClickHouse CloudClickHouse can store Prometheus metrics in a TimeSeries table and evaluate PromQL queries. See Prometheus protocols and PromQL for ingestion, query, and visualization configuration.