This is documentation for the next version of Grafana Tempo documentation. For the latest stable release, go to the latest version.

Plan your deployment

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Plan your Tempo deployment

Before you deploy Tempo, you should consider how you plan to use traces and Tempo as well as any special requirements for Tempo 3.0.

Considerations for Tempo 3.0

Before planning your Tempo deployment, be aware that Tempo v3.0 requires:

Kafka-compatible system: Tempo requires a Kafka-compatible system (such as Apache Kafka, Redpanda, or WarpStream) for both monolithic and microservices modes. Kafka serves as the durable write-ahead log that decouples write and read paths.
Object storage: Tempo stores trace data in object storage (S3, GCS, or Azure Storage).

Include these infrastructure components in your deployment planning and resource estimation.

To plan your Grafana Tempo deployment, you should:

Identify your use case Decide what you need from Tempo. For example, consider if you want a basic installation, horizontal scalability, multi-tenancy, or advanced data storage. Your use case determines the deployment architecture and resource requirements.
Estimate tracing data volume Assess the amount of tracing data your environment will generate. This helps you size your cluster and storage. Refer to the Size your cluster section for guidance on calculating storage and performance needs.
Choose a deployment mode. Tempo supports monolithic and microservices deployment modes.
- Use the monolithic mode for simple, single-tenant environments or smaller workloads.
- Use the microservices mode for large-scale, multi-tenant, or highly available deployments. Review the Deployment modes documentation to compare options and select the best fit for your use case.

By following these recommendations, you can plan a Tempo deployment that matches your operational requirements and scales with your tracing data.