Configure Grafana Tempo deployments for tracing scalability and cost-efficiency.
npx skills add https://github.com/julianobarbosa/claude-code-skills --skill tempo
Please help me install this Agent Skill. Skill: tempo Source: https://github.com/julianobarbosa/claude-code-skills/tree/main/skills/tempo Command: npx skills add https://github.com/julianobarbosa/claude-code-skills --skill tempo
This Skill covers Grafana Tempo - a high-scale, multi-tenant tracing backend designed for OpenTelemetry, enabling efficient trace storage and TraceQL querying.
Install Tempo with the distributed Helm chart and point to an object store; run a basic TraceQL query to locate traces by duration.
High-intent search queries and answers about installing and using this skill.
Grafana Tempo is a high-scale, multi-tenant tracing backend for OpenTelemetry. Deploy it on Kubernetes using the distributed Helm chart, configure an object store (S3, GCS, or Azure Blob) for Parquet-based trace storage, and point your OpenTelemetry collectors to Tempo's OTLP endpoint.
Yes. TraceQL enables powerful trace-based queries with strong performance. Write queries to locate traces by duration, span attributes, or service names, then retrieve results from your object store backend.
Yes. Tempo provides built-in multi-tenant isolation using X-Scope-OrgID headers, allowing you to isolate traces and queries by tenant within a single deployment on Kubernetes.
Tempo stores traces in Parquet format across S3, Google Cloud Storage, or Azure Blob Storage, reducing storage costs while maintaining query performance on large-scale trace datasets.
Use the distributed Helm chart to deploy Tempo on Kubernetes. Configure the chart to point to your chosen object store backend—S3 for AWS, GCS for Google Cloud, or Azure Blob for Microsoft Azure—enabling multi-cloud flexibility.
Use TraceQL queries to verify trace ingestion and storage, inspect Parquet blocks in your object store, check OTLP endpoint connectivity, and validate multi-tenant X-Scope-OrgID configuration across your Kubernetes deployment.
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