tempo

Name: tempo
Availability: InStock
Author: n4vysh

Store and query distributed traces with OTLP, Jaeger, and Zipkin ingestion.

5|Updated Apr 29, 2023

Search Tags:#kubernetes #observability #tracing #traceql #distributed-tracing #tempo #otlp

Ready to run

npx skills add https://github.com/n4vysh/dotfiles --skill tempo-n4vysh

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: tempo
Source: https://github.com/n4vysh/dotfiles/tree/main/home/dot_agents/skills/tempo
Command: npx skills add https://github.com/n4vysh/dotfiles --skill tempo-n4vysh

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Tempo provides a scalable, cost-efficient backend to store and query distributed traces, enabling efficient trace exploration and integration with Grafana.

Core Features & Use Cases

TraceQL language reference, configuration reference, and architecture overview for end-to-end tracing workflows
Ingestion support (OTLP/ Jaeger / Zipkin), multi-tenancy, and deployment options (monolithic, microservices, Helm/Kubernetes)
Metrics and service graphs derived from traces, tracing pipelines, and Grafana integration

Quick Start

Install Tempo locally and start a minimal single-node config to begin sending traces via OTLP.

Frequently Asked Questions about tempo

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I store and query distributed traces at scale on Kubernetes?▼

Tempo provides a scalable, cost-efficient backend to store and query distributed traces at scale on Kubernetes, supporting microservices deployment patterns via Helm and ingesting traces through OTLP, Jaeger, or Zipkin protocols for querying with TraceQL.

Can I ingest Jaeger and Zipkin traces into a Tempo backend?▼

Yes, Tempo supports ingestion from multiple tracing formats including Jaeger and Zipkin, allowing you to consolidate distributed trace data from different instrumentation libraries into a single backend for unified querying.

How do I query distributed traces using TraceQL?▼

You query distributed traces using TraceQL by writing structured queries against your ingested trace data, enabling you to filter, explore, and derive metrics from traces stored in the Tempo backend.

Does Tempo support multi-tenancy for distributed tracing pipelines?▼

Yes, Tempo supports multi-tenancy for distributed tracing pipelines, allowing multiple teams or customers to share a single Tempo backend while maintaining isolated trace data access and query boundaries.

How do I deploy Tempo in a microservices architecture?▼

You can deploy Tempo in a microservices architecture using Helm on Kubernetes, configuring separate components for ingestion, storage, and querying to scale your distributed tracing backend horizontally across your cluster nodes.