alibaba

alibaba / obz-cli

Public

Multi-backend observability CLI for metrics, logs, and traces — unified interface, AI-Agent friendly

ai-agent cli logs metrics observability
12
1
100% credibility
Found Apr 30, 2026 at 12 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Rust
AI Summary

obz is a command-line tool providing a unified way to query metrics, logs, and traces across multiple observability backends.

How It Works

1
🔍 Discover obz

You hear about a simple tool that lets you check your app's health data from anywhere without switching programs.

2
📥 Get obz

Download and set it up on your computer with one quick action.

3
🔗 Connect your data

Point it to where your monitoring info lives, like your logs or performance numbers.

4
✨ Ask about your app

Type a natural question like 'show errors from the last hour' and get clear answers instantly.

5
📊 See your results

View neat tables or lists of exactly what you need, easy to read and share.

✅ Stay on top effortlessly

Now you always know how your app is doing, no hassle, from any service.

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Star Growth

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AI-Generated Review

What is obz-cli?

obz-cli is a Rust-built CLI delivering a unified interface for querying metrics, logs, and traces across 10+ observability backends like Prometheus, Loki, Jaeger, VictoriaMetrics, and Datadog. It tackles scattered data silos by standardizing commands—`obz metric query -p prom -q 'up'`, `obz log search -p loki -q '{job="varlogs"}'`, or `obz trace search -p tempo 'frontend'`—with structured JSON output, config-driven endpoints, and native query passthrough. Users get predictable responses that are ai-agent friendly, complete with skill docs and projection flags to trim token use.

Why is it gaining traction?

The multi-backend coverage and agent-first hooks like deterministic errors, built-in provider skills, and `--fields` truncation make obz clicks for automation without custom parsers. Unlike siloed CLIs, it unifies observability workflows via one tool, with config.yaml handling creds across clouds. Extensibility via provider traits keeps it future-proof as backends evolve.

Who should use this?

DevOps engineers juggling Prometheus, Loki, and Jaeger in hybrid stacks, tired of context-switching CLIs. SREs scripting alerts or dashboards across self-hosted and SaaS tools like Datadog or Alibaba SLS. AI agent developers needing reliable, structured observability data pulls.

Verdict

Promising for multi-backend observability but immature at 12 stars and 1.0% credibility—docs are strong, install is curl-simple, yet low adoption signals caution. Try it if you query diverse stacks; semantic querying roadmap could boost it.

(198 words)

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