trycatchkamal

trycatchkamal / gauzer

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The observability-first validation library for Go. Drop-in struct tags, ~61ns zero-alloc performance, and native slog/OTel telemetry on every failure.

go go-lib go-library golang golang-library
12
0
100% credibility
Found Apr 04, 2026 at 12 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Go
AI Summary

Gauzer helps app builders validate user data and create detailed, searchable error reports that work seamlessly with common logging systems.

How It Works

1
🔍 Discover Gauzer

You hear about a helpful tool that turns confusing error messages into clear, easy-to-search details when checking user data in your app.

2
📦 Add it easily

You bring the tool into your project in moments, ready to make your data checks smarter.

3
✏️ Set simple rules

You add friendly notes to your data fields, like 'name must be at least 3 letters' or 'age over 18', so the tool knows what to watch for.

4
✅ Check your data

As users send info to your app, you run a quick check to spot anything off.

5
🚨 Spot issues clearly

If something's wrong, you instantly see exactly which part failed, the rule it broke, and the bad value— all neatly organized.

6
📊 Search and analyze

Your logs now let you filter errors by field or rule, spotting patterns like 'too many young users' without hassle.

🎉 Team loves it

Your on-call shifts get easier, fixes happen faster, and everyone celebrates reliable, insightful error tracking.

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Star Growth

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AI-Generated Review

What is gauzer?

Gauzer is an observability-first validation library for Go that uses drop-in struct tags to check fields like email, min length, or oneof options. Instead of flat error strings, every failure emits a structured event with field, constraint, value, and type—landing natively in slog or OTel for querying in Datadog or CloudWatch. Go teams get ~61ns zero-alloc performance on valid inputs, with telemetry only on the sad path.

Why is it gaining traction?

It stands out with zero-friction migration—just swap "validate" tags to "gauzer"—while solving the SRE nightmare of parsing log strings for failure patterns like "age gte:18 with value 16". Native slog/OTel integration means structured events query by err.field or err.constraint without regex hacks, plus PII masking and cross-field checks like eqfield. Gauzer reviews highlight its gauzer energy for production observability over raw performance alone.

Who should use this?

Backend Go devs building API handlers that decode JSON requests into structs, especially in microservices with slog logging or OTel tracing. SREs on-call for high-volume forms (user signups, payments) who need to alert on failure spikes. Teams migrating from go-playground/validator wanting telemetry without custom emitters.

Verdict

Try Gauzer if observability trumps everything—its docs, benchmarks, and audit tests show polish beyond the 12 stars and 1.0% credibility score. Still early (v0.1), so watch for roadmap items like nested dive and CloudWatch adapters before prime time.

(198 words)

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