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JaiminVadadoriya
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observability-driven-testing

Create and validate tests using production traces, logs, and metrics.

1|Updated Feb 18, 2026
Search Tags:#testing#observability#test coverage#telemetry#OpenTelemetry
One-click install
npx skills add https://github.com/JaiminVadadoriya/Distributed-Cloud-Storage---Sync-Platform --skill observability-driven-testing-jaiminvadadoriya
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: observability-driven-testing
Source: https://github.com/JaiminVadadoriya/Distributed-Cloud-Storage---Sync-Platform/tree/main/.agents/skills/observability-driven-testing
Command: npx skills add https://github.com/JaiminVadadoriya/Distributed-Cloud-Storage---Sync-Platform --skill observability-driven-testing-jaiminvadadoriya

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires @opentelemetry/tracing, sentry, bugsnag, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill addresses the challenge of insufficient test coverage in software development by leveraging production insights and observability data to guide and improve testing efforts.

Core Features & Use Cases

  • Production-Informed Testing: Uses real production data, including error logs, traces, and metrics, to inform test creation and prioritize testing efforts.
  • Trace-Based Assertions: Enables tests to verify the correctness of the application's behavior at every layer using traces.
  • Log-Informed Test Design: Analyzes production error logs to identify test gaps and suggests improvements.
  • Telemetry-Driven Prioritization: Prioritizes tests based on real usage data and error rates to focus on the most critical code paths.
  • Error Analysis Pipeline: Converts production errors into actionable tests to prevent recurrence.

Quick Start

Integrate the observability-driven-testing skill into your QA pipeline by following the steps outlined in the provided documentation.

Frequently Asked Questions about observability-driven-testing

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

FAQPage Schema
How can I use production observability data to improve test coverage?▼

Production observability data improves test coverage by analyzing real traces, logs, and metrics to identify untested code paths. This approach uses telemetry to prioritize tests based on actual usage patterns and error rates, focusing validation on critical application behaviors.

How do I create trace-based assertions for microservices testing?▼

Trace-based assertions verify application behavior across every layer by leveraging OpenTelemetry tracing data. This allows tests to validate the correctness of distributed microservices transactions and ensure that execution paths match expected production behaviors.

Can I convert production error logs into automated tests?▼

You can convert production error logs into automated tests through an error analysis pipeline. By examining log data from tracking tools like Sentry or Bugsnag, you can identify test gaps and generate actionable tests to prevent error recurrence.

Do I need OpenTelemetry to implement telemetry-driven test prioritization?▼

Yes, telemetry-driven test prioritization requires OpenTelemetry to gather the necessary traces and metrics. It also depends on error tracking tools like Sentry or Bugsnag to analyze production error logs and convert them into informed test cases.

What is the best way to find untested code paths in a microservices architecture?▼

Finding untested code paths in microservices is best achieved by analyzing production observability data. Using telemetry and trace-based testing reveals real execution flows, highlighting critical areas missed by traditional code coverage tools.

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