The Fifth Elephant
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The Fifth Elephant Pune edition

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Ameya Natu

@ameyanatu

From Postman Collections to Production-Ready Load Tests in Minutes: AI-Powered Performance Testing for Modern QA Teams

Submitted Dec 16, 2025

Indicate the track in which your submission fits: Track 1 AI in Software Development Life Cycle (SDLC) Type of submission: 15 mins talk

Session Description

Let’s face it — every QA team has a bunch of well-crafted Postman collections that handle all their functional testing magic. But when the word performance testing drops in a meeting, everyone suddenly pretends to check Slack. Why? Because load testing usually means extra tools, extra time, and extra brainpower.

This session is all about changing that. We’ll show how you can convert your existing Postman collections into shiny, production-ready k6 load tests—automatically, intelligently, and with a little help from AI. This isn’t just a converter; it’s like giving your APIs a gym trainer. AI doesn’t just generate tests—it studies your endpoints, figures out smart load profiles, ramp-up patterns, even suggests thresholds, and tunes parameters based on your endpoint’s business importance (think: payment APIs get more muscle than your analytics endpoints).

During the live demo, we’ll walk through how this setup plugs right into your CI/CD (GitHub Actions or GitLab CI) without touching a single line of code. You’ll see AI reviewing your test runs like an intelligent teammate who actually enjoys metrics—spotting bottlenecks, flagging anomalies, and giving you roasted-but-helpful feedback on what to optimize next.

By the end, you’ll probably ask yourself: Why didn’t we do this earlier?

Key Takeaways

Bridge the Gap (Without Extra Work): Reuse Postman collections for realistic load testing—no rewriting, no new tools, and definitely no performance PhD required.

AI-Powered Brains: Learn how AI can craft intelligent load patterns, tweak VU counts, and even summarize performance results like a pro.

Business-Aware Testing: Discover how optional API metadata (like domain, criticality, and expected traffic) helps AI create smart, contextual threshold profiles that match real-world usage.

Target Audience

This talk is for everyone who secretly wants performance testing to be easier (and smarter):

QA engineers who’ve got great Postman collections but haven’t had time to go "k6.”

DevOps folks who prefer automating things instead of manually tuning test configs.

Performance testers curious about AI taking on their analysis headache.

Engineering managers who want to add performance testing maturity to their team without adding another full-time expert to the payroll.

Speaker Bio
Ameya Natu is a Senior SDET at ClearRoute, specializing in automation, performance engineering, and creative tool-building to make testing less painful and more powerful. With over 12+ years in QA and DevOps integration, he’s been on a mission to shrink the gap between “it works” and “it scales.”

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