Proactive Observability in Testing with Anam Hira

Proactive Observability in Testing with Anam Hira

In today's episode, we're diving into proactive observability and testing with our special guest, Anam Hira, cofounder of Reveal.ai. Anam, who also has experience working at Uber AI, shares an intriguing journey where he developed "Dragon Crawl," an innovative project aimed at tackling challenges Uber faced with its end-to-end testing across multiple cities.

We explore how Dragon Crawl utilized LLMs to enhance testing reliability, making tests less flaky across varied UIs.

Anam's journey didn't stop there. He co-founded Reveal, a platform that takes testing and observability to a new level by connecting end-to-end tests with telemetry data. This modern approach, termed proactive observability, allows for detecting bugs before they hit production, saving companies significant time and cost.

Join us as we explore the principles of proactive observability, how Reveal leverages telemetry for seamless integration, and its impact on testing efficiency. Whether you're a startup or an enterprise, if you're keen to ship faster without sacrificing quality, this is an episode you won't want to miss!

👉 Start building accessible apps with BrowserStack: https://testguild.me/accessiblity

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7 Heinä 43min

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Most API testing stops at the happy path. The problem is that the bugs that actually hurt you in production are sitting in everything many testers skip, like the boundary values, the oversized payload...

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Your AI code review tools read the diff. They stare at your code. But they never actually run it. So the bugs that only show up at runtime, the broken user flows, the bad query plan, the duplicate sub...

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