The Future of Testing: AI-Driven Quality Engineering Practices
About Topic
In the rapidly evolving landscape of software testing, innovative AI-powered observability platforms are transforming quality engineering practices by automatically detecting patterns and predicting potential issues across complex microservices architectures. Niranjani Manoharan, Engineering Manager at Amazon will show you how combining serverless functions with machine learning creates an intelligent test failure analysis pipeline that reduces mean time to resolution by 60% and infrastructure costs by 40%. This crash course in AI-powered quality engineering will equip you with practical knowledge to implement similar solutions in your own testing environments. Her top tips to revolutionize your testing practices include leveraging custom ML models, building efficient data pipelines, and implementing continuous model training and validation for maximum effectiveness.
Key Takeaways
1. Innovation creates noise, making obvious truths harder to see.
2. Question if a problem really needs GenAI or if existing tools suffice.
3. Understand GenAI’s true value beyond the hype.
4. Old and new solutions should complement, not replace, each other.
5. A real-world case study shows how GenAI can be used effectively.
6. Clarity comes from cutting through illusions and embracing simplicity.
About Speaker
An accomplished software engineering leader in building tools, test infrastructure and improving quality and developer productivity for industry pioneers like Lyft, Pinterest, eBay, Twitter and now at Amazon. She holds a Masters in software engineering from San Jose State University and has been working in the Silicon Valley navigating between startups and tech giants.
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