Enterprises today are working hard to advance their DevOps processes and implement continuous testing that can scale across digital channels, yet many find themselves overwhelmed by data and frustrated by too many failed tests.
The reality is that continuous automated testing generates a ton of data and a lot of noise in the form of false negatives and flakiness. Unless you can reduce the noise, analyze the data quickly and pinpoint the real issues, what’s the benefit of automation?
In this live web seminar, Tzvika Shahaf, Director of Product Management at Perfecto, will share a new approach to continuous testing that leverages advanced ML/AI capabilities to not just automate test suites, but to make them smarter.
Watch this webinar and learn:
- Common failures, pitfalls and bottlenecks in CT
- How ML/AI can improve test stabilization and analysis
- New methods for noise reduction and failure classification