Transparency Through Peer Review in the SDLC - Webinar and Live Demo

Artificial Intelligence (AI) isn't just a buzzword - businesses across all industries are leveraging the technology today to solve a wide range of problems. Even test automation tools are benefiting from AI, from AI-powered visual recognition and intelligent test recommendations, to risk profiling and bug hunting. At every step in the QA cycle, we see AI infusing itself to accelerate test creation, maintenance and execution.

Szilard Szell, DevOps and Test Automation Expert, is sharing how to excel in exploratory testing and make bug hunting events a crucial part of the team life and where this concept fits into Scaled Agile Framework and DevOps. Watch the interview with Szilard and share your experience after doing bug hunting in comments.

API consumers have high expectations and API providers know they need to standardize their services to provide the best possible developer experience.

Nowadays performance is everything. It only takes one second of lag time to lose 7% of the conversions you would have had if your performance met the standards of your users. So how can agile teams keep up with their continuous delivery cycles and ensure they execute all the necessary performance tests? One way to do this is to integrate performance testing into your CI/CD pipeline.

Performance testing is critical if you want to scale web applications. Poor performance is a major reasons why digital companies lose users, which is why it’s imperative to ensure your application infrastructure is able to handle the anticipated load without compromising on your end user experience.