Systems | Development | Analytics | API | Testing

Writing maintainable Gherkin test cases requires focusing on behavior over implementation while avoiding common pitfalls that create brittle tests. The difference between a valuable test suite and an expensive maintenance burden often comes down to how you structure your Gherkin scenarios from day one.

November brings expanded on-premise flexibility, deeper analytics customization, and smoother cross-platform automation. TestOps adds on-prem Jira and GitHub integrations, and custom chart creation for faster insights. Studio introduces new MCP Server tools that automate test object management end-to-end. TestCloud simplifies mobile app version handling with dynamic applications and now supports secure live testing on private environments.

Engineering teams want to understand the real health of their applications – not just what was planned or what was tested, but what is actually happening in production. The challenge is that these signals live in different systems, each optimized for a specific part of the delivery lifecycle. Test execution data, issue tracking, and production monitoring each describe a different aspect of system behavior. On their own, they answer narrow questions about validation, delivery, or stability.

Every business running Dynamics 365 Finance and Operations (D365 F&O) relies on the promise of “Evergreen Updates,” which provide seamless, continuous improvement with zero disruption. For a major hospital which was already stretched thin by rising costs and patient loads, the latest update was supposed to be a lifeline, delivering new financial automation features.

In an age where software developers are speeding up their code development to meet the demand of rapid application deployment, there are new tools being developed based on Artificial Intelligence (AI) technology. Replit and Cursor have received a lot of excitement for both of these platforms due to their use of artificial intelligence in assisting developers with coding.

Testing is changing, and AI is leading the next step Every QA team faces the same pressure: test more, deliver faster, and never miss a defect. But as projects grow and release cycles shorten, running every test in every sprint isn’t always realistic. The challenge isn’t just about automating more, it’s about deciding what to test first. That’s where AI comes in.

If your company handles customer payment information, it’s critical for you to understand PCI DSS compliance requirements. A single breach can result in substantial financial penalties and damage your brand's reputation. In my experience working with enterprise customers, I’ve seen firsthand how non-production environments often become a blind spot for compliance efforts.