Systems | Development | Analytics | API | Testing

These days, in the quickly evolving world of software, just executing automated testing is not sufficient. Real quality only results from what follows results analysis, pattern tracking, and insights from failure.Test reporting and analytics come into their own here. By converting raw test data into valuable insights, teams can catch flaky tests, pinpoint common problems, and make better decisions more quickly.

When I started at Speedscale, I looked like this: And after one year of learning, growing, and keeping pace with innovation well, let’s just say the journey has left its mark: Of course, I’m joking (sort of). The truth is, this past year has been intense, energizing, and filled with new challenges. If anything, it’s made me feel younger in spirit, even if the mirror might disagree some mornings.

When AI projects derail, it’s rarely because the model was weak. More often, failure comes from using MCP in the wrong way—forcing it to act as a universal API, data pipeline, or real-time engine instead of what it truly is: an orchestration and intelligence layer. Recently, Nate B.

In January this year, financial institutions across the EU were faced with a clear mandate – the Digital Operational Resilience Act (DORA): to ensure digital resilience, maintain service continuity and strengthen oversight of Information and Communication Technology (ICT) partners.

Databases are the spine of most any app we use today, from a banking app to an online shopping site. Good application is hidden under cover of the user interface, in the basement, in the room where the data is stored, processed and fetched. Database testing is vital for that very reason. It makes data accurate, secure and trustworthy, which in turn keeps apps stable and businesses running smoothly.

API gateways are often viewed as the centralized entry point for client HTTP requests in a distributed system. They act as intermediaries between clients and backend services, managing API request routing, load balancing, rate limiting, access control, and traffic shaping across multiple backend services. This API management is vital for many services and products, but many organizations can put too much stock in it.

Over the weekend, I was looking to book flights for holidays. All excited, I was able to find a decent price for my family to head for some sunshine later this summer. I reached the payment stage, and that’s where the excitement and smile stopped. I was waiting for confirmation that my payment was finalizing, but then the system took a turn, and I was back on the booking page. Even more, I now had a higher price to pay for the flights. Did I continue with booking, NOOOOOO.

The shift is already happening. Over the past few years, you’ve invested resources in optimizing your APIs for human developers. Meanwhile, a new class of customers has quietly emerged – one that never takes coffee breaks, never sleeps, and processes information at superhuman speeds. AI agents are rapidly becoming the primary consumers of APIs, and this fundamental change demands a complete rethinking of how we design, deploy, and maintain our digital interfaces.