Systems | Development | Analytics | API | Testing

Performance Testing and Artificial Intelligence (1/2)

If you believe many articles online you would believe that automation in testing will soon be defined, managed and executed by Artificial Intelligence (AI). AI is embedded in many organisations technology landscape and to think that this model will change is shortsighted. AI is here to stay undoubtedly in one form or another, but should it be responsible for the automated testing of your applications under test?

Part 2: Building a Production-Grade Traffic Capture, Transform and Replay System

When developers try to build realistic mocks and automated tests from production network traffic, the real challenge isn’t just in the capturing—it’s in the data manipulation. Raw traffic is a chaotic sea of patterns, dynamic tokens, environment-specific secrets, and tangled dependencies that seem impossible to untangle by hand. Over my two decades of building these sytems, I learned that solving this problem requires more than brute-force parsing or ad hoc scripts.

Node.js 24 Becomes LTS: What You Need to Know

With the release of Node.js 24.11.0 “Krypton”, the Node.js 24 line has officially entered Long-Term Support (LTS) and will continue receiving maintenance and security updates through April 2028. This marks the beginning of a new stable era for production workloads, bringing developers enhanced security, stricter runtime behavior, and improved Web API support.

A CFO's Guide to Test Automation: 5 Metrics That Matter

Test automation has evolved far beyond QA. Today, it plays a direct role in product speed, developer efficiency, and even customer retention. That means one thing: it’s no longer just a technical investment. It’s a financial decision. If you’re a CFO, you’ve likely seen test automation mentioned in strategy decks or budget line items. But what does the return really look like?

What Is Monkey Testing In Software Testing? Types, Tools & More

What happens when an inquisitive, unpredictable user, without manual or training, just begins clicking and typing in your application? Will everything handle the unpredictability gracefully or crash prematurely? This chaotic scene is not hypothetical in the field of Quality Assurance (QA); it is actually an established testing technique called Monkey Testing. While structured testing is important, it often ignores the unstructured actions of actual users.

What is Exposure Management? Explained for Vulnerability Management Teams

If you're a vulnerability management professional or have experience leading teams that do vulnerability management, you know CVEs inside and out. You've got your scanning tools configured, your patch cycles running, and your CVSS score thresholds set. But lately, something probably feels off. Maybe it's the fact that breaches keep happening despite all the patching. Maybe it's that your CVE count keeps growing faster than you can remediate. Or maybe you're just tired of explaining why that "critical" vulnerability in a disconnected test server isn't actually critical.

Ensuring ethical AI use in QA: guidelines for responsible testing

Artificial Intelligence (AI) is reshaping Quality Assurance (QA) by accelerating testing, improving accuracy, and uncovering insights that once required hours of manual analysis. Yet, with great capability comes great responsibility. As AI begins to influence how tests are designed, executed, and interpreted, ensuring that it’s used ethically has never been more important. Responsible AI in QA isn’t only about compliance — it’s about trust.