Systems | Development | Analytics | API | Testing

API Gateway vs. AI Gateway: The Definitive Guide to Modern AI Infrastructure

Traditional API Gateways: Excellent for routing, auth, and microservice traffic; poor at AI workloads. Limitations: Can't track tokens, manage streaming responses, enforce content-level security, or use semantic caching. AI Gateways Purpose-built for LLMs with: Architecture Recommendation: Layered approach: Benefits: Lower costs (20--40%), better performance, centralized governance, future-proof AI infrastructure. Market Context.

High user satisfaction scores aren't worth a burned-out team

Multiplayer transforms the chaos of support tickets, eliminating manual work, sloppy hand-offs, and grepping through log files. End-user support has always been messy. Manual steps, tool-switching, and scattered communication turn what should be a simple fix into a marathon of frustration. Tickets feel like scavenger hunts: everyone’s searching for details, logs, screenshots, or that missing repro step. Developers are left waiting on context that never arrives.

Performance Testing and Artificial Intelligence (2/2)

If you recall part one of this blog post, we were going to use ChatGPT in parallel with how we would work to cover these aspects of performance testing. We left the first part of this blog post at the point at which we had compared Requirements Gathering and Risk Assessment, we will pick this post up by looking at Script Creation before concluding with Results Analysis. Our performance testing tool of choice will be JMeter.

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.

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.

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?

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.

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.