Systems | Development | Analytics | API | Testing

For years, APIs have been designed with one primary audience in mind: developers. The focus has been on making APIs discoverable, consistent, and easy for humans to consume. But in the AI era, a new audience has arrived: AI agents. As detailed in SmartBear’s newly published AI-Enabled API Lifecycle Report, this shift demands that organizations rethink how APIs are designed, tested, and managed to serve both human developers and intelligent systems effectively.

As coding has become more autonomous, so has code-based testing. AI agents can now write functions, generate code-based tests, and validate logic in the same workflow. But the other half of the testing equation, the system-level validation of non-code-based testing, hasn’t kept up. That disconnect is becoming one of the most critical constraints in modern software delivery.

API gateways connect on-premises systems with cloud applications, managing tasks like authentication, traffic routing, and monitoring. Key Benefits: Centralized security to protect sensitive data. Reduced latency by processing requests closer to the data source. Simplified compliance for regulations like HIPAA and GDPR. Scalability and failover support for uninterrupted service. Setup Essentials: Secure connectivity using VPNs or dedicated links.

The updates we make to Perforce ALM are deeply influenced by the real-world challenges our users face. We understand that those who work in highly regulated industries need trustworthy tools that deliver precision, traceability, and efficiency. That’s why we plan each round of ALM enhancements based directly on user comments and suggestions. This quick guide will look at recent updates around tagging and filtering and how to leverage these features for a more intuitive and efficient user experience.

Most finance leaders are curious about AI—but hesitant to adopt it. The concern makes sense: what happens if automated systems pull the wrong data or miss critical details? Yet finance teams need some help. Teams are stretched thin. Reporting cycles are taking too long. When they’re relying on manual processes, they can’t keep pace with growth. Sound familiar? On a recent episode of the podcast “Don’t Panic!

Do you know where your data is? The number of people who can pat their server and say fondly, “Right here!” is decreasing. Instead, more people are lifting their eyes to the heavens and answering, “Um… up there… somewhere…” McKinsey reports that in 2025, large enterprises have 60% of their environment in the cloud. If you’re considering moving your data assets, processes, and applications to the cloud, you’re in good company.

Mobile crash reporting keeps apps reliable at scale, helping developers root out the cause of problems and prevent them recurring. In this guide, we compare the top mobile crash reporting tools for 2025, including Android-friendly and cross-platform options, to help you choose the right fit for your workflow. You’ll find: This guide focuses on what truly matters for real development teams, not just feature lists. And yep, we’re slightly biased, as one of the solutions is our own.

Hi everyone, I’m Elly, Katalon Community Specialist by title, tester at heart. I spend a good chunk of my time researching around the Katalon Forum reading bug reports, answering questions, and watching how this brilliant community solves problems together. Over the past month, I’ve been tracking what everyone’s been talking about: the tricky bugs, the clever fixes, and the shout-worthy contributions. This post is my way of sharing that back with all of you.

What if a single, untriggered logical flaw could compromise an autonomous vehicle’s braking system or ground a commercial airliner? The stakes are unbelievably high with safety-critical software. Traditional code coverage metrics, however, often fail to test the subtle, complex dependencies within a single decision. Knowing that a line of code executed isn’t the same as knowing the logic works.

Enterprise integration has shifted from simple data connections to AI-driven ecosystems that manage, analyze, and optimize workflows in real time. Here's what you need to know: APIs are the backbone of modern businesses, linking systems like CRMs, ERPs, and analytics tools. They eliminate manual data entry, reduce errors, and support microservices architectures. AI systems are the next step, addressing the complexity of managing hundreds of APIs.