Systems | Development | Analytics | API | Testing

From Hospitals to Home Care: Digital Innovations in Healthcare

What exactly comes to your mind when we say ‘Digital Advancements’? What’s the first thing you think of when you hear the word? Is it cloud technology? Digital transformation? Gen-AI? Blockchain? Or everything that caters to Digital Transformation as a whole? We know that the last sentence is the one you’ll prefer. But has it ever come across your mind why digital transformation solutions are taking all the limelight from different industries?

Confluent Intelligence expands real-time business data to enterprise AI

Support for the Agent2Agent protocol helps connect AI agents anywhere in real time so they can collaborate at enterprise scale. Multivariate Anomaly Detection takes anomaly detection to the next level, stopping problems before they start.

Top Test Automation Best Practices Every Team Should Follow

Test automation has become an essential part of modern software development. In 2026, shipping fast without reliable test automation is almost impossible. Done right, it ensures consistent quality, faster feedback, and fewer production incidents. This guide covers practical test automation best practices used by real engineering teams to deliver measurable results.

Reflect vision-based AI demo | Create one test for multiple platforms

Create a single mobile test that runs reliably on both iOS and Android - without building separate tests per platform or relying on brittle, platform-specific locators. In this high-level demo, we use SmartBear Reflect’s vision-based AI to record a typical workflow in a sample coffee app, where each step is backed by visual context and intent. Then we run the same test across a mix of Apple and Android devices, including an iPhone, to show how Reflect adapts to the environment at runtime and helps reduce flakiness and false positives.

February in Node.js: Release Discipline, Security Signal, and Runtime Progression

February was not defined by major feature drops. It was defined by process hardening, structured release cadence, and continued runtime iteration across both LTS and Current lines. For production teams, this month reinforced three pillars: This is the technical breakdown of what actually mattered.

Modernizing Legacy APIs Without a Risky Rewrite: A Step-by-Step Enterprise Playbook

Modernizing fragile, undocumented APIs can feel risky in conservative enterprises. This guide shows how to prove value safely using a strangler-fig approach, traffic controls, and an API abstraction layer. You will learn how to frame a proof of concept, build a governed façade, and incrementally redirect traffic without disrupting production.

Al boosts developer speed, so why does it slow testers down?

AI slows testers down when it’s added without a tester-first experience. Testers naturally question coverage and intent, so Katalon designs AI around real testing workflows to boost productivity instead of creating friction. — Alex Martins, VP of Strategy at Katalon Follow Katalon for more insights in our series!

The (not so) hidden cost of custom logging

Custom logging can technically capture everything, but in practice, it rarely does. Coverage degrades over time, external APIs get forgotten, and during incidents, you're left asking "did anyone log this?" instead of debugging. Automatic capture solves this. If you're a technical leader, there's a good chance your team is spending significant time on custom logging… and you might not even realize how much it's costing you in productivity and incomplete debugging data.