Systems | Development | Analytics | API | Testing

The EU AI Act is here, and for many enterprises, it represents a massive coordination challenge. As the world’s first comprehensive AI law, it mandates strict governance on transparency, risk management, and data quality. For platform engineers and architects, the immediate question is operational: How do we comply with these new regulations without forcing every developer to rewrite their applications?

Every year, KubeCon offers a candid look at where the cloud-native community stands — the tools gaining traction, the pain points teams share, and the big gaps still holding organizations back. After a week of deep conversations, session hopping, and talking to dozens of platform teams, one theme became impossible to ignore: Platform engineering still isn’t doing enough testing. And even more surprising: many teams don’t think testing is their responsibility.

TL;DR: Claude Code writes features fast, but you need integration tests. With proxymock MCP, Claude Code can pull real production traffic and validate your changes automatically—one prompt, no manual setup. Watch it catch bugs before production.

When we first published this report last year, AI in software testing was still an experiment for most teams. Since then, well… everything has changed. In 2025, AI hasn’t been a promise of what’s to come — it’s become an everyday reality.

‍ Healthcare isn’t short on data; it’s short on usable insight. Hospitals generate an enormous share of global data, and about 30% of the world’s data now comes from healthcare, growing at one of the fastest rates across industries (RBC Capital Markets). Yet an estimated 97% of health data still goes unused for care and operations (World Economic Forum).

Testing is a very important and necessary step in the SDLC, but most teams ignore it or don’t care much about it, while some teams spend most of their time on testing instead of building features. AI is really changing the way we write code, but most people use it mainly for writing test cases, and we still end up doing it manually. So in this blog, let’s see what AI testing is, how AI helps in testing our software, what AI tools are available, and which tools help with which part of testing.

Better audience data means better ROAS, and ClickUp demonstrated this using Census to enhance ad performance, personalization, and cross-channel consistency.

This guide focuses on the critical configurations every DreamFactory administrator must understand: memory_limit, upload_max_filesize, post_max_size, PHP-FPM worker settings, and the often-overlooked configuration hierarchy where pool settings override php.ini values.

APIs are no longer just simple integration interfaces. As AI models, agents, and digital ecosystems become increasingly interlinked, APIs have become products. They have their own usage patterns, costs, and business implications. To make informed, data-driven, and business decisions, you require deep visibility into your systems. To address these challenges, the latest v4.6.0 release of WSO2 API Manager includes a dedicated API intelligence engine, powered by Moesif.

If you’ve worked in QA long enough, you’ve seen how much testing has changed inside Jira. What started as a mix of spreadsheets, manual checklists, and endless review cycles has grown into fully integrated Test Management workflows. But even with automation, some challenges never went away. Writing test cases from requirements still takes time.