Systems | Development | Analytics | API | Testing

Modern app users don’t tolerate glitches — speed and stability are non-negotiable. Debugging across multiple Android devices, however, can be tedious if done manually. That’s why developers rely on Android Debug Bridge (ADB) to streamline development. With ADB, we can: In this guide, we’ll cover what ADB is, how it works, installation steps, and the most useful commands for debugging Android applications.

Live streaming has evolved from a novelty to the backbone of modern digital events. When major brands host virtual conferences, product launches, or community gatherings, they're no longer dealing with hundreds of viewers – they're managing tens of thousands of concurrent participants, all expecting to engage in realtime chat. We recently worked with a team building live chat for a major creative software company's annual event.

‍ Note: This article is the second in this series. Check out the first one here: Why we ditched frontier AI agents and built our own.

The close of 2025 is near, and that also means a new version of PHP is about to be released: 8.5! There has already been some discussion regarding the latest features and modifications affecting developers, for example on Laravel News, PHP.Watch or the Zend Blog. In this post we are highlighting just the performance, debugging, and operations-related changes in PHP 8.5 that you will not find in the posts listed above. Several of these changes were even contributed by Tideways employees.

Salesforce has now completed its acquisition of Informatica, in a deal positioned as a way to strengthen Salesforce’s AI data foundation. If you are an Informatica customer, that headline is not the end of the story. It is the start of a long, complicated chapter. Informatica is no longer an independent data company. It is now one piece of Salesforce’s AI CRM story. That has real consequences for your data strategy, your AI roadmap, and your room to manoeuvre.

Enterprise data infrastructure is reaching an inflection point. The traditional approach — building for predictability, optimizing for stability — no longer matches how organizations actually operate. Companies are inundated with data that now comes from and lives everywhere: on-premises systems, multiple clouds, edge environments, and partner and industry ecosystems. Workloads shift daily.

When building modern React applications that need to interact with existing enterprise infrastructure, organizations often face several challenges.

AI systems change faster than traditional QA models can react, which means quality risks now emerge in real time rather than at release.