Systems | Development | Analytics | API | Testing

Companies are rapidly adopting AI, but it's not all roses. The excitement comes with significant risks, such as shadow AI, runaway costs, and security nightmares. This post explores the real challenges organizations face in AI governance today and highlights how forward-thinking companies are beginning to tackle them. Companies are charging headfirst into AI, with research around agentic AI in the enterprise finding as many as 9 out of 10 organizations are actively working to adopt AI agents.

The messaging and data streaming industries are constantly evolving, with major shifts such as large vendor purchases. If your company relies heavily on a platform such as Apache Kafka and you recently discovered that your vendor was acquired by a competitor, you are most likely dealing with a combination of uncertainty, budgetary risks, and technical difficulties.

In the steel fabrication industry, operational efficiency is defined by how well you manage data. Tekla PowerFab is the undisputed heavy lifter for estimating, production control, and inventory management. It is robust, reliable, and deeply integrated into shop floor workflows. However, as steel fabricators look to digital transformation—building custom mobile apps for site managers or feeding data into modern analytics platforms—they hit a roadblock.

In today’s fast-paced software environment, getting product features out the door quickly is the minimum. Getting features out the door quickly + with reliability is what separates high performing teams opening up larger opportunities. This is where DevOps testing comes into play, testing not just at the endpoint of the development + operations lifecycle but as an integrated process throughout every step of the life of the product.

A comprehensive guide to DreamFactory's evolution from a monolithic platform to a modular, container-ready architecture—and how administrators should approach version upgrades.

"Too much information running through my brain." When The Police sang this opening line on their 1981 album Ghost in the Machine, they weren't thinking about artificial intelligence, but the sentiment perfectly captures the state of modern AI. The song warns of an overload of data that parallels how modern AI agents process extensive collections of messages and data.

I just finished building Speedscale’s eBPF-based component to capture and analyze network traffic in a Kubernetes cluster, and it forced me to confront some uncomfortable truths about observability. While there were certainly some challenges along the way, particularly in dealing with Go applications, the approach was relatively straightforward.