Operations | Monitoring | ITSM | DevOps | Cloud

Aiven's PG Studio is now in Early Availability, allowing you to work with your Aiven for PostgreSQL instances, directly in the Aiven Console. Over the last several decades, PostgreSQL has been steadily climbing its way to the top of popularity amongst DBAs and app developers. With the rise of AI development, PG has become the tool that you can build with at many different development stages. This starts at the home of your data, which is the Aiven for PostgreSQL service page in the Aiven Console.

Imagine it’s 2 AM and a critical system flatlines without warning. A bleary-eyed on-call engineer scrambles to restore service, shielding customers from a major outage that could torpedo your next Service Level Objective (SLO) review. Yet when daylight returns, debates over fair on-call compensation start all over again: What’s “just” pay for sleepless nights, unpredictable pings, and rapid-fire incident responses?

Shipping velocity has never been faster, but reliability can’t be the trade-off either. For engineering leaders, deploying AI for operations is no longer optional. The question is whether you’ll lead the transformation or fall behind. The hard truth? Organizations can’t keep relying on humans as the first line of defense. Not when the pace of shipping has never been faster. It’s simply not scalable.

In the world of modern microservices, scale is a necessary challenge. Enterprise service inventories start modestly with a handful of components, only to balloon to hundreds over time. Traditional monitoring approaches cannot support that weight. The more organizations build, the more work they create, often only to keep systems running.

RFID asset tracking software is rapidly becoming a key technology for organizations that manage large volumes of equipment, tools, and operational assets. Businesses across industries such as manufacturing, healthcare, logistics, and education rely on RFID technology to maintain accurate asset records and improve operational visibility.

Westminster is starting to recognise the importance of technology sovereignty. The recent Westminster Hall debate on technology sovereignty was encouraging to see. For those of us working in the UK technology sector, it felt like an important moment. Conversations about cloud infrastructure, data control and platform dependency have been happening inside the industry for years.

Enterprise operations reached a point where complexity outpaced human interpretation and outgrew the capabilities of generic AI. As environments became more distributed and interdependent, every incident, anomaly, and degradation produced ripple effects across systems that require context, lineage, and reasoning. Yet most AI models were not built for this reality. They were trained for general knowledge tasks, not the deeply connected operational truths that define enterprise performance.

I've spent a lot of time talking to platform teams who feel like they're running in circles. They build incredible automation to speed up service delivery, but even when it's running perfectly, nobody actually knows what's happening across the organization. It's hard to see who owns which service or if those services even meet basic company standards. Automation's a great start, but it usually hits a wall when you try to scale it.

A new HBR study reveals that the race to build and manage AI agents may be pushing knowledge workers toward a new form of cognitive overload. If you spend any time on LinkedIn these days, you’ve probably seen the same type of post over and over. Someone proudly announces they built an AI agent that now writes their emails, analyzes data, drafts presentations, and maybe even ships code.

Veterinary clinics typically operate during standard 9–5 business hours. But emergencies don’t follow a schedule. The puppy you just brought home might decide that the rubber duck your toddler dropped on the floor looks like the perfect snack. Or your dog might get into a box of Valentine’s Day desserts you left on the counter. Suddenly, what seemed like an ordinary evening turns into a frantic search for help.