Operations | Monitoring | ITSM | DevOps | Cloud

Sovereign cloud for financial services: Meeting FCA and PRA requirements with UK infrastructure

Financial services in the UK operates under one of the most demanding regulatory frameworks in the world. The FCA and PRA between them set expectations for operational resilience, outsourcing, data governance, and concentration risk that shape every infrastructure decision a regulated firm makes. Cloud adoption in the sector has happened, but it's happened under regulatory scrutiny that's grown steadily more pointed over the last several years.

Managing DHCP Across Distributed Networks

Managing DHCP across distributed networks gets messy fast. Lease activity changes constantly. Naming conventions drift. Infrastructure changes happen independently across locations. Before long, your team no longer has a complete view of what’s happening across the network. What started as a straightforward service becomes a records problem with real operational consequences.

Fix flaky tests with AI, and track future test work in Jira

In January we launched Tests in Bitbucket Pipelines – a single place to track, organize, and understand your test health over time. In April we added automatic flaky test detection so unreliable tests get flagged before they slow your team down. But spotting a problem is only half the battle. Day to day, your team still needs to act on a test – track it as work, clean it up, or route it to the right person.

Reading the agent traces is how you make the call your eval can't

Remember being excited (or dreading, depending on the stage of your career and the company you worked at) about writing unit tests? Or sweating all the details in your end-to-end and integration tests you were sure covered all the use cases your users would hit? These days a lot of UIs are slowly being replaced by a single input field and an agent that promises to deliver the same value a UI would, but with the elegance and pun-ness of a “Jarvis”.

Shipped: Turn your Bifrost gateway into an AI spend meter

If you route model traffic through Bifrost, you already have the hard part: one place every AI call passes through, where the model, the tokens, and the cost are visible on the way past. It’s the cheapest spot in your stack to measure AI spend. What’s missing is everything downstream – today that usage only becomes “spend” weeks later, when the provider invoice lands as a lump sum you can’t break apart.

Don't 'control' your AI spend. Understand it and be intentional.

There’s a good interview making the rounds. BizTech sat down with IBM’s James Stevenson to talk about how financial institutions can get a handle on cloud and AI costs. The advice is solid: get visibility, kill idle resources, tighten governance, tag everything. And pull finance and engineering into the same room. I don’t disagree with it. But I read the whole piece and noticed where the gravity pulls: control costs, reduce waste, bring down spend. The headline says it (‘Q&A.

Accelerate investigations with AI in Datadog Incident Response

Engineering teams spend much of their incident response time investigating the problem and coordinating the response. Both tasks become harder when telemetry data lives in one place, deployment history is stored in another, and conversations unfold across chat channels and incident bridges. Responders often spend the first part of an incident rebuilding context before they can begin testing hypotheses and working toward resolution.

How Datadog uses AI to build internal software delivery tools and improve system performance

At Datadog, we want our developers to become better at using AI tools with the end goal of building quality software, faster, that generates real value. This includes not only the products and features that our customers use, but also the internal tools that help keep our workflows running smoothly behind the scenes.

What the World Cup Looks Like in Internet Traffic

The World Cup may be the most-watched event in media history — so what does it look like from inside the network? We dug into ISP traffic data to reveal how Fox Sports peaks during US games, why second halves usually win, and how traffic flows shift for entire nations like Brazil and Iran when their team takes the field.

What's New in InfluxDB and Telegraf: Q2 2026 Product Updates

Summary: Q2 was about giving teams more leverage with less overhead. Between April and June 2026, releases across Telegraf, InfluxDB 3, and InfluxDB 3 Explorer focused on reducing manual work and putting more control directly in their hands as they scale. Telegraf Enterprise reached general availability, giving teams a centralized way to manage, monitor, and support tens of thousands of Telegraf agents.