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The latest News and Information on DevOps, CI/CD, Automation and related technologies.

Konstruct product updates: Hosted control planes and multi-cloud

March signified a very important period for the Konstruct team, where we were able to focus on something we’ve heard consistently from teams: reduce the time to value without compromising control. In the previous post, we walked through how Konstruct 0.1–0.3 established the core platform model, introduced templates, and expanded GitOps into something that can represent both infrastructure and applications. With 0.4, we’re taking a more opinionated step forward.

npm axios attack - What happened and how to protect your supply chain

100M+ weekly downloads. One compromised maintainer account. A remote access trojan in two active release branches. This is a 30-minute breakdown of the Axios npm supply chain attack – how it happened, why it was hard to detect, and what any engineering team can do right now to reduce exposure. Nigel Douglas, Head of Developer Relations at Cloudsmith, is joined by Jenn Gile, co-founder of Open Source Malware, a community-driven threat intelligence platform focused on malicious open source packages.

90% AI Adoption. Still Failing. DORA Explains Why.

AI adoption is nearly universal. So why are most teams still struggling? In this session from GitKon, Nathen Harvey, head of DORA at Google Cloud, shares findings from the 2025 DORA State of AI-Assisted Software Development report, drawing on data from nearly 5,000 developers worldwide. The answer isn't more AI. It's what surrounds it.

Managing Kubernetes deployment YAML across multi-cloud enterprise fleets

At enterprise scale, managing provider-specific Kubernetes YAML across multiple clouds creates crippling configuration drift and operational toil. By adopting an agentic Kubernetes management platform, infrastructure teams abstract cloud-specific configurations (like ingress controllers and storage classes) into a single, declarative intent that automatically reconciles across 1,000+ clusters.

Introducing: Final Steps in Bitbucket Pipelines

If you’ve ever run a pipeline, you’ve certainly encountered the following situation: The pipeline fails halfway through, and the cleanup script you needed at the end to tear down test infrastructure or archive the logs never gets to run. Until now, there was no built-in way in Bitbucket Pipelines to guarantee that a step always executes at the end of your pipeline, regardless of what happened before it. Today, we’re fixing that.

Data centre security checklist: executive oversight for compliance and continuity

Data centre security must meet strict compliance and risk standards, giving regulators, insurers, and clients confidence that critical data is protected. Without it, organisations risk audit failure, downtime, and reputational damage. For executives and auditors, data centre security is part of wider governance and risk management. Oversight means confirming that physical safeguards, environmental systems, and compliance frameworks are in place and can be trusted.

AWS Direct Connect Pricing: A Complete Guide

AWS Direct Connect pricing looks simple until you’re staring at an unexpected bill. Understanding how AWS Direct Connect costs work, such as port hours, data transfer, and the charges that don’t appear on the AWS pricing page, is the first step to managing them. The model has no setup charges and no minimums, but it has enough moving parts that costs can compound quickly if you’re not watching closely.

How Finance Leaders Can Use AI To Stay On Top Of Cloud Costs

There’s always been a bit of a communication breakdown between finance and engineering when it comes to cloud costs. Cloud costs are driven by technical factors expressed in esoteric terms, and so speaking the language of finance does not guarantee that you’ll speak the language of cloud cost. But AI is changing that. Fast. With the right AI tools, finance leaders can now ask natural-language questions about their cost data and get fast, accurate answers.

Your Most Expensive Kubernetes Costs Have Been Hiding In The Wrong Bucket

If your organization is running AI or machine learning workloads on Kubernetes, the bill is real. GPU instances are among the most expensive resources in cloud infrastructure, where a single high-end node can run $30 to $40 per hour, and a multi-day training job on a cluster can cost tens of thousands before anyone looks up from their terminal. What most engineering and FinOps teams haven’t been able to do (until now) is connect that spend to the workloads that caused it.