Operations | Monitoring | ITSM | DevOps | Cloud

AI Supply Chain Attacks Are Here. And Most Organizations Aren't Ready

When I read about the Vercel breach tied to a Context AI compromise, I wasn’t surprised. I’ve been talking with customers for a while now about how AI was going to introduce a new kind of supply chain risk. This is exactly what that looks like. What stands out to me is how familiar the pattern is. We saw it with open source, then again with SaaS, and again with cloud.

AI in Software Delivery: Engineering Excellence or Just Market Hype? | Harness Blog

AWS re:Invent 2025 made one thing very clear: enterprise interest in AI is no longer theoretical. The conversation has moved beyond curiosity. Teams are actively experimenting, leaders are looking for production-ready use cases, and engineering organizations are trying to figure out where AI can create real leverage across software delivery, security, platform engineering, and operations.

Accelerating MTTR with Faster Root Cause Diagnosis: AI Advisor Now Supports On-Demand Connectivity, Config Context, and Device Diagnostics

Knowing something is broken is easy. Figuring out why is hard. Introducing three new, native AI diagnostic capabilities in the Kentik Network Intelligence Platform to accelerate root cause analysis and keep your network running better.

How AI Is Changing the Way Images Are Created

For most of modern history, creating images required skill, time, and specialized tools. Whether it was photography, illustration, or graphic design, the barrier to entry was clear: you had to learn the craft. AI image generation is changing that dynamic, and the shift is happening faster than many people expected. Today, anyone can describe an idea in plain language and receive a detailed visual in seconds. That alone has reshaped expectations around creativity, productivity, and ownership. But the real impact of AI image generation goes deeper than convenience.

Build with Claude Code, Deploy with Qovery

AI coding tools eliminated the 'writing code' bottleneck. But deploying that code? Still a mess. Here's how Claude Code + Qovery Skill lets you go from idea to production in a single prompt - with enterprise-grade guardrails. Romaric founded Qovery to make Kubernetes accessible to every engineering team. He writes about platform strategy, developer experience, and the future of cloud infrastructure.

Resolve Webinar: Introducing AgentLab: The Foundation of the Autonomous Service Desk

Most service desks still operate across fragmented systems. A single ticket can touch 4–7 tools, often more, slowing resolution and increasing cost. Copilots suggest. Traditional automation executes fixed paths. Neither closes the loop. AgentLab changes that. In this webinar, we introduce a new model built on agentic AI and orchestration. One where AI agents don’t just assist. They act, adapt, and resolve.

Google Cloud Next '26 Recap: AI, Efficiency, and the Rise of Frictionless Delivery | Harness Blog

‍Summary: Google Cloud Next ’26 focused on the future of software delivery, emphasizing that AI, platform consolidation, and an urgent push toward efficiency are reshaping the Software Development Life Cycle (SDLC). The key takeaway from the event was that organizations are moving from AI experimentation to operationalization, actively consolidating fragmented tools onto end-to-end platforms that embed AI for control, intelligence, and speed. ‍

Shadow IT Is Back - And Vibe Coding Made It 10x Worse

AI coding tools are the new Shadow IT - but instead of rogue Trello boards, they have OAuth access to your code repos, cloud accounts, and production databases. Here's what's already gone wrong, and how platform engineering fixes it. Romaric founded Qovery to make Kubernetes accessible to every engineering team. He writes about platform strategy, developer experience, and the future of cloud infrastructure.

Top tips: When "sounds right" isn't right

Top Tips is a weekly column where we highlight what’s trending in the tech world today and list ways to explore these trends. This week, we’re looking at why convincing AI answers can still be wrong and how to catch them before they slip through. AI doesn’t fail the way it used to. It doesn’t give obviously wrong answers. It gives answers that are just right enough to trust. And that’s exactly why we stop questioning it. It fits into our workflow so easily.

7 best AI deployment platforms for production Kubernetes workloads in 2026

Training a model in a notebook is easy. What breaks teams is the step after, serving it reliably without haemorrhaging cloud budget or burying your SREs in YAML. The common trap: picking a platform that handles the model but not the surrounding stack. An AI deployment platform should orchestrate the full application graph (inference endpoints, vector databases, caching layers, and frontends) inside a single VPC, with GPU autoscaling that doesn't require a dedicated platform engineer to babysit.