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The latest News and Information on Cloud monitoring, security and related technologies.

Why workflows, not agents, are the primitive your team is missing

If your team has adopted AI coding agents, you've probably noticed something strange: writing code stopped being the hard part. That's the shift Patrick, a principal engineer at Upsun, kept returning to in our latest Product Highlights conversation. He's spent twelve years here, most of them writing back-end APIs in Go, and the past year building with AI on our newest product, Upsun Dispatch. His verdict on where the bottleneck moved is blunt: "The code isn't really a problem anymore.

Don't Trust the Diff: Making AI-Generated Code Reviewable And Maintainable

Coding agents changed implementation economics faster than they changed confidence. They let us produce more code, more quickly, but they did not make reviewers any better at understanding system-wide consequences. In our Kubernetes automation stack, that gap became impossible to ignore once AI started generating meaningful amounts of controller code.

Why Cloud Security Pays Off: Key Benefits Explained for Decision-Makers

Every new app, user, workload and connection creates value, yet it can also create another opening for disruption. One weak password, a missed update or an exposed setting can lead to downtime, lost data and difficult questions from customers and leadership. For decision-makers, the issue is not whether cloud security costs money. It is whether the business can afford the cost of operating without proper safety. Powerful cloud security helps you reduce risk, improve visibility, support compliance and give teams the trust to grow without looking over their shoulders.

AI ROI is not an engineering metric

I spend most of my week talking to companies about AI ROI. A few months ago, that was still a weirdly specific conversation. Now it’s everywhere. CloudZero spends a lot of time in that conversation, so I’m glad the market is talking about it. But the conversation tends to start, and stall, in the wrong place. There are two ideas I keep coming back to: That doesn’t mean developer productivity is fake. It’s very real.

The real cost of your dependency on hyperscalers

There's a version of cloud strategy that looks like a decision and a version that looks like drift. Most enterprises are living the second version. AWS won an early workload because the team knew it. Azure followed the Microsoft enterprise agreement. GCP came in through a data science team that preferred its ML tooling. Nobody chose concentration; it just accumulated.

Shipped: Allocate AWS cost by account name, not account ID

Until now, allocating by account name meant doing the work yourself: hand-building a custom dimension that mapped every twelve-digit AWS ID to a readable name, then maintaining it by hand in CostFormation. That mapping is fragile. Rename a definition or edit the wrong line and dashboards that depended on it quietly break. Now the account name is built in for accounts connected through AWS CUR 2.0.

DNS Spy Now Connects to Amazon Route 53. Read-Only, Every Record, Always in Sync.

When we launched DNS provider sync with six providers, one name came up in nearly every "what about..." email: Amazon Route 53. That makes sense. Route 53 runs DNS for an enormous share of production infrastructure, and it does not support zone transfers — so until now, monitoring a Route 53 zone meant relying on autodiscovery's educated guesses. Today that gap closes.

What engineering teams are getting wrong in 2026

Ask any engineering leader how AI has changed their team, and you'll get an optimistic answer. Ask them to prove it with a number, and most go quiet. That gap is the story of 2026. Individual engineers are faster than they've ever been. Teams, in a lot of cases, aren't. We talked to our own engineering team, the people who've spent the last year building and shipping Upsun Dispatch and living through exactly this shift, and the same tension came up again and again.