Operations | Monitoring | ITSM | DevOps | Cloud

Table of Contents Autoscaling and policy-driven resource management are two sides of the same coin. Autoscaling adjusts capacity as demand changes, while policies define the boundaries it operates within: who can use how much, which workloads can be changed, and what safeguards must be respected. Without autoscaling, clusters are either overprovisioned or overwhelmed. Without policies, autoscaling can create runaway costs, noisy neighbors, or disruptive changes to critical services.

Table of Contents Resource contention happens when workloads compete for more capacity than a node or cluster can provide. For CPU and memory, the symptoms are familiar: CPU throttling, OOM kills, and noisy neighbors slowing latency-sensitive services. These are largely solved problems, addressed by accurate requests and limits, Quality of Service classes, and autoscalers like VPA and HPA that adjust sizing and replicas as demand changes. GPU contention is different, and far more expensive to get wrong.

Replay and recap of our live session: an AI agent reads a Heroku Rails app and deploys the full stack to AWS through Qovery from one prompt. Chapters, timestamps, the four ways teams leave Heroku, and the steps a human should still own. Romaric founded Qovery to make Kubernetes accessible to every engineering team. He writes about platform strategy, developer experience, and the future of cloud infrastructure.

Monitoring Kubernetes in production is structurally different from monitoring traditional servers: pods are ephemeral, nodes autoscale, and the layered resource model—containers, pods, nodes, namespaces, deployments, services—creates an observability challenge that tools built for static infrastructure were never designed to handle.

This week marks the end of our fourth Civo Navigate London event, and it feels like a good moment to say that this one had a slightly different energy from the ones before it. Over the past four years, we have hosted 10 Civo Navigate events across North America, India, and Europe, and each one has taught us something new about what this community actually wants from a day like this. London 2026 was no exception, and I think this year's lineup pushed that a little further than usual.

Jamin Ball’s recent piece, “Systems of Record Won the SaaS Era — Clearinghouses Will Win the Agents Era,” is the cleanest articulation I’ve seen of where the durable moat goes next. His argument is simple and, I think, correct: the SaaS era rewarded whoever owned the system of record, and the agent era will reward whoever owns the clearinghouse.