Operations | Monitoring | ITSM | DevOps | Cloud

Civo has been identified by ABI Research as one of the world’s leading NeoCloud providers. The report underscores our focus on cloud and AI infrastructure that blends high performance, technical innovation, and strong sovereignty. Being included in the ABI NeoCloud report validates the work we have done to support modern AI workloads while giving organisations control over where and how their data is handled.

Stop overpaying for Kubernetes observability. Learn how in-cluster monitoring and AI-driven troubleshooting with Qovery Observe can eliminate APM ingestion fees, reduce SRE bottlenecks, and make your cloud costs predictable.

Westminster is starting to recognise the importance of technology sovereignty. The recent Westminster Hall debate on technology sovereignty was encouraging to see. For those of us working in the UK technology sector, it felt like an important moment. Conversations about cloud infrastructure, data control and platform dependency have been happening inside the industry for years.

Karpenter is a fast, flexible Kubernetes autoscaler designed to improve cluster performance and cost efficiency. When the cluster doesn’t have capacity to schedule a pod, Karpenter requests additional compute from the cloud provider, specifying a right-sized instance that matches the preferences you’ve set (for example, instance family).

In Part 1 of this series, we explored how Karpenter’s architecture enables just-in-time provisioning and active node consolidation. Because Karpenter is constantly making infrastructure decisions based on real-time scheduling pressure, its metrics can give you early warning of provisioning slowdowns, cloud API throttling, and misconfigurations that prevent it from scaling the way you expect.

In the first two parts of this series, we explored how Karpenter’s architecture enables just-in-time provisioning and active node consolidation, and we identified the key Karpenter metrics you should track to keep your cluster performant and cost-efficient. In this post, we’ll look at vendor-agnostic tools you can use to capture these signals.

In this series, we’ve explored Karpenter’s architecture, the key metrics that reflect its health and performance, and the vendor-agnostic tools for collecting and analyzing its telemetry data. In this final post, we’ll show you how Datadog helps you monitor and alert on Karpenter alongside your Kubernetes cluster and the infrastructure that runs it.