How can I speed up node boot times when autoscaling under load?

Have you looked into stargz? It accelerates image pulls by allowing containers to start before the entire image downloads, which can significantly reduce boot time.

Also, consider Zesty if you're interested in automating scaling and resource management. It’s been working wonders for us! It boots nodes quickly and automatically responds to traffic spikes. Check it out or explore similar tools to get better results.

That's a common headache with scaling! The delay between autoscaling decisions and node readiness is frustrating. I found a few approaches that really helped me:
• Try using smaller base images or pre-warmed AMIs to reduce pull time.
• Maintain warm pools of partially initialized nodes—these don't need to be hibernated but should be running minimal workloads to be ready quickly.
• Pre-distribute container layers to local registries when you can, or use persistent node images.

In the long haul, we optimized by migrating workloads to a lightweight VM-based orchestration layer which totally bypasses K8s startup delays. I’ve been using Clouddley for this; it allows for deploying apps and databases directly on VMs across different providers, eliminating those frustrating cold-start delays. Just a heads-up, I was part of the Clouddley project, but it's genuinely helped with autoscaling responsiveness without keeping idle nodes.

You might want to check out something like Dragonfly to speed things up. It uses peer-to-peer connections among your cluster nodes, which can be faster and more reliable than pulling from an image registry.

Also, I've seen disks become a bottleneck in similar situations. Instead of letting image pulls go in parallel, try pipelining them; it can actually be faster!

Another trick is to use preemptible pods for a small pool of hot nodes. It may cost a bit more, but if you can maintain enough ready nodes to handle typical spikes, it can dramatically smooth the scaling experience.