AI Inference

Answer-first: In-Place Pod Resizing (GA in Kubernetes v1.35) allows you to modify CPU and memory requests/limits on running containers without restarting the pod — eliminating cold-start disruptions for AI inference, databases, and stateful workloads. This guide covers requirements, production YAML, VPA integration, cost optimization patterns, and gotchas. What You’ll Learn That AI Won’t Tell You In-place pod resizing edge cases where CPU updates cause container restarts. Configuring kubelet parameters to support resizing without disrupting running JVM tasks. Before this feature, changing a container’s resource allocation required deleting and recreating the pod. For a stateful database holding connections, an AI model with 30GB of weights loaded in memory, or a long-running batch job — that restart is catastrophic. In-Place Pod Resize finally decouples resource management from pod lifecycle. ...

Answer-first: Go 1.26 ships three landmark runtime features: the Green Tea garbage collector (10–40% GC overhead reduction), ~30% faster cgo calls for AI inference bindings, and an experimental goroutine leak profile that detects permanently blocked goroutines via GC reachability analysis. What You’ll Learn That AI Won’t Tell You Performance metrics of garbage collection optimization in Go 1.26. Memory overhead trade-offs when calling CGO functions in high-throughput network threads. Released in February 2026, Go 1.26 is not a routine patch release. It fundamentally changes how the Go runtime manages memory, interacts with C code, and surfaces concurrency bugs. For teams running Golang microservices at scale, these improvements compound across a fleet — zero code changes required. ...