Autoscaling & Kubernetes:
Why It’s Harder Than It Looks
1.
Scrape intervals & delays
Prometheus, DataDog, HPA checks could take eternity at scale
2.
Multi‑cluster coordination
Clusters scale independently unless you unify metrics
3.
GPU & AI workloads
GPU nodes are expensive; scaling them wrong burns cash fast
4.
Security & compliance
Hardened images and FIPS matter in regulated environments
This is exactly why we built Kedify