← Platform Engineering & Kubernetes
Autoscaling & Cost Control
Enough capacity for the spike, none of the waste the rest of the time.
Static capacity sized for the peak wastes money every hour you're not at the peak; sized for the average, it falls over when traffic arrives. Autoscaling resolves the dilemma — horizontal and vertical pod autoscaling, cluster autoscaling and right-sized node pools that follow demand up and back down. The lever most teams under-use is well-tuned resource requests and limits paired with spot or preemptible capacity for tolerant workloads, and I add per-workload cost visibility so scaling decisions are made against real numbers, not guesses.
What's included
- Horizontal & vertical pod autoscaling
- Cluster autoscaling & node pools
- Spot / preemptible strategies
- Resource requests & limits tuning
- Cost visibility per workload
Platform Engineering & Kubernetes
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