Amey-Thakur Cloud cost optimization
You cannot cut what you cannot attribute. Visibility first, then the big three levers: rightsizing, commitments, and storage lifecycle; everything else is decoration until those are done.
Method
- Attribute before optimizing. Enforce tags (team, service, env) at provision time via IaC policy, not wiki pleading; untagged resources get a weekly report and an owner hunt. Turn on the billing export to a queryable store; the console's month view hides the per-service trends you need.
- Rightsize from utilization, not fear. Pull 30 days of p95 CPU/memory per instance; anything under ~40% at p95 drops a size (halving cost per step). Do the same for provisioned IOPS, over-replicated dev databases, and idle load balancers. Schedule non-prod to sleep nights and weekends: 70% of the week is off-hours.
- Buy commitments for the floor, spot for the burst. Cover the stable baseline (12 months of history says what that is) with savings plans/reserved capacity at 60-70% coverage; leave headroom on-demand. Fault-tolerant batch and CI go on spot at 60-90% off, with interruption handling tested (see kubernetes-workloads for disruption budgets).
- Lifecycle the storage. Objects: transition to infrequent-access after 30 days, archive after 90, delete what compliance does not require (see data-retention); abort incomplete multipart uploads. Snapshots and orphaned volumes/IPs are the classic silent leak: sweep monthly.
- Respect egress and cross-zone gravity. Data leaving the provider or crossing regions costs more than compute reading it in place. Process where data lives, cache at the edge, and check NAT gateway processing charges: a chatty service behind NAT can out-cost its instances.
- Institutionalize the loop. Unit economics metric (cost per request/customer/GB) on a dashboard, anomaly alerts on daily spend, a monthly 30-minute review per team with the top-5 movers, and cost as a line item in design reviews (see architecture-review-board). One-off cleanups decay in a quarter; the loop does not.
Boundaries
- Do not trade reliability invisibly: dropping multi-AZ, backups, or headroom is a risk decision for the service owner, not a cost optimizer's line edit.
- Engineering time is a cost too; a week of work to save $40/month fails its own review.
- Provider pricing shifts and this skill's ratios drift; re-verify numbers against current price sheets before big commitments.