14 ideas (5 main, 9 under them), ranked. Strongest: Right-Size Idle Instances. Click through to explore this as a live bubble map, grow any idea further, or re-score it for your situation.
Ranked by overall score (1-10), the average of Impact, Feasibility, Cost to implement (lower is better, flipped).
Compare CPU and memory p95 utilization over 14 days, then downsize persistently underused instances.
On burstable instances, low average CPU can hide credit depletion; inspect surplus-credit charges and throttling metrics.
Collect working-set and swap data because low p95 memory can mask brief peaks that cause OOM restarts.
Canary one workload on the next smaller instance class and compare latency and error rate before fleet-wide changes.
Stop dev and test resources overnight and weekends; verify schedules against deployment and batch-job calendars.
Require dev and test tags at provisioning so shutdown policies target nonproduction assets without touching production.
Compare scheduler logs with deployment and batch calendars weekly to catch missed stops and accidental production shutdowns.
Create CI test stacks on demand and destroy them after runs to eliminate idle compute between jobs.
Use a year of hourly usage data to cover predictable compute demand without locking in variable workloads.
Review provider billing reports monthly; low utilization flags commitments that should be reduced at renewal.
Group hourly usage by family and region, then cover only the recurring baseline to avoid stranded commitments.
Model hourly rates against On-Demand spend and verify the commitment pays back before its term ends.
Identify untouched object versions and snapshots, then transition or delete them according to retention requirements.
Use billing and flow logs to locate cross-zone traffic and NAT-heavy services before changing routing.
Generated with Idea Bubbles. Created 2026-10-19.