The Cloud & AI Cost Optimization Checklist

Compare CPU/memory utilization against instance size; downsize or stop instances running well under their provisioned capacity.

CostMon CostMon surfaces per-service AWS spend trends so an oversized instance's cost stands out before you have to go hunting for it in the console.

Audit for unattached EBS volumes, snapshots past their retention need, and unassociated Elastic IPs. All are billed whether anything uses them or not.

Stop dev, staging, and test instances outside business hours instead of leaving them running around the clock.

Check scale-out thresholds and max instance limits against actual peak traffic, not the peak you originally provisioned for.

Identify objects and backups that haven't been accessed in months and move them to infrequent-access or archive tiers.

CostMon CostMon's normalized, service-level view makes a growing storage line easy to spot over time, across providers.

Cross-region, cross-AZ, and internet egress traffic bills per GB. Check whether services could be colocated to avoid it.

Automate expiration and tiering rules on buckets and volumes so cleanup doesn't depend on someone remembering to do it.

Confirm backup cadence and retention windows match your actual recovery requirements, not a default nobody has revisited.

Break spend down by model and by workload. A blended total hides whether an increase is a deliberate upgrade or a regression.

CostMon CostMon's Anthropic connector pulls per-model, per-day usage so this breakdown doesn't require a spreadsheet.

Estimate a rough cost per request or per task before a feature ships, so a regression is visible immediately, not a month later.

A single logic bug in an agent loop or retry policy can multiply call volume as much as per-call cost. Watch call counts as well as spend.

Reuse cached context for calls that repeat the same system prompt or reference documents instead of resending it every time.

The cheapest model per call isn't always the cheapest per completed task. Compare on results, not the sticker price.

Compare current commitment coverage against your actual footprint. Commitments sized for last year's usage rarely fit this year's.

CostMon A normalized daily view makes it easy to compare current usage against what a commitment was originally sized for.

Use shorter or convertible commitments for workloads you're not confident will run steady for the full commitment term.

Flag reserved capacity sitting unused, or commitments expiring soon, so you can renew, resize, or let them lapse on purpose.

Provider discount tiers and enterprise agreements are usually renegotiable once your spend has grown past the terms they were set at.

Pull every provider's billing data into the same schema, currency, and cadence so totals are actually comparable.

CostMon This is what CostMon does first: aggregates AWS, Anthropic, and the rest of your stack into one deduplicated daily table.

A single service moving sharply off its own historical trend is a stronger signal than total spend moving at all.

CostMon CostMon watches each connected service's daily trend and can flag a deviation from its own baseline.

An alert that lands on a specific engineer's radar gets acted on; one that lands in a shared inbox decays into being ignored.

AWS, Anthropic, and OpenAI can each stop spend outright once it crosses a number you set. Google Cloud and Azure alert but don't cap; wire your own automation if you need a real stop there.

A short, regular review against a normalized view catches drift while it's small, instead of at invoice time.

Consistent tagging at the point resources are created makes it possible to attribute cost instead of just seeing a total.

Any tool that only needs to read billing data should never be granted write access to workloads or infrastructure.

CostMon CostMon only ever requests read-only, cost-scoped access to each connector, never write access to your infrastructure.

Cross-check active users against paid seats for every SaaS subscription. An unused seat is pure waste with no offsetting benefit.

Keep a checklist for tearing down a project's resources when it ends, instead of relying on someone remembering to look later.