Cloud Cost Optimization Guide

Spend is a symptom, not the problem

Most cloud bills are not high because the prices are unfair. They are high because of decisions that were reasonable in the moment and never revisited: an oversized instance chosen "to be safe", a test environment left running, a forgotten storage bucket filling up for years.

This guide gives you a repeatable way to find that waste, fix it safely, and — most importantly — stop it coming back. Work top to bottom; the early steps usually pay for the rest.

Step 1: Get visibility before you cut anything

You cannot optimise what you cannot see. Before changing a single resource:

• Turn on detailed billing and cost reporting.
• Enforce a tagging standard (owner, environment, application, cost centre) so spend can be attributed.
• Identify your top ten line items by cost — they almost always drive the majority of the bill.

A small number of services usually account for most of the spend. Start there, not with the long tail of small charges.

Step 2: Eliminate obvious waste

This is the fastest, lowest-risk return. Look for resources that cost money while delivering nothing.

• Idle compute — instances running at near-zero utilisation around the clock.
• Unattached storage — volumes and disks no longer connected to anything.
• Orphaned snapshots and old backups beyond your retention policy.
• Unused load balancers, IP addresses, and gateways.
• Non-production environments running outside working hours.

Scheduling non-production to shut down on evenings and weekends alone often removes a large slice of those environments' cost, with zero impact on users.

Step 3: Right-size what remains

Once the waste is gone, match the resources you keep to the work they actually do.

Right-size in small steps and watch the metrics after each change. The goal is efficiency, not fragility.

Step 4: Commit to your steady-state usage

After right-sizing, you will have a baseline of usage that runs all the time. Paying full on-demand prices for predictable, always-on workloads is the most common avoidable cost.

• Identify the workloads that run continuously and are unlikely to change soon.
• Apply committed pricing (reserved capacity or savings plans) to that baseline.
• Keep flexible, on-demand pricing for genuinely variable or short-lived workloads.
• Re-check commitments periodically as your baseline shifts.

Commit only to what you are confident will keep running. A discount on capacity you stop using is not a saving.

Step 5: Optimise architecture where it pays

Deeper savings come from design choices, but they cost engineering time — pursue them where the spend justifies it.

• Move suitable workloads to managed or serverless services to stop paying for idle capacity.
• Cache aggressively to reduce repeated compute and database work.
• Review data transfer paths; egress and cross-region traffic are easy to overlook.
• Set lifecycle rules so data moves to cheaper tiers or is deleted automatically.

Step 6: Build the habit so waste does not return

One-off clean-ups drift back within months. The teams that keep costs down change how they work.

• Set budgets and alerts so surprises surface early, not at month end.
• Make cost a visible metric owned by engineering, not only finance.
• Include a cost check in design reviews for new workloads.
• Hold a short, recurring review of spend and savings opportunities.

A simple operating rhythm

1. Weekly: Check alerts and any unexpected spikes.

2. Monthly: Review the top cost drivers and clean up waste.

3. Quarterly: Re-evaluate right-sizing and committed-use coverage.

Cost optimisation is not a project you finish; it is a discipline you keep. Done well, it frees budget for the work that actually moves your business forward — without ever trading away the reliability your users depend on.