Cost Optimisation
“Our AWS bill keeps climbing and nobody can explain why”
Last month's bill was 40% higher than expected. Finance wants answers. Your engineers can't explain it because they're building features, not tracking spend. The bill is a growing black box.
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Your AWS bill is predictable and you know exactly where every pound goes.
Right-sized instances, optimised commitments, zero waste. Clear cost allocation by team and service. A bill you can explain to finance in 30 seconds.
Your AWS bill arrives. It’s higher than last month. Again. Finance wants to know why. Your engineers shrug. They’re building features, not analysing invoices. The bill is a growing black box that nobody has time to open.
Why AWS bills are hard to control
AWS pricing is complex by design. Hundreds of services, each with their own pricing model. On-demand, reserved, spot, savings plans. Per-hour, per-request, per-GB. The bill is a spreadsheet, not an explanation.
Without deliberate cost governance, waste creeps in from every direction. Development environments that mirror production specs. Test resources that were never cleaned up. Reserved Instances bought based on optimistic projections. Each one seems small. Together, they’re 20-40% of your total bill.
How we optimise
Cost optimisation isn’t a one-time exercise. We identify the quick wins, implement the changes, and then maintain ongoing governance so the savings stick.
Quick wins first. Unused resources, oversized instances, and missing commitments. These typically account for 15-25% savings and can be implemented in weeks.
Tagging that maps to your business. Every resource tagged with team, environment, and service. Your finance team can see what each team spends without asking engineering.
Ongoing governance. Automated policies prevent waste from returning. Quarterly reviews catch new optimisation opportunities as your workloads evolve. Your bill stays predictable because someone is actively managing it.
What's usually in the way
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No cost allocation or tagging strategy
Resources aren't tagged consistently. You can't break the bill down by team, environment, or service. The total number is all you have.
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Oversized instances running 24/7
Development environments run full production specs around the clock. Production instances were sized for peak traffic that happens 2 hours a day.
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Forgotten resources accumulating silently
Unattached EBS volumes, unused Elastic IPs, orphaned snapshots, test environments that were never torn down. Each one is small. Together, they're significant.
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No Savings Plans or wrong commitments
You're paying on-demand prices for stable workloads, or you bought Reserved Instances based on projections that didn't match reality.
What we resolve
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Tagging strategy that maps cost to business
Consistent tagging across your estate with cost allocation enabled. Every pound mapped to a team, environment, or service. Visible in Cost Explorer.
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Right-sizing based on actual usage
Instance types matched to real utilisation patterns. Development environments scaled down or scheduled. You pay for what you use.
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Waste eliminated with ongoing governance
Unused resources identified and removed. Automated policies prevent future waste. Regular reviews catch new drift before it accumulates.
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Commitment strategy aligned to actual workloads
Savings Plans and Reserved Instances purchased based on real, stable usage, not projections. Reviewed quarterly as your workload evolves.
“We found savings we didn't know existed. The optimisation paid for itself in the first month.”
Finance Director , E-commerce platform
Frequently asked questions
What does AWS cost optimisation cover?
We tag every resource so finance can see exactly where the bill goes. We right-size instances based on real usage. We eliminate forgotten resources. We buy Savings Plans only when they match stable workloads. Then we set up ongoing reviews so the savings stick.
How much can we typically save?
Most clients see a 20-40% reduction in their AWS bill within the first 90 days. The exact number depends on how mature your current setup is. We tell you the realistic ceiling before you commit.
How long before we see savings?
Quick wins land in the first month: deleting waste, right-sizing the obvious culprits, fixing tagging. Larger savings such as Savings Plans and architectural changes take 60-90 days to bed in. The bill drops month-on-month, not in one big step.
Will right-sizing slow our application down?
No. We size based on actual utilisation, not best-guess. If a production server only ever uses 20% of its CPU, a smaller instance handles the workload identically and costs 30% less. We keep headroom for spikes; we don't run anything to its limit.
What if our usage changes after we commit to Savings Plans?
That's the risk we manage for you. We buy commitments cautiously, in increments, based on workload patterns we've already observed. If your usage drops, we adjust. Most commitments cover the floor of your usage, not the peak, so there's room to grow without exposure.
Ready to take the next step?
No obligation, just a clear conversation about where you are and what's possible.