Cloud Cost Optimization (FinOps)
I cut cloud bills 20-50% without hurting reliability, by rightsizing over-provisioned resources, fixing autoscaling, using spot and savings plans, and killing waste. You see the savings on the next invoice. I usually pay for myself in weeks.
Sound familiar?
- ✕The cloud bill grows every month and no one can fully explain it
- ✕You suspect you're massively over-provisioned but can't prove where
- ✕Idle, orphaned, and forgotten resources are quietly burning money
- ✕Kubernetes requests/limits were guessed once and never revisited
- ✕You're paying on-demand for steady, predictable workloads
- ✕Finance is asking hard questions and you need real answers
What you get
- ✓A clear, itemized map of where the money actually goes
- ✓20-50% reduction on targeted spend, visible on the next invoice
- ✓Rightsized compute, storage, and Kubernetes requests/limits
- ✓Spot and savings-plan strategy for the workloads that fit
- ✓Guardrails and dashboards so costs don't creep back up
Cloud bills usually grow because nobody’s watching, not because you’re doing more
Most cloud waste isn’t dramatic. It’s a thousand small things. Instances sized for a launch-day spike that never came, volumes left behind after migrations, dev environments running all weekend, Kubernetes requests padded “just to be safe,” steady workloads paying on-demand rates. Add it all up and it’s 20-50% of the bill.
What I help with
- Cost visibility. An itemized map of where the money actually goes, by service, team, and workload.
- Rightsizing. Compute, storage, and Kubernetes requests and limits matched to real usage, with sane headroom.
- Pricing strategy. Spot for fault-tolerant work, savings plans and committed-use discounts for steady baseload.
- Waste cleanup. Idle resources, orphaned disks, oversized logging and egress, environments everyone forgot about.
- Guardrails. Budgets, alerts, and dashboards so the bill doesn’t quietly creep back up.
How an engagement works
- Analyze. Pull billing and usage data and find the biggest levers first.
- Quick wins. Ship the safe, high-impact cuts so savings hit the next invoice.
- Structural fixes. Autoscaling, pricing commitments, and rightsizing for reduction that lasts.
- Lock it in. Dashboards and guardrails so the savings stick.
Frequently asked questions
How much can I realistically cut my cloud bill?+
Most teams that haven't done a focused FinOps pass are carrying 20-50% waste hiding in over-provisioned instances, idle resources, unattached storage, and on-demand pricing for workloads that never change. I go after the biggest levers first, so savings show up on the very next invoice instead of after a months-long project.
Will cost cutting make my system slower or less reliable?+
No, and that's the whole point of doing it properly. I rightsize from actual usage with real headroom rather than aggressive guesses, and I won't trade away reliability for a cheaper bill. If a change carries a tradeoff, you hear about it before I make it.
How do you cut Kubernetes costs specifically?+
Right-sizing requests and limits to real usage, bin-packing with the right node types, autoscaling nodes (Karpenter/Cluster Autoscaler) and pods (HPA/VPA), moving fault-tolerant workloads to spot, and cleaning up idle namespaces and orphaned volumes. The requests and limits fix alone usually recovers a big chunk.
Do you charge a percentage of savings?+
I'm flexible. Fixed-scope or a share-of-savings arrangement both work. Either way the engagement should pay for itself quickly and obviously.
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