Cloud cost optimization services
Your cloud bill grew faster than your traffic, and nobody is quite sure which line item is to blame. I find where the money actually goes and bring it down, without trading away the reliability you are paying for.
What is cloud cost optimization?
Cloud cost optimization is the work of matching what you spend to what you actually use. Most bills carry 30 to 60% of avoidable waste: over-provisioned nodes, idle resources, the wrong pricing model, and egress nobody budgeted for. The cluster works, so the waste compounds quietly month after month.
I treat it as an engineering problem, not a spreadsheet exercise. The same hands that design and run the infrastructure go through compute, storage, data transfer and tooling, fix the root causes, and leave you with cost visibility you can keep.
What the service covers
Right-sizing
Match compute and memory to real usage so you stop paying for reserved headroom that never gets used.
Pricing model
Reserved Instances and Savings Plans for steady-state load (up to ~72% off), spot capacity for the elastic middle (up to ~90% off).
Autoscaling
Scale nodes and pods with demand so idle capacity stops running overnight and on weekends.
Egress & data transfer
Find the cross-zone and cross-region transfer that quietly inflates the bill, and keep traffic where it belongs.
Observability cost
Tame Datadog and logging spend: metric cardinality, log indexing, host counts and retention.
Cost visibility
Tagging, budgets and alerting so the savings hold instead of drifting back up after I leave.
How the engagement works
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1. Audit
I map your bill to its real cost drivers and rank the waste by how much it costs and how hard it is to fix.
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2. Quick wins
We start with the changes that carry no architectural risk: orphaned resources, right-sizing and commitment pricing.
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3. Structural fixes
Autoscaling, spot adoption, egress and observability changes that need more engineering, done as code.
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4. Keep it down
Guardrails, budgets and a short playbook so your team can hold the line without me.
Where I cut cost
Provider-agnostic, with the deepest experience where the bills hurt most: Kubernetes, AWS and observability tooling.
AWS
Right-sizing, Savings Plans, reserved and spot capacity, storage tiering and egress reduction.
Kubernetes
Cluster right-sizing, bin-packing and spot node pools for stateless and batch workloads.
Datadog
Custom-metric cardinality, log indexing and APM spend that balloons without anyone deciding it should.
Google Cloud & Azure
Committed-use and sustained-use discounts, autoscaling and storage tiers to trim steady-state spend.
Where the savings usually come from
Every environment is different, but the biggest wins tend to land in the same few places. I have written these up in detail on the blog.
Over-provisioning
Wrong pricing model
Idle resources
Egress
Observability
Snowflake & data
Frequently asked questions
How much can you cut my cloud bill?
It varies, but most environments that have not been optimized carry 30 to 60% of avoidable waste. After an audit I can give you a grounded range for your specific setup rather than a generic promise.
Will cutting cost make things less reliable?
No. The goal is to remove waste, not the headroom you actually need. Right-sizing, commitment pricing and egress fixes change the bill, not the reliability. The safety margins that earn their keep stay put.
How do you charge for cost optimization?
A day rate or a fixed-price audit, depending on scope. For larger savings I am happy to discuss an arrangement tied to results. Send me your setup and you will get a clear proposal.
Which platforms do you cover?
Mainly AWS, Kubernetes and Datadog, where I have the deepest experience and where bills tend to hurt most, plus Google Cloud, Azure and Snowflake. You can also try the free Kubernetes cost calculator for a quick ballpark.
Want to know what is hiding in your cloud bill?
Send me your setup or a recent bill, and you will get an honest read on where the waste is and what it would take to cut it.
Email me →