We optimize your cloud bill or you don't pay.
Hands-on optimization across your entire stack, done by us, in your repos, following your process. We take a share of what we actually save you, and nothing else.
We work with teams spending $100k+/month (or $1M+/year) on cloud. AWS is our core; Azure and GCP through our specialist network.
You already know the bill is too high.
The hard part is who does something about it.
You have to find someone.
Cloud cost work needs current pricing knowledge across a dozen services, and the patience to go volume by volume, instance by instance, log group by log group. Very few engineers have that, and the ones who do are usually the ones you least want to pull off the roadmap.
You have to train them, and then keep them.
AWS pricing and service options change every quarter, so whatever your team learned last year is already partly stale and the internal doc that captured it was never updated. Worse, that knowledge lives in one person's head. When they leave, it leaves, and you start again.
And when it is done, nobody wants to do it again.
Cost work lands as a one-off project, gets celebrated, then decays. Six months later the bill is back where it started and the same conversation begins again, except now the team is tired of it.
Meanwhile every hour spent on this is an hour not spent on the product your customers actually pay for, and every hour you wait is another hour of overspending you never get back.
Why not just do it yourselves?
You could do all of this in-house. Some teams do, and it works, if cloud cost is the most valuable thing that engineer could be doing this quarter.
We have spent more than 10 years doing cloud optimization. Keeping current with every pricing and service change is our job, not a side quest for your team.
Four ways to fix this. One of them is free if it fails.
| Do it yourselves | Consultant on a day rate | FinOps SaaS tool | LeanerCloud | |
|---|---|---|---|---|
| Who does the work | Your engineers | Consultant advises, your engineers implement | Your engineers, guided by a dashboard | We do it, in your repos, in your process |
| What you pay | Salary plus the roadmap you did not ship | Day rate, outcome or not | Subscription, outcome or not | A share of savings we actually delivered |
| If nothing gets saved | You still paid the salaries | You still pay the invoice | You still pay the subscription | You pay nothing |
| Incentive to keep digging | Competes with every other priority | Hours are the product | None after signature | Direct: more savings, more revenue for us |
| Coverage | Whatever the team gets round to | Whatever is in the statement of work | Whatever the tool detects | Everything we can find, including the small stuff |
| The long tail of small wins | Never worth an engineer's day | Never worth billing a day for | Flagged, then buried in a backlog | Automated, so a $200/month win still pays |
| Speed to first saving | Weeks to quarters | Weeks | Weeks after rollout and triage | Days |
| Knowledge after it ends | Leaves with the engineer | Leaves with the consultant | Rented, as long as you keep paying | Savings live in your infrastructure, tooling is self-hosted and yours |
The trade-offs the table cannot show
- Hourly: you carry all the outcome risk, scope is fixed before anyone knows where the money is, small wins get skipped, and you end up managing the consultant.
- SaaS tool: it reports more than it fixes, so your engineers still do the work. Any automation does not know your application, so it stays generic or limited and still needs their attention. You pay whether or not anything ships, and your whole footprint lives on someone else's backend.
- Us, stated honestly: if we do this well the invoice is bigger than you expected. That is what success costs, and it is a fraction of money you would not otherwise have had. A cap is available if you want one.
How we work
We make low-risk, reversible changes in your repos and ship them through your own review and rollout process.
- 1
Read-only access
You grant scoped, read-only access. No standing admin, minimal IAM.
- 2
Audit and prioritised list
Every finding, what it saves per month, and how risky it is. Yours to keep whether or not you continue.
- 3
First changes in your repo
We open pull requests in your repositories, usually within days of getting access. They follow your process, stay low risk and reversible, and rarely require major architecture changes.
- 4
First measured savings
Changes land and the effect shows up on your bill in the same billing period.
- 5
Monthly report
What landed, what it saved, measured per change against the bill before it, and what is next.
Anyone can buy a Savings Plan
Buying commitments is an easy win, an afternoon of work, but they only ever cover part of the bill. Storage, logging and networking are not covered by any Savings Plan or Reserved Instance, so they only get cheaper when someone actually optimizes them.
So before we get anywhere near a Reserved Instance, we go through the whole stack and leave nothing unturned.
Compute
Spot, Graviton, right-sizing, autoscaling, and idle or oversized non-production.
Storage and databases
EBS types and IOPS, snapshots, S3 classes and lifecycle, Aurora I/O mode, oversized replicas.
Logging and networking
Log retention and volume, NAT and cross-AZ transfer, VPC endpoints.
Commitments
RIs and Savings Plans sized to your optimized footprint, plus EDP and private pricing.
The point is to commit to what you will actually run, not to what you happen to run today. Commit blindly up front and you lock in a year of paying for resources we may have removed.
The money is not in one big line item. It is in two hundred small ones.
Most of what we find is small. A few hundred dollars a month each, low risk, with no migration project or major architecture change. Individually, none of them justify pulling an engineer off the roadmap for half a day to research, execute and verify.
That is exactly why they never get done. Not because your team is not good enough, but because the arithmetic does not work for them.
It works for us, because we automated it.
We have spent years building and battle-testing tooling across multiple engagements. Detection, safety checks, execution and measurement are already automated end to end for most of the scenarios we run into. Batteries included. What costs your engineer half a day costs us minutes.
40 small optimizations, averaging $250 a month each.
Individually: not worth a half day of engineering time.
Together: $10,000 a month. $120,000 a year.
Manually, at half a day each: 20 engineering days, spread across people who have other jobs.
For us: a few days, mostly automated, and you pay only out of what it saves.
Why we do not bill by the hour
A day rate pays for effort. We are paid for outcomes, so we only make money when you save money.
That is not a fairness slogan. A vendor paid a subscription is done when you sign. A consultant paid by the day is done when the days run out. We are done when there is nothing profitable left to find.
Our Engagement Models
We take a share of the savings for the first year after each change lands, invoiced monthly and measured per change against the bill before it. We can also bill our services through AWS Marketplace. It typically costs less than a FinOps SaaS subscription. If you want a cap, we will agree one. We work with teams spending $100k+/month on cloud.
Done with You
We work side by side with your team to optimize your cloud costs together
- We show your team what we do and help them adopt an efficiency mindset
- Your team participates in implementation decisions
- Your team keeps the knowledge behind each optimization
- Changes follow your existing review and rollout process
Done for You
We offload as much as possible of the hands-on optimization work
- The hands-on work happens in your repos
- We handle the audit, implementation and measurement
- Your engineers review changes instead of researching them
- Monthly reports show what landed, what it saved and what is next
Do it Yourself
Our cost savings automation software saves you money while you sleep
- Start saving in minutes for certain AWS resources
- Minimal effort and no config changes
- We help you get started if needed
- Billed through the AWS Marketplace
What this looks like on your P&L
The bill is the wrong number to manage. What matters is what your infrastructure costs per customer, per transaction, per gigabyte processed, per seat.
We report savings that way wherever you can share the denominator: infrastructure cost per active user before and after, cloud cost as a percentage of revenue, gross margin impact.
A 30% reduction in run rate on a $200,000 a month bill is not an infrastructure result, it is two points of gross margin. For fast-growing teams the absolute bill may still rise, while the cost per unit falls and growth stays sustainable.
The automation that makes this economical
We have a broad set of tools that cover most common use cases. Some automate an optimization end to end and are available on the AWS Marketplace; we use the others ourselves in client engagements.
AutoSpotting
Makes it a breeze to safely adopt Spot instances in AutoScaling groups: no configuration changes, automated instance type diversification with a bias for newer instance types, and failover to on-demand.
- Up to 90% savings on auto-pilot
- Install in minutes from CloudFormation or Terraform
- Tag-based control - no resource reconfiguration
- Self-hosted and privacy-focused: no SaaS backend
EBS Optimizer
Converts EBS volumes attached to your EC2 instances to the most suitable volume type, for lower costs with often better and more predictable performance.
- GP2 to GP3 conversions for ~20% lower cost
- Better and more predictable performance
- Minimal IAM permissions and serverless design
- Priced fairly as a small share of the savings
About LeanerCloud
LeanerCloud is a network of freelance cloud optimization specialists with decades of combined AWS experience. It was founded in 2022 by Cristian Magherusan-Stanciu after leaving AWS, where he worked as a Specialist Solutions Architect for Spot and Graviton.
We aim to offer the deepest and most comprehensive cloud optimization services on the market, at fair, customer-obsessed prices. AWS is our core, and we cover Azure and GCP through specialists in our network. We're always open to talented cloud professionals interested in joining us.
We often share insights and learnings through our podcast and YouTube channel.
Frequently Asked Questions
Common questions about working with LeanerCloud
Still have questions?
Book a free savings audit or email us and we will get back to you.