Your FinOps and cost engineering partner.
We find where your cloud spend actually goes, remove the waste in the architecture rather than the spreadsheet, and put guardrails in so it stays down.
A cloud bill grows the way code does: one reasonable decision at a time. The instance sized for launch traffic, the environment spun up for a demo, the retention policy nobody set — none of it is a mistake on its own, and none of it shows up in a monthly total that only says the number went up.
We treat cost as an engineering problem rather than a procurement one. First we make the spend legible — per service, per team, per customer — so each line has an owner. Then we remove the waste in the architecture itself: sizing, scheduling, autoscaling, storage tiers, data-transfer paths and commitment coverage, shipped as ordinary changes with the saving measured after.
The last part matters most. Without budgets, anomaly alerts and cost checks in the pipeline, a one-off clean-up is undone within two quarters — so we leave those behind along with the savings.
What you get
- A full breakdown of spend by service, team and customer, with an owner named against each line
- A prioritised savings backlog, ordered by saving against effort and risk
- Rightsizing, autoscaling and commitment changes applied, not just recommended
- Unit-cost metrics — cost per tenant, per request or per job — reported next to the bill
- Budgets, anomaly alerts and cost checks wired into CI and your dashboards
What we help with.
Cost visibility and allocation
Tagging, account and project structure, and showback per team, service and customer — so the bill stops being one number nobody owns.
Rightsizing and waste removal
Oversized instances, idle and orphaned resources, forgotten environments, unattached volumes and old snapshots, found and removed with the change reviewed like any other.
Commitment and discount strategy
Savings plans, reserved instances and committed-use discounts sized against real usage, with coverage and expiry tracked rather than bought once and forgotten.
Kubernetes and workload efficiency
Requests and limits set from actual usage, bin-packing, autoscaling that scales down as well as up, and spot capacity where the workload can take it.
Data and storage cost
Storage tiering and retention, warehouse query and compute cost, and the data-transfer paths that quietly make up a large share of the invoice.
Cost guardrails in delivery
Budgets, anomaly alerts and cost checks in CI, so an expensive change is caught in review instead of on next month's invoice.
Why choose Covaratech for finops and cost engineering.
One team, start to finish
One team owns your system from architecture to on-call. There is no handover wall to throw requirements over.
Evidence before launch
AI features get an evaluation set before they get a launch date. If we cannot measure it, we say so.
Built to be handed over
Documentation and knowledge transfer are contract terms, not favours. You should be able to leave us at any point.
Senior engineers, not a bench
The people who scope your engagement are the ones who build and run it, never handed off to someone you haven't met.
Need help with finops and cost engineering?
We find where your cloud spend actually goes, remove the waste in the architecture rather than the spreadsheet, and put guardrails in so it stays down.
Talk to usQuestions about finops and cost engineering.
What comes up on the first call, with the answers we give on it.
1.Where does a cost engagement start?
With visibility. Tagging, account and project structure, and showback per team, service and customer, so the bill stops being one number nobody owns. Until the spend is allocated, every saving is a guess.
2.Do you recommend savings, or actually make the changes?
We apply them. Rightsizing, autoscaling and commitment changes ship as ordinary reviewed changes, with the saving measured after — the deliverable is a lower bill, not a findings deck.
3.Will cutting cost make the system slower or less reliable?
The savings backlog is ordered by saving against effort and risk, and the risky items are treated as engineering work with the same review and rollback as any other change. Idle resources, forgotten environments and untiered storage come first because they cost you nothing to lose.
4.What about Kubernetes, where nobody can see per-team cost?
Requests and limits set from actual usage, bin-packing, autoscaling that scales down as well as up, and spot capacity where the workload can take it — with per-namespace and per-team cost broken out so the numbers have owners.
5.How do you stop the bill creeping back up?
Budgets, anomaly alerts and cost checks wired into CI and your dashboards, plus unit-cost metrics — cost per tenant, per request or per job — reported next to the bill. Without those, a one-off clean-up is undone within two quarters.