Cost analysis
Examine cloud spending by service, account, environment, workload, and available allocation data.
Cloud cost optimization based on engineering evidence.
Cloud bills increase for many reasons. Some costs reflect legitimate growth. Others come from unused resources, oversized workloads, inefficient architectures, or missing ownership. We analyze cloud and Kubernetes spending, identify costs that can realistically be reduced, and implement engineering changes that address the underlying causes. We do not promise savings percentages before examining the infrastructure and its usage.
The problem
The cloud bill is growing, but nobody can explain all of it.
The bill is growing, and the line items still do not map to a service, an environment, or a decision.
One bill
As found
- no owner
By line item
- Compute, 38 of 100
- Database, 18 of 100
- Storage, 14 of 100
- Network, 12 of 100
- Kubernetes, 10 of 100
- Other, 8 of 100
By owner
- checkout, 22 of 100
- No owner, 78 of 100
Illustrative proportions
01
Spending lacks ownership
Costs cannot reliably be assigned to products, environments, or engineering teams.
02
Unused resources accumulate
Old environments, oversized instances, unattached storage, and forgotten infrastructure remain billable.
03
Kubernetes capacity is inefficient
Resource requests, scheduling, and scaling decisions lead to capacity that is paid for but rarely used.
04
Architecture creates ongoing costs
Network transfer, duplicated infrastructure, data services, and unnecessary environments make the baseline more expensive than required.
What changes
Understand the bill before deciding what to cut.
Identifiable savings opportunities
We distinguish real waste from resources needed for reliability, resilience, or product demand.
One bill
- no owner
- waste candidate
By line item
- Compute, 38 of 100
- Database, 18 of 100
- Storage, 14 of 100
- Network, 12 of 100
- Kubernetes, 10 of 100
- Other, 8 of 100
By owner
- checkout, 22 of 100
- No owner, 78 of 100
Illustrative proportions
By owner
- checkout, 28 of 100
- search, 15 of 100
- data, 25 of 100
- platform, 20 of 100
- idle staging, 7 of 100
- unattached volumes, 5 of 100
Waste candidates, checked before removal
Illustrative proportions
Costs assigned to owners
Teams can understand which services and infrastructure decisions contribute to spending.
Changes that remain effective
Automation and operating practices help prevent the same unnecessary costs from accumulating again.
Cloud cost and FinOps engineering.
Rightsizing
Evaluate compute, storage, databases, and other resources against measured usage.
Kubernetes efficiency
Review resource requests, scheduling, autoscaling, node selection, and cluster utilization.
Cost allocation
Improve tagging, labeling, ownership, and reporting across infrastructure.
Architecture optimization
Investigate expensive data transfer, duplicated platforms, storage patterns, and service choices.
FinOps practices
Establish useful reporting, forecasting, review processes, and engineering accountability.
Find the cost, understand the cause, change the system.
How the work runs
01
Analyze the spending
Read billing and usage data alongside the architecture and the engineers who understand it.
02
Separate waste from necessary capacity
Evaluate potential changes against performance, reliability, and operational requirements.
03
Implement improvements
Remove waste, adjust capacity, or change infrastructure architecture where justified.
04
Establish ongoing visibility
Make cost attribution and review part of normal engineering decisions.
Technologies
Used when they fit the system you already run. Not as a checklist.
AWS Cost Explorer · GCP Billing · Kubecost · OpenCost · Kubernetes
From the notes
Common questions
How much can you reduce our cloud bill?
That depends on the workloads, current utilization, purchasing commitments, and architecture. We identify specific opportunities and estimate their impact from actual usage and billing data before making claims.
Is this FinOps consulting?
Yes, with an engineering focus. We work on cost visibility, allocation, and operational decisions, then implement relevant infrastructure improvements.
Do you only optimize Kubernetes?
No. Kubernetes is one component of cloud spending. We also review compute, databases, networking, storage, managed services, and other significant cost drivers.
Do you work on a shared-savings basis?
Our current service description uses engineering engagements with defined deliverables rather than a percentage-of-savings arrangement. This keeps the work focused on sustainable improvements rather than maximizing a claimed savings figure.
Related
- Cloud infrastructure
Cloud environments need clear boundaries, identity, networking, and operational defaults. We design and improve AWS and GCP foundations that teams can extend without recreating everything for each environment.
- Kubernetes
A production cluster needs more than a working deployment. We help with cluster design, upgrades, workload configuration, networking, security, and operations. We also evaluate whether Kubernetes is still the right choice.
- SRE & observability
Production should be understandable before, during, and after an incident. We design telemetry, alerting, service-level objectives, incident response practices, and the operational workflows that turn signals into decisions.
- Infrastructure as code
Infrastructure code should make changes safer, not make every apply a high-risk event. We improve Terraform repositories, modules, state management, automated validation, and deployment workflows.
Platform assessment
Know what needs fixing before committing to a rebuild.
Our Platform & DevOps Assessment examines the infrastructure, delivery process, operational risks, and cloud costs you already have. You receive prioritized findings and a practical 90-day roadmap, including what to fix first, what can wait, and what should be left alone.