Cloud Cost Optimization & FinOps
The cloud bill keeps climbing faster than usage justifies, finance can't tie spend to teams or products, and nobody owns cost as an engineering responsibility.
How we tackle it
Cost optimization that starts and ends with a rightsizing script produces a one-time bump and then regresses within months. We build cost visibility into the same tagging and observability layer engineering already uses, so cost per team or feature becomes a normal engineering signal rather than a quarterly finance exercise, and we prioritize architectural fixes (idle resources, unnecessary redundancy, inefficient data transfer patterns) alongside straightforward rightsizing.
Current-state pain points
- No visibility into which team, service, or feature is driving cost
- Resources provisioned for peak load running at that size permanently
- No use of reserved instances, savings plans, or committed use discounts
- Storage and data transfer costs growing without corresponding investigation
- Engineering has no incentive or visibility to consider cost in design decisions
What is in scope
- Cost and usage data analysis across compute, storage, network, and managed services
- Tagging and cost allocation strategy by team, product, or environment
- Rightsizing recommendations for compute, storage, and database tiers
- Commitment strategy (reserved instances, savings plans, committed use discounts)
- Architectural review for cost-inefficient patterns (idle resources, over-replication, chatty cross-region traffic)
- FinOps reporting and dashboarding for ongoing accountability
Who it is for
- Finance and engineering leaders who can't explain month-over-month cloud cost swings
- Organizations with no cost allocation by team, product, or environment
- Companies over-provisioned on compute or storage from early-stage scaling decisions
- Teams paying on-demand rates without any commitment or savings plan strategy
Prerequisites
- Billing and cost data access (Cost Explorer, Cost Management, or equivalent)
- At least one to two months of historical usage data for meaningful analysis
- Access to relevant engineering teams to validate rightsizing recommendations
- Finance stakeholder involvement to align on allocation and reporting needs
What you end up owning
Artifacts land in your repositories and cloud accounts, with documentation to match.
- Cost and usage baseline report broken down by service, team, and environment
- Tagging policy and enforcement mechanism for cost allocation
- Rightsizing recommendations with estimated impact per change
- Commitment purchase plan aligned to actual usage patterns
- Architectural findings on cost-inefficient patterns with remediation options
- FinOps dashboard for ongoing cost visibility by team/product
- Cost governance runbook for engineering teams
How the work is sequenced
Baseline & Allocation
Establish a cost and usage baseline and implement tagging so spend can be allocated to teams, products, or environments.
Quick-Win Identification
Identify rightsizing opportunities, idle resources, and unused commitments that can be addressed with low risk.
Architectural Review
Assess deeper architectural cost drivers such as data transfer patterns, over-replication, and inefficient storage tiering.
Commitment Strategy
Model and recommend reserved instance or savings plan purchases aligned to demonstrated usage patterns.
Governance & Handover
Stand up ongoing dashboards and a cost governance process so gains don't erode after the engagement ends.
What we typically use
Cost Visibility
FinOps Tooling
Automation
Dashboarding
What changes when this is done
Qualitative outcomes only. Any figures depend entirely on your estate, and we will not quote them before measuring.
- Cost attributed clearly to the team, product, or environment responsible
- Reduced spend on idle or oversized resources without impacting performance
- A commitment strategy matched to actual, demonstrated usage
- Engineering teams with visibility into the cost impact of their design decisions
- A governance process that prevents cost creep from returning after remediation
Common questions
Related service
Other solutions
Cloud Migration
Move workloads off legacy or on-prem infrastructure onto AWS, Azure, or GCP without disrupting the business.
Platform Engineering & Internal Developer Platforms
Give developers self-service infrastructure so platform and DevOps teams stop being a bottleneck.
Infrastructure Automation & IaC
Replace manual, console-driven infrastructure changes with version-controlled, reviewable Terraform.
Talk to the engineers who would do the work
Bring your current architecture, constraints and the problem you are trying to solve. We will tell you what we would change first, what it depends on, and where we would start.