Cloud Cost Optimization
Infrastructure audit, right-sizing, and cost governance — cut cloud waste without cutting performance.
Systematic cloud cost audit and ongoing cost governance — identify waste, right-size resources, and build tagging and budgeting practices that keep bills predictable. Designed for teams post-fundraise, companies with growing cloud bills, and engineering teams that have never done a structured cost review.
What's Included
- Cloud cost audit and baseline report
- Resource right-sizing and reservation planning
- Unused resource identification and cleanup
- Cost allocation tagging strategy
- Reserved instances and savings plans analysis
- Budget alerts and anomaly detection setup
- Cost governance tooling configuration
- Cost governance policy documentation
Tools & Technologies
- AWS Cost Explorer
- Azure Cost Management
- GCP Billing
- Terraform
- Cost Analytics Platforms
- Custom Dashboards
Who This Is For
Startups with growing cloud bills, companies post-fundraise with no cost governance, and engineering teams that have never done a proper cloud audit.
Frequently Asked Questions
- How much can we realistically save on our cloud bill?
- Most environments we review save 20–40% in the first 90 days — primarily from eliminating unused resources, right-sizing over-provisioned instances, and converting on-demand spend to reserved capacity. Savings depend on your current environment, but almost every unreviewed cloud account has significant waste.
- What is the difference between right-sizing and reserved instances?
- Right-sizing means reducing the compute size of instances that are over-provisioned for their actual workload. Reserved instances (or savings plans) are a billing commitment that reduces the cost of resources you know you will keep running. Both reduce cost but through different mechanisms — right-sizing reduces the resource footprint, reservations reduce the unit price.
- Will cost optimization affect our application performance?
- Done correctly, no. We baseline performance before making any changes and validate after. Right-sizing uses actual CPU, memory, and I/O utilization data — we only reduce capacity where there is clear headroom. Performance is a hard constraint in our optimization process.