Cost Optimization & FinOps

The Hidden Tax on Innovation

Cloud infrastructure was supposed to make IT spending more efficient. Instead, many organizations find themselves with cloud bills that grow faster than their business—and no clear understanding of where the money goes.

The problem isn't the cloud itself. It's the gap between how engineering teams provision infrastructure and how finance teams budget for it. We bridge that gap with FinOps practices that bring accountability, visibility, and optimization to cloud spending.

The FinOps Framework

flowchart TB
    subgraph Inform["Inform"]
        A[Cost Visibility] --> B[Allocation]
        B --> C[Forecasting]
    end

    subgraph Optimize["Optimize"]
        D[Right-sizing] --> E[Reserved Capacity]
        E --> F[Spot/Preemptible]
    end

    subgraph Operate["Operate"]
        G[Governance] --> H[Automation]
        H --> I[Continuous Improvement]
    end

    Inform --> Optimize --> Operate
    Operate --> Inform

Why Cloud Costs Spiral

Understanding the root causes of cloud cost overruns is the first step to controlling them:

The Provisioning Problem

Engineers provision for peak load—then forget about it. A instance sized for Black Friday runs at 10% utilization the other 364 days of the year.

The Orphan Problem

Resources get created for testing, development, or one-off projects. The project ends; the resources keep running and billing.

The Architecture Problem

Some architectures are inherently expensive. A system designed without cost awareness will be expensive regardless of optimization efforts.

pie title Typical Cloud Waste Sources
"Over-provisioned compute" : 35
"Orphaned resources" : 25
"Inefficient storage" : 20
"Network transfer" : 12
"Unused licenses" : 8

Our Optimization Approach

Phase 1: Visibility (Week 1-2)

You can't optimize what you can't see. We start by building comprehensive visibility into your cloud spend:

• Cost allocation - Who's spending what, and why?
• Resource inventory - What's running, where, and at what utilization?
• Trend analysis - Where is spending growing, and is it justified?

Phase 2: Quick Wins (Week 2-4)

Immediate savings opportunities that don't require architectural changes:

• Right-sizing - Matching instance sizes to actual utilization
• Reserved instances - Committing to stable workloads
• Storage tiering - Moving cold data to cheaper storage classes
• Zombie hunting - Terminating unused resources

Phase 3: Architectural Optimization (Week 4+)

Deeper changes that require engineering work but deliver larger savings:

• Spot/Preemptible instances - Using interruptible capacity for fault-tolerant workloads
• Serverless migration - Moving appropriate workloads to pay-per-use models
• Multi-region optimization - Balancing availability requirements against cost
• Caching strategies - Reducing expensive compute and database operations

gantt
    title Cost Optimization Timeline
    dateFormat X
    axisFormat
    section
    Cost visibility setup   :a1, 0, 7d
    Right-sizing            :a2, after a1, 7d
    Reserved instances      :a3, after a1, 14d
    Architecture review     :b1, after a2, 14d
    Spot integration        :b2, after b1, 21d
    Serverless migration    :b3, after b2, 28d

The FinOps Maturity Model

Organizations progress through FinOps maturity in stages:

Most organizations we work with start at "Crawl" and reach "Walk" within the first engagement. Reaching "Run" requires organizational commitment beyond just technical changes.

Multi-Cloud Considerations

Most enterprises operate across multiple cloud providers. Each has unique pricing models and optimization strategies:

AWS

• Reserved Instances & Savings Plans - Commitment discounts up to 72%
• Spot Instances - Up to 90% savings for interruptible workloads
• S3 Intelligent Tiering - Automatic storage optimization

Azure

• Reserved Instances - Similar commitment model to AWS
• Azure Hybrid Benefit - Leverage existing Windows/SQL licenses
• Dev/Test pricing - Significant discounts for non-production

Google Cloud

• Committed Use Discounts - Automatic and custom commitments
• Preemptible VMs - Google's spot equivalent
• Sustained Use Discounts - Automatic discounts for consistent usage

flowchart TB
    subgraph AWS["AWS Optimization"]
        A1[Reserved Instances]
        A2[Spot Instances]
        A3[Savings Plans]
    end

    subgraph Azure["Azure Optimization"]
        B1[Reserved Instances]
        B2[Hybrid Benefit]
        B3[Dev/Test Pricing]
    end

    subgraph GCP["GCP Optimization"]
        C1[Committed Use]
        C2[Preemptible VMs]
        C3[Sustained Use]
    end

    D[FinOps Platform] --> AWS & Azure & GCP

Building FinOps Culture

Technical optimization is only part of the solution. Sustainable cost management requires cultural change:

1. Cost awareness - Engineers understand the cost of their decisions
2. Accountability - Teams own their cloud spend
3. Incentive alignment - Savings flow back to teams
4. Continuous improvement - Optimization is ongoing, not one-time

The 127K Difference

What sets our cost optimization apart:

1. Engineering depth - We understand the systems we're optimizing
2. Multi-cloud experience - AWS, Azure, GCP optimization expertise
3. Architecture alignment - Cost optimization that improves performance
4. Knowledge transfer - Your team learns to optimize continuously
5. Business focus - We optimize for business outcomes, not just lower bills