Back to case studies
GCP Technology / SaaS Global

FinOps Program and Platform Cost Optimization

Implementation of FinOps practices and platform optimization for a SaaS company, achieving 38% cost reduction while improving performance and establishing sustainable cloud governance.

Duration4 months
Company Size200-500 employees
SPKR Team5 specialists
38%
Cost reduction achieved ($180K to $112K/mo)
100%
Cost attribution to products/teams
65%
GKE utilization (vs. 15% before)
$820K
Projected annual savings
45%
BigQuery cost reduction
3 weeks
Time to first 20% savings

Challenge

A growing SaaS company with a data analytics platform saw their GCP costs increase from $80K to $180K/month in 18 months without proportional user growth. Engineering teams had no visibility into costs, leading to over-provisioned resources and wasteful spending. The CFO demanded 30% cost reduction without impacting platform performance.

Key Challenges:

  • Cloud costs increased 125% in 18 months ($80K to $180K/month)
  • Zero cost allocation - impossible to attribute costs to products
  • Over-provisioned GKE clusters running at 15% average utilization
  • BigQuery costs growing 20% monthly with no data lifecycle policies
  • No commitment discounts despite predictable baseline workloads
  • Development environments running 24/7 with production-grade specs

Solution

We implemented a comprehensive FinOps program combining technical optimization with organizational practices. This included implementing GCP's native cost management tools, establishing tagging standards for cost allocation, and creating automated policies for resource lifecycle management. We also implemented commitment-based discounts for stable workloads.

What We Implemented:

  • Comprehensive resource tagging for 100% cost attribution
  • GKE cluster rightsizing with vertical and horizontal pod autoscaling
  • BigQuery slot reservations and data lifecycle policies
  • Committed Use Discounts for baseline compute workloads
  • Automated dev environment scheduling (running only business hours)
  • FinOps dashboards with team-level accountability

Solution Architecture

Component 1
GKE Autopilot for automatic node management and optimization
Component 2
BigQuery flat-rate slots with partitioning and clustering
Component 3
Cloud Storage lifecycle policies with Nearline/Coldline tiering
Component 4
Committed Use Discounts (CUDs) for stable workloads
Component 5
Cloud Billing budgets and alerts with Pub/Sub notifications
Component 6
Custom cost dashboards in Looker Studio
Component 7
Spot VMs for fault-tolerant batch workloads
Component 8
Preemptible VMs for development environments

Cost Management

Cloud BillingLooker StudioBigQuery BI Engine

Resource Optimization

GKE Cost AllocationRecommender APIActive Assist

Automation

Cloud SchedulerCloud FunctionsTerraform

Observability

Cloud MonitoringKubecostCustom Metrics

Governance

Organization PoliciesResource ManagerIAM

Project Phases

1

Cost Assessment

2 weeks

Deep analysis of 6 months billing data, resource utilization mapping, and waste identification

2

Quick Wins Implementation

3 weeks

Immediate actions: unused resources cleanup, dev environment scheduling, obvious rightsizing

3

Tagging & Governance

4 weeks

Implementation of labeling standards, budget alerts, and cost allocation reports

4

Platform Optimization

6 weeks

GKE rightsizing, BigQuery optimization, storage tiering, and commitment purchases

5

FinOps Operationalization

2 weeks

Monthly review process, team training, and continuous optimization playbooks

What We Delivered

  • Complete cost assessment report with optimization roadmap
  • Resource labeling strategy and enforcement policies
  • FinOps dashboards with team-level cost views
  • Automated resource scheduling for non-production
  • Committed Use Discount purchase recommendations
  • Monthly FinOps review process and playbooks
  • BigQuery optimization guide and data governance policies
  • Training sessions for engineering and finance teams
"We exceeded our 30% cost reduction target while actually improving platform performance. The FinOps practices SPKR established have become part of our engineering culture - every team now owns their cloud costs."
VP of Engineering — SaaS Analytics Company

Technologies

GCPGKEBigQueryCloud StorageLooker StudioKubecostTerraformCloud Functions

Want results like these for your company?

Schedule a free conversation with our specialists and discover how we can help.

Schedule a call