GCP Cost Optimization Services
Reduce Google Cloud spend through Committed Use Discounts, GKE cluster optimisation, BigQuery cost governance, storage tiering, and systematic elimination of waste across compute, data, and networking.
Why Businesses Need This Service
Google Cloud's pricing model has unique characteristics — Sustained Use Discounts apply automatically, but Committed Use Discounts (CUDs) require planning to capture fully. BigQuery charges by bytes scanned, making query governance critical. GKE clusters commonly run at 30–40% utilisation. GCP Cost Optimization Services address these GCP-specific inefficiencies with deep knowledge of Google Cloud's cost structure.
Key Capabilities
Comprehensive capabilities to address your cloud needs
Committed Use Discount (CUD) modelling and purchase strategy across compute
GKE cluster rightsizing and node auto-provisioning configuration
BigQuery cost governance: query optimisation, slot reservations, and partitioning
Cloud Storage class analysis and lifecycle policy implementation
GCE instance rightsizing using Cloud Monitoring and Recommender API
GCP billing account consolidation, labels, and budget alert engineering
Technologies & Platforms
Industry-leading tools and platforms we use to deliver exceptional results
Technologies
Platforms
Business Outcomes
Measurable results that drive business value
25–45% reduction in GCP spend through CUDs and rightsizing
BigQuery costs reduced 30–60% through query optimisation and slot management
GKE cluster utilisation improved from typical 35% to 70%+
Cloud Storage costs reduced 40% through intelligent lifecycle policies
Full GCP cost attribution by project, label, and team
Common Use Cases
Real-world scenarios where this cloud service delivers value
GCP spend review for organisations with $20K–$2M+ monthly GCP bills
BigQuery cost governance for data teams with large analytical workloads
GKE cost optimisation with right-sized node pools and Spot VMs
Committed Use Discount strategy for steady-state GCE and Cloud SQL
Cloud Storage tiering from Standard to Nearline/Coldline/Archive
GCP project hierarchy and billing account governance design
Typical Architecture
Key components and layers in a typical cloud architecture
Billing Export to BigQuery
Recommender API Dashboard
CUD Tracker
BigQuery Slot Manager
Storage Lifecycle Policies
Budget Alert Automation
Our Implementation Process
A systematic approach that ensures timely delivery and exceeds expectations
GCP Cost Analysis
Export billing data to BigQuery, analyse spend by project and service, identify Sustained vs Committed Use Discount coverage, and model CUD opportunity.
Compute Rightsizing
Use Recommender API and Cloud Monitoring to identify oversized GCE instances, right-size GKE node pools, and optimise Cloud SQL and Cloud Spanner tiers.
CUD Strategy
Model 1-year and 3-year Committed Use Discounts for compute and memory, design purchase plan that maximises discount while maintaining flexibility for growth.
BigQuery Governance
Implement partitioning and clustering for large tables, enforce query preview requirements, configure slot reservations for BI workloads, and establish query cost attribution.
Continuous Governance
Configure GCP Budgets and alerting, enforce resource labels with Org Policy, establish monthly optimisation review, and track CUD utilisation rates.
Industries We Serve
Our cloud services deliver value across diverse industries
AI / Data Platforms
SaaS Platforms
Media & Entertainment
Gaming
Fintech
Healthcare
Cloud Platforms & Tools
Industry-leading platforms and tools we leverage to deliver exceptional results
Technologies
Platforms
Example Success Story
See how we've helped businesses achieve success with cloud solutions
Client Challenge
A data analytics company running on GCP had $180,000/month in cloud costs dominated by BigQuery ($70K) and GKE ($60K). BigQuery costs were unpredictable, GKE clusters ran at 28% utilisation, and CUD coverage was zero.
Cloud Solution Implemented
We implemented BigQuery slot reservations for BI workloads, partitioned the 5 largest tables reducing scanned bytes by 65%, rightsized GKE node pools reducing the cluster count from 8 to 5, and purchased CUDs covering 60% of steady-state compute.
Business Results
$68,000/month reduction (38%) in GCP spend
BigQuery monthly cost from $70K to $28K
GKE utilisation improved from 28% to 71%
CUD coverage established at 60% for compute
Query cost attribution implemented for each data team
Frequently Asked Questions
Common questions about GCP Cost Optimization Services
Committed Use Discounts (CUDs) are 1-year or 3-year commitments to a level of compute usage (measured in vCPUs and memory) in exchange for discounts of 20–57% vs on-demand pricing. Unlike AWS Reserved Instances, GCP CUDs are flexible across machine types within a region, making them easier to manage.
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