Cloud Cost Optimization Services for AWS, Azure & GCP
Relevance Lab helps enterprises reduce cloud costs without slowing engineering down — through rightsizing, reserved capacity and savings plans, storage tiering, and automated governance across AWS, Azure and Google Cloud.
- Discover & BaselineCost and usage audit across AWS, Azure and GCP to surface waste, idle resources and commitment coverage gaps.
- Rightsize & CommitRightsizing, autoscaling and commitment-based discounts through Reserved Instances and Savings Plans.
- Tier & AutomateStorage tiering, lifecycle policies and automated workflows that keep waste from creeping back in.
- Govern & SustainTagging standards, budgets, alerts and showback/chargeback so savings hold up under continuous review.
Quick answerCloud cost optimization is the ongoing practice of reducing AWS, Azure and Google Cloud spend without sacrificing performance or reliability — through rightsizing, reserved capacity, storage tiering and automated governance. Relevance Lab delivers cloud cost optimization as a managed service across all three major cloud platforms and AI/GPU workloads.
Turning cloud spend into a managed, shrinking line item
Cloud cost optimization is the tactical, execution layer of FinOps — the rightsizing, commitment purchasing and automation that actually reduce the bill. Done well, it compounds: savings from rightsizing free up budget for reserved capacity, and governance keeps waste from creeping back in as your environment grows.
As a cloud cost optimization services provider, Relevance Lab runs this as a continuous practice — not a one-time audit — across compute, storage, and the AI/GPU workloads that are now among the fastest-growing, least-optimized parts of the cloud bill.
What a Relevance Lab cost optimization engagement gets you
- Rightsizing and autoscaling tuned to real usage, not peak estimates
- Reserved Instance, Savings Plan and committed use discount coverage
- Storage tiering and lifecycle policies that eliminate silent waste
- Tagging, budgets and showback so every team owns its own spend
The cloud cost problems optimization solves
Most cloud bills carry more waste than teams realize. Here's where it typically hides.
Idle & oversized resources
Instances, databases and clusters sized for peak demand keep running at a fraction of utilization long after the peak has passed.
Missed commitment discounts
Without continuous analysis, Reserved Instance and Savings Plan coverage lags behind actual usage, leaving on-demand pricing on the table.
Storage sprawl
Orphaned snapshots, unattached volumes and data sitting in the wrong storage tier quietly inflate the bill month over month.
No rightsizing automation
Manual, point-in-time rightsizing reviews can't keep pace with environments that scale and change every day.
Weak tagging & showback
Without consistent tagging, nobody can attribute spend to a team or product — so nobody owns the number.
AI & GPU compute waste
Underutilized GPU clusters and inefficient inference configurations are among the fastest-growing sources of avoidable cloud spend.
Why continuous cost optimization beats a one-off RI purchase
Buying reserved capacity once is a start. Sustaining savings as usage shifts takes an ongoing practice.
| Dimension | One-time RI / discount purchase | Continuous cost optimization |
|---|---|---|
| Coverage | Fixed at time of purchase | Rebalanced continuously as usage changes |
| Rightsizing | Not addressed | Instances and databases resized to actual load |
| Storage | Out of scope | Tiering & lifecycle policies applied automatically |
| Accountability | Owned by whoever made the purchase | Shared via tagging, budgets & showback |
| Durability of savings | Erodes as workloads change | Sustained via governance & automation |
Four pillars of a Relevance Lab cost optimization engagement
Each pillar can stand alone or run together as a continuous, managed practice.
Rightsizing & Automated Scaling
Continuous analysis of compute, database and container usage to rightsize instances and automate scaling to real demand.
- Compute & database rightsizing
- Autoscaling policy tuning
- Container & Kubernetes cost tuning
Reserved Capacity & Savings Plans
Commitment coverage analysis and management across Reserved Instances, Savings Plans and committed use discounts.
- Commitment coverage & utilization analysis
- RI / Savings Plan / CUD purchasing strategy
- Spot instance strategy for flexible workloads
Storage Tiering & Lifecycle Management
Lifecycle policies and tiering across object, block and file storage so data lands on the right storage class automatically.
- Automated storage tiering
- Orphaned volume & snapshot cleanup
- Backup & archive cost optimization
Governance, Tagging & Showback
Tagging standards, budgets and alerts paired with showback/chargeback so every team is accountable for its own spend.
- Tagging policy & enforcement
- Budgets, alerts & guardrails
- Showback & chargeback reporting
Cost optimization expertise across AWS, Azure, GCP and your AI stack
- Cost Explorer & Compute Optimizer
- Reserved Instances, Savings Plans & Spot
- S3 storage class & lifecycle tuning
- Azure Advisor & Cost Management
- Reservations & Azure Hybrid Benefit
- Blob storage tiering & lifecycle rules
- Recommender & Active Assist
- Committed use discounts
- Cloud Storage class & lifecycle policies
Running GenAI workloads? Our cloud cost optimization practice pairs with RLCatalyst for automated monitoring and remediation of GPU and inference spend.
Explore cloud cost optimization by platform and practice
Each of these covers the tools, levers and governance specific to that platform or practice in more depth.
AWS FinOps
Cost Explorer, Compute Optimizer, Reserved Instances, Savings Plans and Spot strategy for AWS.
Explore AWS FinOpsAzure FinOps
Cost Management + Advisor, Reservations and Azure Hybrid Benefit for Microsoft Azure.
Explore Azure FinOpsGCP FinOps
Recommender, Active Assist and committed use discounts for Google Cloud.
Explore GCP FinOpsCloud Cost Management
Consolidated cost visibility, allocation, forecasting and reporting across every cloud you run.
Explore Cloud Cost ManagementCloud Cost Governance
Tagging standards, budgets, guardrails and showback/chargeback that keep spend accountable.
Explore Cloud Cost GovernanceCloud Consolidation
Merge scattered accounts, subscriptions and tools into a leaner, better-negotiated footprint.
Explore Cloud ConsolidationFinOps and cloud cost optimization, tuned by industry
Every industry hits cloud cost management differently. Our FinOps services adapt the same core practice to the constraints that matter most in your sector.
Financial Services
FinOps for banks, insurers and fintechs balances aggressive cloud cost optimization with the audit trails, tagging discipline and regulatory reporting that financial services compliance demands.
- Cost governance mapped to compliance & audit needs
- Chargeback across business units and trading desks
- Optimization for high-volume transaction workloads
Hi-Tech
Fast-scaling product and engineering teams get real-time cloud cost management and AI FinOps guardrails that keep pace with rapid deployment cycles, without slowing engineering down.
- Cost visibility by product, team and environment
- AI FinOps for GPU-heavy training and inference
- Automated rightsizing that keeps up with scale
Healthcare & Life Sciences
Research computing, genomics and clinical workloads bring bursty, high-cost cloud usage. Our FinOps services bring cost accountability without compromising data governance or research velocity.
- Cost controls for research & HPC workloads
- Governance aligned to healthcare data compliance
- Grant- and project-based cost allocation
Blogs and case studies on cloud cost optimization
Struggling with Unmanaged Cloud Assets across Providers AWS, Azure, & GCP?
A practical framework for auditing unmanaged, unmonitored assets across AWS, Azure and GCP and turning them into a cost-optimized, governed environment.
Read MoreCase StudyBeyond Migration: 150+ Apps' Journey to the Cloud with Zero Downtime
How a large publisher cut data center costs by 40% by rationalizing 150+ applications and retiring legacy server footprint during an AWS migration.
Read the Case StudyBlogCloud Management, Automation, DevOps and AIOps: Key Offerings from Relevance Lab
How an automation-first approach to cloud management helped enterprise customers cut IT spend by 30% over three years while shipping faster.
Read MoreReady to go beyond cost cutting? Explore our full FinOps services
Pair cloud cost optimization with the governance, forecasting and cross-team accountability of a full FinOps practice — including AI FinOps for your GPU and LLM workloads.
Cloud cost optimization: frequently asked questions
Content last reviewed: September 2026
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