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Cost Review & FinOps Checklist

Cloud cost optimization strategy covering resource sizing, reserved capacity, spot instances, data costs, and budget controls

TL;DR​

Cloud costs grow quickly without discipline. FinOps is a shared responsibility between engineering and finance teams to optimize cloud spending. This checklist covers right-sizing resources, leveraging commitment discounts, using spot instances, managing data costs, and implementing budget controls.

Learning Objectives​

After using this checklist, you will be able to:

  • Right-size cloud resources based on actual usage
  • Implement commitment discounts (reserved instances) effectively
  • Leverage spot instances for fault-tolerant workloads
  • Optimize data transfer and storage costs
  • Establish budget controls and cost alerts
  • Create a culture of cost awareness

Cost Optimization Process​

Resource Sizing & Optimization​

Current State Analysis​

Cost Data Collection

  • Cloud cost reports available (AWS Cost Explorer, GCP BigQuery, Azure Cost Management)
  • Costs broken down by service, environment, team, project
  • Cost trends analyzed over 3-6 month period
  • Cost anomalies investigated and explained
  • Accurate cost allocation applied (tagging, chargeback)

Usage Analysis

  • Compute instances analyzed for utilization (CPU, memory)
  • Storage analyzed for growth and churn rates
  • Network bandwidth usage patterns understood
  • Database workloads (on-demand vs. reserved vs. serverless) analyzed
  • Unused resources identified (stopped instances, orphaned disks)

Right-Sizing​

Compute Optimization

  • Instance types evaluated for actual workload needs
  • Instances with <30% CPU utilization identified for downsizing
  • Instances with >80% utilization identified for upsizing
  • Serverless options evaluated (Lambda, Cloud Functions) vs. containers
  • Right-sizing changes tested in non-production before production deployment

Memory & Storage Optimization

  • Memory allocation matches actual peak usage (not pessimistic estimates)
  • Disk overprovisioning identified and eliminated
  • Database instance sizing reviewed and optimized
  • Unused storage volumes and backups cleaned up

Savings From Right-Sizing

  • Potential savings quantified and tracked
  • Savings prioritized (highest impact first)
  • Changes implemented incrementally with monitoring

Commitment & Discount Programs​

Reserved Instances & Commitments​

Commitment Analysis

  • Current and 3-year cost forecasts prepared
  • Workload stability assessed (can commit for 1-3 years?)
  • Reserved instance utilization analyzed (are current commitments fully utilized?)
  • Commitment expiration dates tracked and reviewed
  • Cost savings from commitments calculated

Commitment Strategy

  • Reserved instances purchased for 80%+ of stable, on-demand usage
  • 1-year commitments for workloads with some growth uncertainty
  • 3-year commitments for stable, mature workloads
  • Commitment flexibility considered (upfront vs. partial upfront)
  • Unused commitments reallocated or sold

Savings Plan Programs

  • Compute Savings Plans evaluated (more flexible than RIs)
  • Storage Savings Plans for predictable data storage costs
  • Commitment-based discounts prioritized for largest spend categories

Spot & Preemptible Instances​

Fault-Tolerant Workload Optimization​

Spot Instance Candidates

  • Batch jobs and data processing workloads identified
  • Fault-tolerant services (can tolerate interruptions) identified
  • Cost savings from spot instances calculated (typically 70-90% discount)
  • Interruption impact on operations understood

Spot Instance Implementation

  • Multi-instance types and availability zones used for resilience
  • Graceful termination handling implemented
  • Fallback to on-demand instances configured
  • Spot price monitoring and alerting configured
  • Cost tracking separates spot from on-demand spending

Data Transfer & Network Costs​

Data Transfer Optimization​

Data Egress Analysis

  • Data egress costs identified and quantified
  • Egress destinations mapped (internet, other regions, etc.)
  • Unnecessary data movement eliminated
  • CDN usage evaluated for public content
  • Cross-region replication requirements justified

Data Transfer Cost Reduction

  • Redundant cross-region transfers eliminated
  • CloudFront (or equivalent) used for frequently accessed content
  • Data caching strategies implemented to reduce transfer volume
  • API pagination implemented to avoid unnecessary data transfer
  • Compression enabled for data transfer (gzip, brotli)

Network Optimization​

Private Network Usage

  • Services kept within same region when possible (no cross-region traffic)
  • Private links/peering used instead of internet gateway
  • NAT gateway costs understood and minimized
  • VPC endpoints used for AWS services (no internet gateway)

Bandwidth Reduction

  • Load balancer placement optimized
  • Unnecessary traffic patterns identified and eliminated
  • Data filtering at source reduces transfer volume

Storage & Database Optimization​

Storage Tiering​

Storage Lifecycle Policies

  • Hot storage (frequently accessed) uses high-performance tiers
  • Warm storage (occasional access) moves to standard tier after 30 days
  • Cold storage (archive) moves to glacier/archive tier after 90 days
  • Automatic lifecycle policies configured and enforced
  • Savings from tiering quantified

Storage Cleanup

  • Duplicate data identified and deduplicated
  • Unused backups deleted (retention policies enforced)
  • Unused snapshots cleaned up
  • Empty S3 buckets and storage accounts removed
  • Data compression evaluated for large datasets

Database Optimization​

Database Workload Assessment

  • On-demand usage patterns analyzed
  • Scheduled/batch workloads identified for provisioned capacity
  • Serverless database options evaluated
  • Read replicas justified and optimized

Database Cost Reduction

  • Multi-AZ replication evaluated (necessary for high availability?)
  • Index optimization reduces query costs
  • Unused indexes and tables removed
  • Query optimization reduces database load
  • Connection pooling reduces connection overhead

Budget Management & Controls​

Budget & Cost Alerts​

Budget Planning

  • Monthly, quarterly, and annual budgets established
  • Budgets broken down by service, team, environment
  • Historical spending trends used for forecasting
  • Growth projections incorporated into budgets
  • Contingency buffers included (typically 10-15%)

Cost Alerts & Thresholds

  • Alerts configured at 50%, 75%, 90%, and 100% of budget
  • Alert escalation paths defined (who is notified)
  • Anomaly detection configured to catch unexpected cost spikes
  • Cost tracking updated in real-time (not just monthly)
  • Teams have visibility into their costs (cost allocation)

Accountability & Ownership​

Cost Attribution

  • All resources tagged for cost center, project, environment
  • Tagging compliance enforced through policy
  • Cost reports available by team/project
  • Cost responsibility assigned to specific individuals/teams

Cost Governance

  • Cost optimization goals established and tracked
  • Quarterly cost reviews conducted with stakeholders
  • Approval required for high-cost resources
  • Cost impact assessment required for architectural decisions
  • Chargeback or showback model implemented

Cost Optimization Best Practices​

FinOps Principles

Make Cost Visible: Teams can't optimize what they can't see. Break down costs by service, team, and project so everyone understands their impact.

Allocate Costs Accurately: Accurate cost attribution drives accountability. Use comprehensive tagging and automation to ensure costs are properly assigned.

Right-Size Ruthlessly: Oversized instances waste money every month. Regularly review utilization and right-size to actual needs.

Exploit Discounts Strategically: Commit discounts (RIs, Savings Plans) offer substantial savings but require forecasting. Combine commitments with on-demand and spot for flexibility.

Automate Cost Optimization: Manually managing resources is expensive. Use auto-scaling, lifecycle policies, and cleanup automation.

Culture Over Tools: Spreadsheets don't reduce costs—culture does. Build a culture where engineers understand and care about costs.

Common FinOps Mistakes​

Mistakes to Avoid

Buying commitments without analysis: 3-year commitments on unstable workloads lock in waste. Analyze workload stability first.

Forgetting to remove old resources: Stopped instances, old snapshots, and orphaned disks quietly accumulate. Implement automated cleanup.

Only reviewing costs monthly: Cost problems appear quickly in cloud. Set up daily/weekly alerts and reviews.

Treating cost optimization as fire-and-forget: Savings creep over time as usage grows. Make optimization an ongoing process.

Not using spot instances: Fault-tolerant workloads can save 70%+ with spot instances. Leave this money on the table and you're optimizing incompletely.

Overprovisioning "just in case": Overprovisioning adds cost without benefitting performance. Right-size based on actual needs.

Cost Review Workflow​

  1. Review Spending

    • Compare actual spending vs. budget
    • Identify cost anomalies and spikes
    • Investigate root causes

  2. Trend Analysis

    • Track cost trends month-over-month
    • Identify growth areas requiring attention
    • Validate forecast accuracy

  3. Alerts & Action

    • Respond to budget alerts
    • Adjust forecasts based on trends
    • Flag large variances for investigation

Self-Check​

Before finalizing your cost review, verify:

  • Current spending is analyzed and understood
  • Resources are appropriately sized to actual usage
  • Commitment discount strategy is in place
  • Data transfer and storage costs are optimized
  • Budget controls and alerts are configured
  • Cost responsibility is assigned to teams
  • Cost metrics are tracked and reported regularly
  • Optimization initiatives have clear ownership and targets
  • Cost impact is assessed for major architectural decisions

One Takeaway​

One Takeaway

Cloud costs are a feature, not a bug. Treating cost optimization as part of normal operations—rather than an afterthought—builds sustainable infrastructure that delivers value without waste.

Next Steps​

  1. Analyze current spending across all cloud services
  2. Identify top 5 optimization opportunities by impact
  3. Implement right-sizing for underutilized instances
  4. Establish commitment strategy (RIs, Savings Plans)
  5. Configure budget alerts and cost tracking
  6. Conduct quarterly reviews with stakeholders

References​