Skip to main content

Optimizing Costs

Transform uncontrolled cloud spending into strategic resource allocation through the FinOps lifecycle: Inform, Optimize, and Operate.

When to Use​

Use this skill when:

  • Reducing cloud spend by 15-40% through systematic optimization
  • Implementing cost visibility dashboards and allocation tracking
  • Establishing budget alerts and anomaly detection
  • Optimizing Kubernetes resource requests and cluster efficiency
  • Managing Reserved Instances, Savings Plans, or Committed Use Discounts
  • Automating idle resource cleanup and right-sizing recommendations
  • Setting up showback/chargeback models for internal teams
  • Preventing cost overruns through CI/CD cost estimation (Infracost)
  • Responding to finance team requests for cloud cost reduction

Key Features​

1. FinOps Lifecycle​

The Three Phases:

┌─────────────────────────────────────────────────────┐
│  INFORM → OPTIMIZE → OPERATE (continuous loop)      │
│    ↓         ↓           ↓                          │
│ Visibility  Action   Automation                     │
└─────────────────────────────────────────────────────┘

Inform Phase: Establish cost visibility

  • Enable cost allocation tags (Owner, Project, Environment)
  • Deploy real-time cost dashboards for engineering teams
  • Integrate cloud billing data (AWS CUR, Azure Consumption API, GCP BigQuery)
  • Set up Kubernetes cost monitoring (Kubecost, OpenCost)

Optimize Phase: Take action on cost drivers

  • Purchase commitment-based discounts (40-72% savings)
  • Right-size over-provisioned resources (target 60-80% utilization)
  • Implement spot/preemptible instances for fault-tolerant workloads
  • Clean up idle resources (unattached volumes, old snapshots)

Operate Phase: Automate and govern

  • Budget alerts with cascading notifications (50%, 75%, 90%, 100%)
  • Automated cleanup scripts for idle resources
  • CI/CD cost estimation to prevent surprise increases
  • Continuous monitoring with anomaly detection

2. Commitment-Based Discounts​

Reserved Instances (RIs): 40-72% discount for 1-3 year commitments

  • Standard RI: Instance type locked, highest discount (60% for 3-year)
  • Convertible RI: Flexible instance types, moderate discount (54% for 3-year)
  • Use for: Databases (RDS, ElastiCache), stable production EC2 workloads

Savings Plans: Flexible compute commitments

  • Compute Savings Plans: Applies to EC2, Fargate, Lambda (54% discount for 3-year)
  • EC2 Instance Savings Plans: Tied to instance family (66% discount for 3-year)
  • Use for: Workloads that change instance types or regions

GCP Committed Use Discounts (CUDs): 25-70% discount

  • Resource-based CUDs: Commit to vCPU, memory, GPUs
  • Spend-based CUDs: Commit to dollar amount (flexible)
  • Sustained Use Discounts: Automatic 20-30% discount for sustained usage (no commitment)

Decision Framework:

Reserve when:
├─ Workload is production-critical (24/7 uptime required)
├─ Usage is predictable (stable baseline over 6+ months)
├─ Architecture is stable (unlikely to change instance types)
└─ Financial commitment acceptable (1-3 year lock-in)

Use On-Demand when:
├─ Development/testing environments
├─ Unpredictable spiky workloads
├─ Short-term projects (<6 months)
└─ Evaluating new instance types

3. Spot and Preemptible Instances​

Discount: 70-90% off on-demand pricing (interruptible with 2-minute warning)

Use Spot For:

  • CI/CD workers
  • Batch jobs
  • ML training (with checkpointing)
  • Kubernetes workers
  • Data analytics

Avoid Spot For:

  • Stateful databases
  • Real-time services
  • Long-running jobs without checkpointing

Best Practices:

  • Diversify instance types and spread across Availability Zones
  • Implement graceful shutdown handlers
  • Auto-fallback to on-demand when capacity unavailable
  • Kubernetes: Mix 70% spot + 30% on-demand nodes with taints/tolerations

4. Right-Sizing Strategies​

Target Utilization: 60-80% average (leave headroom for spikes)

Compute Right-Sizing:

  • Analyze actual CPU/memory utilization over 30+ days
  • Downsize instances with <40% average utilization
  • Consolidate underutilized workloads
  • Switch instance families (compute-optimized vs. memory-optimized)

Database Right-Sizing:

  • Analyze connection pool usage (max connections vs. allocated)
  • Downgrade storage IOPS if utilization <50%
  • Evaluate read replica necessity (can caching replace it?)
  • Consider serverless options (Aurora Serverless, Azure SQL Serverless)

Kubernetes Right-Sizing:

  • Set requests = average usage (not peak)
  • Set limits = 2-3x requests (allow bursting)
  • Use Vertical Pod Autoscaler (VPA) for automated recommendations
  • Identify pods with 0% CPU usage (candidates for consolidation)

Storage Right-Sizing:

  • Delete unattached volumes (EBS, Azure Disks, GCP Persistent Disks)
  • Delete old snapshots (>90 days, retention policy not required)
  • Implement lifecycle policies (S3 Intelligent-Tiering, Azure Blob Lifecycle)
  • Compress/deduplicate data

5. Kubernetes Cost Management​

Resource Requests and Limits:

# Set requests = average usage (enables efficient bin-packing)
resources:
  requests:
    cpu: 500m        # 0.5 CPU cores (average usage)
    memory: 1Gi      # 1 GiB memory (average usage)
  limits:
    cpu: 1500m       # 1.5 CPU cores (3x requests, allows bursting)
    memory: 3Gi      # 3 GiB memory (3x requests)

Namespace Quotas: Prevent runaway resource consumption

  • ResourceQuota: Limit total CPU/memory per namespace
  • LimitRange: Default/max requests per pod
  • PriorityClass: Ensure critical pods get resources

Cluster Autoscaling:

  • Scale down idle nodes to reduce costs
  • Scale-to-zero for dev clusters during off-hours
  • Use multiple node pools (spot + on-demand mix)
  • Set max node limits to prevent overspend

Cost Visibility:

  • Deploy Kubecost or OpenCost for namespace-level cost tracking
  • Allocate costs by labels (team, project, environment)
  • Track idle cost (cluster capacity not allocated to workloads)
  • Generate showback/chargeback reports

6. Cost Visibility and Monitoring​

Tagging for Cost Allocation:

Required Tags:

  • Owner or Team - Responsible team/department
  • Project or Application - Business unit or application name
  • Environment - prod, staging, dev, test
  • CostCenter - Finance cost center code

Monitoring and Dashboards:

Native Cloud Tools:

  • AWS Cost Explorer: Analyze spending patterns, forecast costs
  • Azure Cost Management + Billing: Budget tracking, cost analysis
  • GCP Cloud Billing: BigQuery export for custom analysis

Third-Party Platforms:

  • Kubecost: Kubernetes cost visibility and optimization
  • CloudZero: Unit cost economics, anomaly detection
  • CloudHealth: Multi-cloud cost management
  • Infracost: Terraform cost estimation in CI/CD

Key Metrics to Track:

  • Total monthly cloud spend (trend over time)
  • Cost per service/team/project (allocation accuracy)
  • Unit cost metrics (cost per customer, cost per transaction)
  • Reserved Instance/Savings Plan utilization (target >95%)
  • Idle resource waste (target <5% of total spend)
  • Budget variance (forecasted vs. actual)

7. Budget Alerts and Anomaly Detection​

Cascading Budget Alerts:

50% of budget  → Email to team lead (informational)
75% of budget  → Email + Slack to team (warning)
90% of budget  → Email + Slack + PagerDuty (urgent)
100% of budget → Automated shutdown (non-prod only) or escalation

Anomaly Detection: Alert on unexpected cost spikes

  • >20% cost increase week-over-week
  • >$500 unexpected daily cost spike
  • New resource types (unusual spend patterns)

Quick Start​

Enable AWS Cost Allocation Tags​

# Using AWS CLI
aws ce create-cost-allocation-tag --key Environment
aws ce create-cost-allocation-tag --key Project

Deploy Kubecost for Kubernetes​

# Install via Helm
helm repo add kubecost https://kubecost.github.io/cost-analyzer/
helm install kubecost kubecost/cost-analyzer \
  --namespace kubecost \
  --create-namespace \
  --set kubecostToken="your-token"

Set Up Budget Alerts (AWS)​

aws budgets create-budget \
  --account-id 123456789012 \
  --budget file://budget.json \
  --notifications-with-subscribers file://notifications.json

Implementation Checklist​

Phase 1: Establish Visibility (Week 1-2)​

  • Enable cost allocation tags (Owner, Project, Environment)
  • Activate cost allocation tags in cloud billing console
  • Deploy Kubecost for Kubernetes cost visibility (if using K8s)
  • Create cost dashboards (Grafana, CloudWatch, Azure Monitor, GCP)
  • Set up weekly cost reports (emailed to team leads)

Phase 2: Set Up Governance (Week 2-3)​

  • Create budget alerts (50%, 75%, 90%, 100% thresholds)
  • Enable anomaly detection (>20% WoW increase)
  • Implement tagging policy enforcement (Azure Policy, AWS Config, GCP Org Policy)
  • Establish showback reports (cost by team/project)
  • Document cost ownership (who owns which services)

Phase 3: Quick Wins (Week 3-4)​

  • Delete idle resources (unattached volumes, old snapshots)
  • Stop/terminate unused development instances
  • Right-size top 10 over-provisioned instances (<40% utilization)
  • Implement S3 Intelligent-Tiering or lifecycle policies
  • Evaluate Reserved Instance/Savings Plan coverage

Phase 4: Commitment Discounts (Month 2)​

  • Analyze 6-12 months usage history
  • Calculate baseline usage for commitment sizing
  • Purchase Reserved Instances for databases
  • Purchase Savings Plans for compute workloads
  • Monitor RI/SP utilization (target >95%)

Phase 5: Automation (Month 2-3)​

  • Deploy automated cleanup scripts (weekly schedule)
  • Integrate Infracost into CI/CD pipelines
  • Implement auto-shutdown for dev/test environments (off-hours)
  • Enable Vertical Pod Autoscaler (VPA) for K8s rightsizing
  • Set up Spot instance automation (Spot.io, CAST AI, or native)

Phase 6: Continuous Optimization (Ongoing)​

  • Weekly cost reviews with engineering teams
  • Monthly optimization sprints (top cost drivers)
  • Quarterly commitment adjustments (RI/SP coverage)
  • Annual FinOps maturity assessment

Common Pitfalls​

Pitfall 1: No Cost Visibility​

❌ Problem: Finance team sees cloud bill at end of month, surprises everywhere ✅ Solution: Deploy real-time cost dashboards, daily Slack reports to engineering teams

Pitfall 2: Reserved Instance Underutilization​

❌ Problem: Purchased 100 RIs, only using 60 (40% wasted commitment) ✅ Solution: Monitor RI utilization weekly (target >95%), sell unused RIs on marketplace

Pitfall 3: Missing Kubernetes Resource Requests​

❌ Problem: Pods with no requests set → inefficient bin-packing → wasted nodes ✅ Solution: Use VPA to auto-generate recommendations, enforce via admission control

Pitfall 4: Idle Resources Not Cleaned Up​

❌ Problem: 50 stopped EC2 instances (still paying for EBS), 200 unattached volumes ✅ Solution: Weekly automated cleanup of idle resources >7 days old

Pitfall 5: No Budget Alerts​

❌ Problem: Accidentally left test cluster running, $10K bill surprise ✅ Solution: Budget alerts at 50%, 75%, 90%, 100% with Slack/PagerDuty notifications

  • resource-tagging: Cost allocation tags enable showback/chargeback models
  • operating-kubernetes: K8s rightsizing, VPA, cluster autoscaling
  • writing-infrastructure-code: Infracost for Terraform cost estimation
  • deploying-on-aws: AWS-specific cost optimization tactics
  • deploying-on-gcp: GCP-specific optimizations
  • deploying-on-azure: Azure-specific optimizations
  • engineering-platforms: Internal FinOps platforms and self-service dashboards
  • planning-disaster-recovery: Balance cost vs. RTO/RPO

Key Takeaways​

  1. FinOps is a Culture: Collaboration between finance, engineering, and operations
  2. Visibility First: Can't optimize what can't measure (tags + dashboards mandatory)
  3. Commitment = Savings: Reserved Instances/Savings Plans provide 40-72% discounts
  4. Right-Size Continuously: Target 60-80% utilization (leave headroom for spikes)
  5. Automate Cleanup: Idle resources are 100% waste (weekly automated deletion)
  6. Kubernetes Costs Hidden: Use Kubecost/OpenCost for namespace-level visibility
  7. Shift-Left Cost Awareness: Infracost in CI/CD prevents surprise cost increases
  8. Budget Alerts Prevent Overspend: Cascading notifications at 50%, 75%, 90%, 100%
  9. Spot for Fault-Tolerant Workloads: 70-90% discount (CI/CD, batch jobs, ML training)
  10. Unit Cost Metrics Drive Value: Track cost per customer, cost per transaction

References​

  • Full skill documentation: /skills/optimizing-costs/SKILL.md
  • FinOps foundations: /skills/optimizing-costs/references/finops-foundations.md
  • Commitment strategies: /skills/optimizing-costs/references/commitment-strategies.md
  • Kubernetes cost optimization: /skills/optimizing-costs/references/kubernetes-cost-optimization.md
  • Tagging for cost allocation: /skills/optimizing-costs/references/tagging-for-cost-allocation.md
  • Cloud-specific tactics: /skills/optimizing-costs/references/cloud-specific-tactics.md
  • Tools comparison: /skills/optimizing-costs/references/tools-comparison.md