Optimize cloud costs
Cased analyzes your AWS infrastructure to identify cost optimization opportunities, including underutilized resources, idle instances, oversized services, and inefficient configurations that are driving up your cloud costs.
Cloud costs can quickly spiral out of control without proper monitoring and optimization. Cased provides intelligent cost analysis that goes beyond simple billing reports to identify specific optimization opportunities and provide actionable recommendations for reducing your AWS spend.
How it Works
Section titled “How it Works”Cased’s cost optimization combines real-time infrastructure analysis with usage pattern recognition:
- Resource Discovery: Scan your AWS infrastructure to catalog all resources and their configurations
- Utilization Analysis: Monitor CPU, memory, network, and storage utilization patterns over time
- Cost Correlation: Correlate resource usage with AWS billing data to identify cost drivers
- Optimization Identification: Use AI to identify specific optimization opportunities
- Recommendation Generation: Provide actionable recommendations with estimated savings
Cost Optimization Categories
Section titled “Cost Optimization Categories”Compute Optimization
Section titled “Compute Optimization”- Right-sizing EC2 Instances: Identify oversized instances that can be downsized
- Reserved Instance Opportunities: Recommend Reserved Instance purchases for predictable workloads
- Spot Instance Usage: Identify workloads suitable for Spot instances
- Instance Scheduling: Detect instances that can be scheduled (dev/test environments)
Storage Optimization
Section titled “Storage Optimization”- EBS Volume Right-sizing: Identify oversized EBS volumes
- Storage Class Optimization: Recommend appropriate S3 storage classes
- Snapshot Management: Identify old or unnecessary snapshots
- Unattached Resources: Find unattached EBS volumes and Elastic IPs
Database Optimization
Section titled “Database Optimization”- RDS Right-sizing: Analyze RDS instance utilization and recommend sizing
- Multi-AZ Analysis: Evaluate if Multi-AZ is necessary for all databases
- Read Replica Optimization: Optimize read replica configurations
- Database Engine Efficiency: Recommend more cost-effective database engines
Network Optimization
Section titled “Network Optimization”- Data Transfer Analysis: Identify expensive data transfer patterns
- NAT Gateway Optimization: Optimize NAT Gateway usage and placement
- Load Balancer Efficiency: Analyze load balancer necessity and configuration
- VPC Endpoint Opportunities: Recommend VPC endpoints to reduce data transfer costs
Intelligent Analysis Features
Section titled “Intelligent Analysis Features”Usage Pattern Recognition
Section titled “Usage Pattern Recognition”Example Analysis Output:
EC2 Instance: i-0123456789abcdef0- Instance Type: m5.xlarge ($0.192/hour)- Average CPU: 15%- Average Memory: 25%- Recommendation: Downsize to m5.large- Estimated Monthly Savings: $69.12
RDS Instance: myapp-prod-db- Instance Type: db.r5.2xlarge ($0.504/hour)- Average CPU: 8%- Average Connections: 12- Recommendation: Downsize to db.r5.large- Estimated Monthly Savings: $181.44
Idle Resource Detection
Section titled “Idle Resource Detection”- Zero-Activity Instances: Identify EC2 instances with no activity
- Unused Load Balancers: Find load balancers with no traffic
- Orphaned Resources: Detect resources not associated with active applications
- Development Resource Cleanup: Identify forgotten development resources
Scheduling Opportunities
Section titled “Scheduling Opportunities”- Development Environments: Identify dev/test resources that can be scheduled
- Batch Processing: Optimize batch job resource allocation
- Seasonal Workloads: Identify workloads with predictable usage patterns
- Weekend Shutdown: Find resources that can be shut down during off-hours
Automated Recommendations
Section titled “Automated Recommendations”Infrastructure as Code Updates
Section titled “Infrastructure as Code Updates”Cased can generate Terraform updates to implement optimizations:
# Example Terraform optimization generated by Casedresource "aws_instance" "web_server" { # Changed from m5.xlarge to m5.large based on utilization analysis instance_type = "m5.large" # Previous: m5.xlarge
# Added scheduling for development environment tags = { Name = "web-server-dev" Schedule = "weekdays-9to5" # New: Auto-shutdown schedule }}
# New: Reserved Instance recommendationresource "aws_ec2_reserved_instance" "web_server_ri" { instance_type = "m5.large" instance_count = 2 offering_type = "All Upfront" # Estimated savings: $1,200/year}
Policy Recommendations
Section titled “Policy Recommendations”- Lifecycle Policies: Automated S3 lifecycle policies for cost optimization
- Auto Scaling Policies: Optimize auto scaling configurations
- Backup Policies: Optimize backup retention and frequency
- Access Policies: Identify unused IAM roles and policies
Cost Tracking and Reporting
Section titled “Cost Tracking and Reporting”Savings Tracking
Section titled “Savings Tracking”- Before/After Analysis: Track cost reductions from implemented optimizations
- ROI Calculation: Calculate return on investment for optimization efforts
- Trend Analysis: Monitor cost trends over time
- Budget Impact: Show how optimizations affect budget forecasts
Custom Reporting
Section titled “Custom Reporting”Monthly Cost Optimization Report:
💰 Total Potential Savings Identified: $2,847/month
🔧 Optimization Opportunities:- EC2 Right-sizing: $1,234/month (8 instances)- RDS Optimization: $567/month (3 databases)- Storage Cleanup: $345/month (unused volumes)- Reserved Instance: $701/month (annual commitment)
📊 Implementation Status:- Completed: $1,200/month (42% of potential)- In Progress: $890/month (31% of potential)- Planned: $757/month (27% of potential)
🎯 Quick Wins (< 1 hour implementation):- Delete 12 unused EBS snapshots: $89/month- Terminate 3 idle EC2 instances: $234/month- Optimize S3 storage classes: $156/month
Integration Examples
Section titled “Integration Examples”Automated Cost Analysis
Section titled “Automated Cost Analysis”name: Weekly Cost Analysison: schedule: - cron: "0 9 * * 1" # Every Monday at 9 AM
jobs: cost-analysis: runs-on: ubuntu-latest steps: - name: Run Cost Analysis run: | curl -X POST https://app.cased.com/api/v1/cost-analysis/ \ -H "Authorization: Bearer ${{ secrets.CASED_API_KEY }}" \ -H "Content-Type: application/json" \ -d '{ "analysis_type": "comprehensive", "generate_recommendations": true, "create_issues": true }'
Slack Integration
Section titled “Slack Integration”- name: Send Cost Report to Slack uses: cased/slack-notification-action@v1 with: webhook_url: ${{ secrets.SLACK_WEBHOOK }} message: | 📊 Weekly Cost Optimization Report
💰 Potential Savings: $2,847/month 🔧 New Opportunities: 12 items ✅ Completed This Week: $456/month saved
Top Recommendations: • Right-size m5.xlarge instances (8 found) • Clean up unused EBS volumes (23 found) • Implement S3 lifecycle policies (5 buckets)
Best Practices
Section titled “Best Practices”Regular Analysis
Section titled “Regular Analysis”- Weekly Reviews: Run cost analysis weekly to catch new optimization opportunities
- Monthly Deep Dives: Perform comprehensive analysis monthly
- Quarterly Planning: Align cost optimization with capacity planning
- Annual Budgeting: Use optimization insights for annual budget planning
Implementation Strategy
Section titled “Implementation Strategy”- Quick Wins First: Implement easy optimizations to build momentum
- Risk Assessment: Evaluate business impact before making changes
- Gradual Implementation: Roll out changes gradually to minimize risk
- Monitoring: Monitor performance after optimizations
Team Collaboration
Section titled “Team Collaboration”- Shared Responsibility: Make cost optimization a team responsibility
- Regular Reviews: Include cost optimization in sprint planning
- Documentation: Document optimization decisions and their outcomes
- Knowledge Sharing: Share cost optimization learnings across teams
Advanced Features
Section titled “Advanced Features”Predictive Analysis
Section titled “Predictive Analysis”- Seasonal Forecasting: Predict cost changes based on seasonal patterns
- Growth Projections: Forecast costs based on application growth
- Optimization Impact: Predict the impact of proposed optimizations
- Budget Variance: Predict budget variance based on current trends
Custom Optimization Rules
Section titled “Custom Optimization Rules”# Example custom optimization rulesoptimization_rules: compute: - name: "Dev Environment Scheduling" condition: "environment == 'dev' AND cpu_avg < 20%" action: "schedule_shutdown" schedule: "weekdays-18:00-to-08:00"
- name: "Underutilized Production" condition: "environment == 'prod' AND cpu_avg < 30% AND memory_avg < 40%" action: "recommend_downsize" approval_required: true
storage: - name: "Old Snapshot Cleanup" condition: "age > 90_days AND not_used_for_ami" action: "delete_snapshot" approval_required: false
Multi-Account Analysis
Section titled “Multi-Account Analysis”- Cross-Account Optimization: Analyze costs across multiple AWS accounts
- Consolidated Reporting: Unified cost optimization reports
- Account Comparison: Compare optimization opportunities across accounts
- Shared Resource Optimization: Optimize shared resources like NAT gateways
Cost optimization with Cased transforms cloud cost management from a reactive process into a proactive, data-driven practice that continuously identifies and implements cost savings opportunities.