ranbot-ai/aws-cost-operations

AWS Cost & Operations

This skill provides comprehensive guidance for AWS cost optimization, monitoring, observability, and operational excellence with integrated MCP servers.

AWS Documentation Requirement

Always verify AWS facts using MCP tools (mcp__aws-mcp__* or mcp__*awsdocs*__*) before answering. The aws-mcp-setup dependency is auto-loaded — if MCP tools are unavailable, guide the user through that skill's setup flow.

Integrated MCP Servers

This plugin provides 3 MCP servers:

Bundled Servers

1. AWS Pricing MCP Server (pricing)

Purpose: Pre-deployment cost estimation and optimization

• Estimate costs before deploying resources
• Compare pricing across regions
• Calculate Total Cost of Ownership (TCO)
• Evaluate different service options for cost efficiency

2. AWS Cost Explorer MCP Server (costexp)

Purpose: Detailed cost analysis and reporting

• Analyze historical spending patterns
• Identify cost anomalies and trends
• Forecast future costs
• Analyze cost by service, region, or tag

3. Amazon CloudWatch MCP Server (cw)

Purpose: Metrics, alarms, and logs analysis

• Query CloudWatch metrics and logs
• Create and manage CloudWatch alarms
• Troubleshoot operational issues
• Monitor resource utilization

Note: The following servers are available separately via the Full AWS MCP Server (see aws-mcp-setup skill) and are not bundled with this plugin:

• AWS Billing and Cost Management MCP — Real-time billing details
• CloudWatch Application Signals MCP — APM and SLOs
• AWS Managed Prometheus MCP — PromQL queries for containers
• AWS CloudTrail MCP — API activity audit
• AWS Well-Architected Security Assessment MCP — Security posture assessment

When to Use This Skill

Use this skill when:

• Optimizing AWS costs and reducing spending
• Estimating costs before deployment
• Monitoring application and infrastructure performance
• Setting up observability and alerting
• Analyzing spending patterns and trends
• Investigating operational issues
• Auditing AWS activity and changes
• Assessing security posture
• Implementing operational excellence

Cost Optimization Best Practices

Pre-Deployment Cost Estimation

Always estimate costs before deploying:

1. Use AWS Pricing MCP to estimate resource costs
2. Compare pricing across different regions
3. Evaluate alternative service options
4. Calculate expected monthly costs
5. Plan for scaling and growth

Example workflow:

"Estimate the monthly cost of running a Lambda function with
1 million invocations, 512MB memory, 3-second duration in us-east-1"

Cost Analysis and Optimization

Regular cost reviews:

1. Use Cost Explorer MCP to analyze spending trends
2. Identify cost anomalies and unexpected charges
3. Review costs by service, region, and environment
4. Compare actual vs. budgeted costs
5. Generate cost optimization recommendations

Cost optimization strategies:

• Right-size over-provisioned resources
• Use appropriate storage classes (S3, EBS)
• Implement auto-scaling for dynamic workloads
• Leverage Savings Plans and Reserved Instances
• Delete unused resources and snapshots
• Use cost allocation tags effectively

Budget Monitoring

Track spending against budgets:

1. Use Billing and Cost Management MCP to monitor budgets
2. Set up budget alerts for threshold breaches
3. Review budget utilization regularly
4. Adjust budgets based on trends
5. Implement cost controls and governance

Monitoring and Observability Best Practices

CloudWatch Metrics and Alarms

Implement comprehensive monitoring:

1. Use CloudWatch MCP to query metrics and logs
2. Set up alarms for critical metrics:
   • CPU and memory utilization
   • Error rates and latency
   • Queue depths and processing times
   • API gateway throttling
   • Lambda errors and timeouts
3. Create CloudWatch dashboards for visualization
4. Use log insights for troubleshooting

Example alarm scenarios:

• Lambda error rate > 1%
• EC2 CPU utilization > 80%
• API Gateway 4xx/5xx error spike
• DynamoDB throttled requests
• ECS task failures

Application Performance Monitoring

Monitor application health:

1. Use CloudWatch Application Signals MCP for APM
2. Track service-level objectives (SLOs)
3. Monitor application dependencies
4. Identify performance bottlenecks
5. Set up distributed tracing

Container and Kubernetes Monitoring

For containerized workloads:

1. Use AWS Managed Prometheus MCP for metrics
2. Monitor container resource utilization
3. Track pod and node health
4. Create PromQL queries for custom metrics
5. Set up alerts for container anomalies

Audit and Security Best Practices

CloudTrail Activity Analysis

Audit AWS activity:

1. Use CloudTrail MCP to analyze API activity
2. Track who made changes to resources
3. Investigate security incidents
4. Monitor for suspicious activity patterns
5. Audit compliance with policies

**Co