New serverless checks - potential migration of provisioned RDS servers to serverless

Summary of New RDS Checks

1. **1. co_rdscloudwatchanalysis.py - RDS CloudWatch Spike Analysis**

Purpose: Advanced RDS spike analysis using 14 days of CloudWatch metrics to identify optimal serverless migration candidates.

**Key Features:**

Deep Statistical Analysis: Analyzes hourly CPU utilization patterns with variance calculations

Spike Detection: Identifies instances with >2x average CPU spikes and calculates spike frequency

**Workload Classification:**

Highly Spiky (>60 score): Up to 50% savings potential

Moderately Spiky (40-60 score): 35% savings potential

Low Utilization (<20% avg CPU): Good candidates regardless of spikes

Comprehensive Metrics: CPU, IOPS, memory usage, database connections

Serverless Suitability Scoring: 0-100 scale based on variability and spike patterns

Data Sources: CloudWatch metrics (CPUUtilization, DatabaseConnections, ReadIOPS, WriteIOPS, FreeableMemory)

1. **2. co_rdsserverless.py - RDS Serverless Optimization**

Purpose: Identifies RDS instances suitable for Aurora Serverless v2 migration using Compute Optimizer data.

**Key Features:**

Compatibility Assessment: Checks engine compatibility (Aurora MySQL/PostgreSQL direct, MySQL/PostgreSQL migration path)

Migration Complexity Scoring: Low/Medium/High based on engine type

Cost Savings Calculation: Up to 40% savings for variable workloads

Workload Pattern Analysis: Identifies spiky, variable, low, and steady patterns

Utilization Thresholds: Prioritizes instances with <50% average CPU

Data Sources: AWS Compute Optimizer RDS recommendations

**Key Differences:**
CloudWatch Analysis: Uses real CloudWatch metrics for detailed spike analysis over 14 days

Serverless Optimization: Uses Compute Optimizer recommendations for broader compatibility assessment

Complementary Approach: CloudWatch provides deeper analysis, while Serverless provides broader coverage using existing CO data

Both checks focus on identifying cost optimization opportunities through Aurora Serverless v2 migration, with different data sources and analysis depths.