Initial commit
This commit is contained in:
Zhongwei Li
347
scripts/analyze_ri_recommendations.py
Executable file
347
scripts/analyze_ri_recommendations.py
Executable file
@@ -0,0 +1,347 @@
|
||||
#!/usr/bin/env python3
|
||||
"""
|
||||
Analyze EC2 and RDS usage patterns to recommend Reserved Instances.
|
||||
|
||||
This script:
|
||||
- Identifies consistently running EC2 instances
|
||||
- Calculates potential savings with Reserved Instances
|
||||
- Recommends RI types (Standard vs Convertible) and commitment levels (1yr vs 3yr)
|
||||
- Analyzes RDS instances for RI opportunities
|
||||
|
||||
Usage:
|
||||
python3 analyze_ri_recommendations.py [--region REGION] [--profile PROFILE] [--days DAYS]
|
||||
|
||||
Requirements:
|
||||
pip install boto3 tabulate
|
||||
"""
|
||||
|
||||
import argparse
|
||||
import boto3
|
||||
from datetime import datetime, timedelta
|
||||
from typing import List, Dict, Any
|
||||
from collections import defaultdict
|
||||
from tabulate import tabulate
|
||||
import sys
|
||||
|
||||
|
||||
class RIAnalyzer:
|
||||
def __init__(self, profile: str = None, region: str = None, days: int = 30):
|
||||
self.session = boto3.Session(profile_name=profile) if profile else boto3.Session()
|
||||
self.regions = [region] if region else self._get_all_regions()
|
||||
self.days = days
|
||||
self.recommendations = {
|
||||
'ec2': [],
|
||||
'rds': []
|
||||
}
|
||||
self.total_potential_savings = 0.0
|
||||
|
||||
# Simplified RI discount rates (actual rates vary by region/instance type)
|
||||
self.ri_discounts = {
|
||||
'1yr_no_upfront': 0.40, # ~40% savings
|
||||
'1yr_partial_upfront': 0.42, # ~42% savings
|
||||
'1yr_all_upfront': 0.43, # ~43% savings
|
||||
'3yr_no_upfront': 0.60, # ~60% savings
|
||||
'3yr_partial_upfront': 0.62, # ~62% savings
|
||||
'3yr_all_upfront': 0.63 # ~63% savings
|
||||
}
|
||||
|
||||
def _get_all_regions(self) -> List[str]:
|
||||
"""Get all enabled AWS regions."""
|
||||
ec2 = self.session.client('ec2', region_name='us-east-1')
|
||||
regions = ec2.describe_regions(AllRegions=False)
|
||||
return [region['RegionName'] for region in regions['Regions']]
|
||||
|
||||
def _estimate_hourly_cost(self, instance_type: str) -> float:
|
||||
"""Rough estimate of On-Demand hourly cost."""
|
||||
cost_map = {
|
||||
't2.micro': 0.0116, 't2.small': 0.023, 't2.medium': 0.0464,
|
||||
't3.micro': 0.0104, 't3.small': 0.0208, 't3.medium': 0.0416,
|
||||
't3.large': 0.0832, 't3.xlarge': 0.1664, 't3.2xlarge': 0.3328,
|
||||
'm5.large': 0.096, 'm5.xlarge': 0.192, 'm5.2xlarge': 0.384,
|
||||
'm5.4xlarge': 0.768, 'm5.8xlarge': 1.536, 'm5.12xlarge': 2.304,
|
||||
'c5.large': 0.085, 'c5.xlarge': 0.17, 'c5.2xlarge': 0.34,
|
||||
'c5.4xlarge': 0.68, 'c5.9xlarge': 1.53, 'c5.18xlarge': 3.06,
|
||||
'r5.large': 0.126, 'r5.xlarge': 0.252, 'r5.2xlarge': 0.504,
|
||||
'r5.4xlarge': 1.008, 'r5.8xlarge': 2.016, 'r5.12xlarge': 3.024,
|
||||
}
|
||||
|
||||
# Default fallback based on instance family
|
||||
if instance_type not in cost_map:
|
||||
family = instance_type.split('.')[0]
|
||||
family_defaults = {'t2': 0.02, 't3': 0.02, 'm5': 0.10, 'c5': 0.09, 'r5': 0.13}
|
||||
return family_defaults.get(family, 0.10)
|
||||
|
||||
return cost_map[instance_type]
|
||||
|
||||
def _calculate_savings(self, hourly_cost: float, hours_running: float) -> Dict[str, float]:
|
||||
"""Calculate potential savings with different RI options."""
|
||||
monthly_od_cost = hourly_cost * hours_running
|
||||
|
||||
savings = {}
|
||||
for ri_type, discount in self.ri_discounts.items():
|
||||
monthly_ri_cost = monthly_od_cost * (1 - discount)
|
||||
monthly_savings = monthly_od_cost - monthly_ri_cost
|
||||
savings[ri_type] = {
|
||||
'monthly_cost': monthly_ri_cost,
|
||||
'monthly_savings': monthly_savings,
|
||||
'annual_savings': monthly_savings * 12
|
||||
}
|
||||
|
||||
return savings
|
||||
|
||||
def analyze_ec2_instances(self):
|
||||
"""Analyze EC2 instances for RI opportunities."""
|
||||
print(f"\n[1/2] Analyzing EC2 instances (last {self.days} days)...")
|
||||
|
||||
# Group instances by type and platform
|
||||
instance_groups = defaultdict(lambda: {'count': 0, 'instances': []})
|
||||
|
||||
for region in self.regions:
|
||||
try:
|
||||
ec2 = self.session.client('ec2', region_name=region)
|
||||
cloudwatch = self.session.client('cloudwatch', region_name=region)
|
||||
|
||||
instances = ec2.describe_instances(
|
||||
Filters=[{'Name': 'instance-state-name', 'Values': ['running']}]
|
||||
)
|
||||
|
||||
for reservation in instances['Reservations']:
|
||||
for instance in reservation['Instances']:
|
||||
instance_id = instance['InstanceId']
|
||||
instance_type = instance['InstanceType']
|
||||
platform = instance.get('Platform', 'Linux/UNIX')
|
||||
|
||||
# Check if instance has been running consistently
|
||||
launch_time = instance['LaunchTime']
|
||||
days_running = (datetime.now(launch_time.tzinfo) - launch_time).days
|
||||
|
||||
if days_running >= self.days:
|
||||
# Check uptime via CloudWatch
|
||||
end_time = datetime.now()
|
||||
start_time = end_time - timedelta(days=self.days)
|
||||
|
||||
try:
|
||||
metrics = cloudwatch.get_metric_statistics(
|
||||
Namespace='AWS/EC2',
|
||||
MetricName='StatusCheckFailed',
|
||||
Dimensions=[{'Name': 'InstanceId', 'Value': instance_id}],
|
||||
StartTime=start_time,
|
||||
EndTime=end_time,
|
||||
Period=3600,
|
||||
Statistics=['Sum']
|
||||
)
|
||||
|
||||
# If we have metrics, the instance has been running
|
||||
if metrics['Datapoints'] or days_running >= self.days:
|
||||
key = f"{instance_type}_{platform}_{region}"
|
||||
instance_groups[key]['count'] += 1
|
||||
instance_groups[key]['instances'].append({
|
||||
'id': instance_id,
|
||||
'type': instance_type,
|
||||
'platform': platform,
|
||||
'region': region,
|
||||
'days_running': days_running
|
||||
})
|
||||
except Exception:
|
||||
# If CloudWatch fails, still count long-running instances
|
||||
if days_running >= self.days:
|
||||
key = f"{instance_type}_{platform}_{region}"
|
||||
instance_groups[key]['count'] += 1
|
||||
instance_groups[key]['instances'].append({
|
||||
'id': instance_id,
|
||||
'type': instance_type,
|
||||
'platform': platform,
|
||||
'region': region,
|
||||
'days_running': days_running
|
||||
})
|
||||
|
||||
except Exception as e:
|
||||
print(f" Error scanning {region}: {str(e)}")
|
||||
|
||||
# Generate recommendations
|
||||
for key, data in instance_groups.items():
|
||||
if data['count'] > 0:
|
||||
sample = data['instances'][0]
|
||||
instance_type = sample['type']
|
||||
platform = sample['platform']
|
||||
region = sample['region']
|
||||
count = data['count']
|
||||
|
||||
hourly_cost = self._estimate_hourly_cost(instance_type)
|
||||
hours_per_month = 730 # Average hours in a month
|
||||
savings = self._calculate_savings(hourly_cost, hours_per_month * count)
|
||||
|
||||
# Recommend best option (3yr all upfront for max savings)
|
||||
best_option = savings['3yr_all_upfront']
|
||||
self.total_potential_savings += best_option['annual_savings']
|
||||
|
||||
self.recommendations['ec2'].append({
|
||||
'Region': region,
|
||||
'Instance Type': instance_type,
|
||||
'Platform': platform,
|
||||
'Count': count,
|
||||
'Current Monthly Cost': f"${hourly_cost * hours_per_month * count:.2f}",
|
||||
'1yr Savings (monthly)': f"${savings['1yr_all_upfront']['monthly_savings']:.2f}",
|
||||
'3yr Savings (monthly)': f"${savings['3yr_all_upfront']['monthly_savings']:.2f}",
|
||||
'Annual Savings (3yr)': f"${best_option['annual_savings']:.2f}",
|
||||
'Recommendation': '3yr Standard RI (All Upfront)'
|
||||
})
|
||||
|
||||
print(f" Found {len(self.recommendations['ec2'])} RI opportunities")
|
||||
|
||||
def analyze_rds_instances(self):
|
||||
"""Analyze RDS instances for RI opportunities."""
|
||||
print(f"\n[2/2] Analyzing RDS instances (last {self.days} days)...")
|
||||
|
||||
instance_groups = defaultdict(lambda: {'count': 0, 'instances': []})
|
||||
|
||||
for region in self.regions:
|
||||
try:
|
||||
rds = self.session.client('rds', region_name=region)
|
||||
instances = rds.describe_db_instances()
|
||||
|
||||
for instance in instances['DBInstances']:
|
||||
instance_id = instance['DBInstanceIdentifier']
|
||||
instance_class = instance['DBInstanceClass']
|
||||
engine = instance['Engine']
|
||||
multi_az = instance['MultiAZ']
|
||||
|
||||
# Check if instance has been running for the analysis period
|
||||
create_time = instance['InstanceCreateTime']
|
||||
days_running = (datetime.now(create_time.tzinfo) - create_time).days
|
||||
|
||||
if days_running >= self.days:
|
||||
key = f"{instance_class}_{engine}_{multi_az}_{region}"
|
||||
instance_groups[key]['count'] += 1
|
||||
instance_groups[key]['instances'].append({
|
||||
'id': instance_id,
|
||||
'class': instance_class,
|
||||
'engine': engine,
|
||||
'multi_az': multi_az,
|
||||
'region': region,
|
||||
'days_running': days_running
|
||||
})
|
||||
|
||||
except Exception as e:
|
||||
print(f" Error scanning {region}: {str(e)}")
|
||||
|
||||
# Generate recommendations
|
||||
for key, data in instance_groups.items():
|
||||
if data['count'] > 0:
|
||||
sample = data['instances'][0]
|
||||
instance_class = sample['class']
|
||||
engine = sample['engine']
|
||||
multi_az = sample['multi_az']
|
||||
region = sample['region']
|
||||
count = data['count']
|
||||
|
||||
# RDS pricing is roughly 2x EC2 for same instance type
|
||||
# This is a rough approximation
|
||||
base_hourly = self._estimate_hourly_cost(instance_class.replace('db.', ''))
|
||||
hourly_cost = base_hourly * 2
|
||||
if multi_az:
|
||||
hourly_cost *= 2 # Multi-AZ doubles the cost
|
||||
|
||||
hours_per_month = 730
|
||||
savings = self._calculate_savings(hourly_cost, hours_per_month * count)
|
||||
|
||||
best_option = savings['3yr_all_upfront']
|
||||
self.total_potential_savings += best_option['annual_savings']
|
||||
|
||||
self.recommendations['rds'].append({
|
||||
'Region': region,
|
||||
'Instance Class': instance_class,
|
||||
'Engine': engine,
|
||||
'Multi-AZ': 'Yes' if multi_az else 'No',
|
||||
'Count': count,
|
||||
'Current Monthly Cost': f"${hourly_cost * hours_per_month * count:.2f}",
|
||||
'1yr Savings (monthly)': f"${savings['1yr_all_upfront']['monthly_savings']:.2f}",
|
||||
'3yr Savings (monthly)': f"${savings['3yr_all_upfront']['monthly_savings']:.2f}",
|
||||
'Annual Savings (3yr)': f"${best_option['annual_savings']:.2f}",
|
||||
'Recommendation': '3yr Standard RI (All Upfront)'
|
||||
})
|
||||
|
||||
print(f" Found {len(self.recommendations['rds'])} RI opportunities")
|
||||
|
||||
def print_report(self):
|
||||
"""Print RI recommendations report."""
|
||||
print("\n" + "="*100)
|
||||
print("RESERVED INSTANCE RECOMMENDATIONS")
|
||||
print("="*100)
|
||||
|
||||
if self.recommendations['ec2']:
|
||||
print("\nEC2 RESERVED INSTANCE OPPORTUNITIES")
|
||||
print("-" * 100)
|
||||
print(tabulate(self.recommendations['ec2'], headers='keys', tablefmt='grid'))
|
||||
|
||||
if self.recommendations['rds']:
|
||||
print("\nRDS RESERVED INSTANCE OPPORTUNITIES")
|
||||
print("-" * 100)
|
||||
print(tabulate(self.recommendations['rds'], headers='keys', tablefmt='grid'))
|
||||
|
||||
print("\n" + "="*100)
|
||||
print(f"TOTAL ANNUAL SAVINGS POTENTIAL: ${self.total_potential_savings:.2f}")
|
||||
print("="*100)
|
||||
|
||||
print("\n\nRECOMMENDATIONS:")
|
||||
print("- Standard RIs offer the highest discount but no flexibility to change instance type")
|
||||
print("- Consider Convertible RIs if you need flexibility (slightly lower discount)")
|
||||
print("- All Upfront payment offers maximum savings")
|
||||
print("- Partial Upfront balances savings with cash flow")
|
||||
print("- No Upfront minimizes initial cost but reduces savings")
|
||||
print("\nNEXT STEPS:")
|
||||
print("1. Review workload stability and growth projections")
|
||||
print("2. Compare RI costs with Savings Plans for additional flexibility")
|
||||
print("3. Purchase RIs through AWS Console or CLI")
|
||||
print("4. Monitor RI utilization to ensure maximum benefit")
|
||||
|
||||
def run(self):
|
||||
"""Run RI analysis."""
|
||||
print(f"Analyzing AWS resources for RI opportunities...")
|
||||
print(f"Looking at instances running for at least {self.days} days")
|
||||
print(f"Scanning {len(self.regions)} region(s)...\n")
|
||||
|
||||
self.analyze_ec2_instances()
|
||||
self.analyze_rds_instances()
|
||||
|
||||
self.print_report()
|
||||
|
||||
|
||||
def main():
|
||||
parser = argparse.ArgumentParser(
|
||||
description='Analyze AWS resources for Reserved Instance opportunities',
|
||||
formatter_class=argparse.RawDescriptionHelpFormatter,
|
||||
epilog="""
|
||||
Examples:
|
||||
# Analyze all regions with default profile
|
||||
python3 analyze_ri_recommendations.py
|
||||
|
||||
# Analyze specific region for instances running 60+ days
|
||||
python3 analyze_ri_recommendations.py --region us-east-1 --days 60
|
||||
|
||||
# Use named profile
|
||||
python3 analyze_ri_recommendations.py --profile production
|
||||
"""
|
||||
)
|
||||
|
||||
parser.add_argument('--region', help='AWS region (default: all regions)')
|
||||
parser.add_argument('--profile', help='AWS profile name (default: default profile)')
|
||||
parser.add_argument('--days', type=int, default=30,
|
||||
help='Minimum days instance must be running (default: 30)')
|
||||
|
||||
args = parser.parse_args()
|
||||
|
||||
try:
|
||||
analyzer = RIAnalyzer(
|
||||
profile=args.profile,
|
||||
region=args.region,
|
||||
days=args.days
|
||||
)
|
||||
analyzer.run()
|
||||
except Exception as e:
|
||||
print(f"Error: {str(e)}", file=sys.stderr)
|
||||
sys.exit(1)
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
main()
|
||||
Reference in New Issue
Block a user