Aggregate and Visualize Comprehensive EC2 CPU Utilization

import boto3 from datetime import datetime, timedelta last_n_days=30 # AWS Credentials creds = _get_creds(cred_label)['creds'] # Placeholder function to get AWS credentials access_key = creds['username'] secret_key = creds['password'] '''# Placeholder for instances_list instances_list = [ {'InstanceId': 'instance1', 'Region': 'us-east-1', 'State': 'running'}, {'InstanceId': 'instance2', 'Region': 'us-east-1', 'State': 'running'}, # Add more instances as needed ] ''' def fetch_cpu_utilization(instance_id, region, start_time, end_time): cloudwatch = boto3.client('cloudwatch', aws_access_key_id=access_key, aws_secret_access_key=secret_key, region_name=region) metrics = cloudwatch.get_metric_statistics( Namespace='AWS/EC2', MetricName='CPUUtilization', Dimensions=[{'Name': 'InstanceId', 'Value': instance_id}], StartTime=start_time, EndTime=end_time, Period=3600, Statistics=['Average'] ) # Calculate average CPU utilization without NumPy data_points = metrics.get('Datapoints', []) if data_points: avg_cpu = sum(dp['Average'] for dp in data_points) / len(data_points) else: avg_cpu = 0 return avg_cpu def plot_cpu_utilization(instances_list, last_n_days=7): start_time = datetime.utcnow() - timedelta(days=last_n_days) end_time = datetime.utcnow() avg_utilizations = [] for instance in instances_list: if instance['State'] == 'running': avg_cpu = fetch_cpu_utilization(instance['InstanceId'], instance['Region'], start_time, end_time) avg_utilizations.append((instance['InstanceId'], avg_cpu)) # Sort instances by average CPU utilization and select top 3 and bottom 3 avg_utilizations.sort(key=lambda x: x[1], reverse=True) top_instances = avg_utilizations[:3] bottom_instances = avg_utilizations[-3:] # Prepare data for plotting instance_ids = [x[0] for x in top_instances + bottom_instances] utilizations = [x[1] for x in top_instances + bottom_instances] # Plotting context.plot.add_trace( name="CPU Utilization", xpts=instance_ids, ypts=utilizations, tracetype='bar' ) context.plot.xlabel = 'Instance ID' context.plot.ylabel = 'Average CPU Utilization (%)' context.plot.title = f'Top & Bottom 3 EC2 Instances by CPU Utilization (Last {last_n_days} Days)' plot_cpu_utilization(instances_list, last_n_days=30)