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Merge pull request #8760 from ministryofjustice/Update_221124_2
Update_221124_2
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101 changes: 101 additions & 0 deletions
101
terraform/environments/ppud/lambda_scripts/send_cpu_graph_dev.py
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,101 @@ | ||
| import boto3 | ||
| import datetime | ||
| import matplotlib.pyplot as plt | ||
| import io | ||
| import base64 | ||
| from botocore.exceptions import ClientError | ||
|
|
||
| # Initialize clients | ||
| cloudwatch = boto3.client('cloudwatch') | ||
| ses = boto3.client('ses') | ||
|
|
||
| def lambda_handler(event, context): | ||
| # 1. Define parameters | ||
| instance_id = event.get('InstanceId', 'i-0c98db0c20242e12c') # Replace with your instance ID | ||
| email_recipient = event.get('RecipientEmail', '[email protected]') # Replace with recipient email | ||
| email_sender = '[email protected]' # Replace with a verified SES sender email | ||
| region = 'eu-west-2' # Replace with your AWS region | ||
|
|
||
| # 2. Fetch CPU Utilization data from CloudWatch | ||
| try: | ||
| response = cloudwatch.get_metric_data( | ||
| MetricDataQueries=[ | ||
| { | ||
| 'Id': 'cpuUtilization', | ||
| 'MetricStat': { | ||
| 'Metric': { | ||
| 'Namespace': 'AWS/EC2', | ||
| 'MetricName': 'CPUUtilization', | ||
| 'Dimensions': [{'Name': 'InstanceId', 'Value': instance_id}] | ||
| }, | ||
| 'Period': 300, # 5 minutes | ||
| 'Stat': 'Average' | ||
| }, | ||
| 'ReturnData': True | ||
| } | ||
| ], | ||
| StartTime=datetime.datetime.utcnow() - datetime.timedelta(hours=168), | ||
| EndTime=datetime.datetime.utcnow() | ||
| ) | ||
| except ClientError as e: | ||
| print(f"Error fetching CloudWatch data: {e}") | ||
| return {'statusCode': 500, 'body': str(e)} | ||
|
|
||
| # 3. Process data for graphing | ||
| timestamps = [] | ||
| values = [] | ||
| for data_point in response['MetricDataResults'][0]['Timestamps']: | ||
| timestamps.append(data_point) | ||
| for data_point in response['MetricDataResults'][0]['Values']: | ||
| values.append(data_point) | ||
|
|
||
| # Sort data by timestamps | ||
| sorted_data = sorted(zip(timestamps, values)) | ||
| timestamps, values = zip(*sorted_data) | ||
|
|
||
| # 4. Generate a graph | ||
| plt.figure(figsize=(10, 6)) | ||
| plt.plot(timestamps, values, label="CPU Utilization", marker='o') | ||
| plt.xlabel('Time') | ||
| plt.ylabel('CPU Utilization (%)') | ||
| plt.title(f'CPU Utilization for {instance_id}') | ||
| plt.legend() | ||
| plt.grid(True) | ||
|
|
||
| # Save the graph to memory | ||
| image_buffer = io.BytesIO() | ||
| plt.savefig(image_buffer, format='png') | ||
| image_buffer.seek(0) | ||
|
|
||
| # Convert to base64 for email attachment | ||
| graph_base64 = base64.b64encode(image_buffer.getvalue()).decode('utf-8') | ||
| image_buffer.close() | ||
|
|
||
| # 5. Send the email via SES | ||
| email_subject = f"CPU Utilization Graph for {instance_id}" | ||
| email_body = ( | ||
| f"Attached is the CPU Utilization graph for the EC2 instance {instance_id} " | ||
| f"for the past week. \n\nBest regards,\nYour Monitoring Team" | ||
| ) | ||
|
|
||
| email_html_body = ( | ||
| f"<html><body><p>{email_body}</p><img src='data:image/png;base64,{graph_base64}'/></body></html>" | ||
| ) | ||
|
|
||
| try: | ||
| ses.send_email( | ||
| Source=email_sender, | ||
| Destination={'ToAddresses': [email_recipient]}, | ||
| Message={ | ||
| 'Subject': {'Data': email_subject}, | ||
| 'Body': { | ||
| 'Html': {'Data': email_html_body} | ||
| } | ||
| } | ||
| ) | ||
| print(f"Email sent successfully to {email_recipient}") | ||
| except ClientError as e: | ||
| print(f"Error sending email: {e}") | ||
| return {'statusCode': 500, 'body': str(e)} | ||
|
|
||
| return {'statusCode': 200, 'body': 'Email sent successfully'} |