UBHtfFjxRLdmgrHvdLL0Filter out low usage AWS EBS volumes
Filter out low usage AWS EBS volumes
There was a problem that the LLM was not able to address. Please rephrase your prompt and try again.
This task aims to identify Amazon Elastic Block Storage (EBS) volumes with minimal usage. It involves scanning through AWS resources to pinpoint EBS volumes that have been scarcely utilized over a predefined threshold period. This process can be crucial for optimizing storage resources and identifying opportunities to reduce costs, as it helps identify volumes that may no longer be necessary due to low activity levels.
inputs
outputs
import boto3
from datetime import datetime, timedelta
creds = _get_creds(cred_label)['creds']
access_key = creds['username']
secret_key = creds['password']
# Set the threshold for low usage in days
#low_usage_threshold = 30
def get_all_regions():
"""Retrieve all AWS regions."""
ec2 = boto3.client('ec2', aws_access_key_id=access_key, aws_secret_access_key=secret_key, region_name='us-east-1')
return [region['RegionName'] for region in ec2.describe_regions()['Regions']]
def find_low_usage_volumes(ec2_client, region):
"""
Find EBS volumes with low usage in a specific AWS region.
Args:
ec2_client (boto3.client): An EC2 client instance for a specific region.
region (str): The AWS region of the volumes.
Returns:
list: List of dictionaries containing volume IDs and their region with low usage.
"""
low_usage_volumes = []
try:
response = ec2_client.describe_volumes()
for volume in response['Volumes']:
volume_id = volume['VolumeId']
create_time = volume['CreateTime']
days_since_creation = (datetime.now() - create_time.replace(tzinfo=None)).days
if days_since_creation >= low_usage_threshold:
low_usage_volumes.append({
'VolumeId': volume_id,
'Region': region,
'LowUsageDays': days_since_creation # Track how many days the volume has been in low usage
})
return low_usage_volumes
except Exception as e:
print(f"Error in finding low usage volumes in region {region}: {e}")
return []
def display_volume_usage(data):
table = context.newtable()
table.title = "Low Usage EBS Volumes"
table.num_cols = 3
table.num_rows = 1
table.has_header_row = True
headers = ["Volume ID", "Region", "Idle Days"]
for col_num, header in enumerate(headers):
table.setval(0, col_num, header)
for region_volumes in data:
for volume in region_volumes:
table.num_rows += 1
values = [
volume["VolumeId"],
volume["Region"],
str(volume["LowUsageDays"]) # Convert idle days count to string for display
]
for col_num, value in enumerate(values):
table.setval(table.num_rows - 1, col_num, value)
# region_name to be provided; if None, script runs for all regions
# Hardcoded for one time result
region_name = None # Set to a specific region, e.g., 'us-east-2', or None for all regions
regions_to_process = [region_name] if region_name else get_all_regions()
low_usage_volumes_info =[]
for region in regions_to_process:
ec2_client = boto3.client('ec2', aws_access_key_id=access_key, aws_secret_access_key=secret_key, region_name=region)
low_usage_volumes = find_low_usage_volumes(ec2_client, region)
if not low_usage_volumes:
#print(f"No low usage EBS volumes found in region {region}")
p=1 # Dummy line to not give an empty conditional block
else:
'''
#print(f"Low usage EBS volumes in region {region}: {low_usage_volumes}")
# Header for the output
print(f"{'Volume ID':<20} {'Region':<10}")
# Looping through each volume in the list
for volume in low_usage_volumes:
volume_id = volume['VolumeId']
region = volume['Region']
# Printing each volume's ID and region in a formatted manner
print(f"{volume_id:<20} {region:<10}")'''
low_usage_volumes_info.append(low_usage_volumes)
display_volume_usage(low_usage_volumes_info)
context.skip_sub_tasks=True
copied- 1EgBjFdEoJfI8cbObKO5fDelete Detached EBS Volumes having low usage
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Delete Detached EBS Volumes having low usage
There was a problem that the LLM was not able to address. Please rephrase your prompt and try again.This task involves scanning through a list of EBS volumes and deleting them, provided they are not associated with any ec2 instances. Deleting these detached volumes that are no longer in use can help optimize storage resources and reduce unnecessary costs.
inputsoutputsimport boto3 creds = _get_creds(cred_label)['creds'] access_key = creds['username'] secret_key = creds['password'] def delete_detached_low_usage_volumes(volume_info): """ Delete detached low usage EBS volumes. Args: volume_info (dict): Dictionary containing the volume ID and its region. Returns: tuple: A tuple containing the count of deleted and skipped volumes. """ deleted_count, skipped_count = 0, 0 volume_id = volume_info['VolumeId'] region = volume_info['Region'] try: ec2_client = boto3.client('ec2', aws_access_key_id=access_key, aws_secret_access_key=secret_key, region_name=region) volume = ec2_client.describe_volumes(VolumeIds=[volume_id])['Volumes'][0] if not volume['Attachments']: ec2_client.delete_volume(VolumeId=volume_id) deleted_count += 1 print(f"Deleted detached low usage EBS volume {volume_id} in region {region}") else: skipped_count += 1 print(f"Volume {volume_id} is attached to an EC2 instance. Skipping deletion in region {region}.") except Exception as e: print(f"Error in deleting volume {volume_id} in region {region}: {e}") return deleted_count, skipped_count # low_usage_volumes is a list of dictionaries received from the upstream task total_deleted, total_skipped = 0, 0 for volume_info in low_usage_volumes: deleted, skipped = delete_detached_low_usage_volumes(volume_info) total_deleted += deleted total_skipped += skipped print(f"Summary: {total_deleted} detached low usage EBS volumes were deleted.") print(f"{total_skipped} volumes were skipped (still attached).") if total_deleted == 0: print("No detached low usage EBS volumes were deleted.")copied1