agent: | Auto Exec |
What is an "Expert"? How do we create our own expert?
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Managing workspaces and access control
DagKnows Architecture Overview
Setting up SSO via Azure AD for Dagknows
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Deployment of an EKS Cluster with Worker Nodes in AWS
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Comprehensive AWS Security and Compliance Evaluation Workflow (SOC2 Super Runbook)
AWS EKS Version Update 1.29 to 1.30 via terraform
Instruction to allow WinRM connection
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Execute a simple task on the proxy
Assign the proxy role to a user
Create roles to access credentials in proxy
Install OpenVPN client on Windows laptop
Setup Kubernetes kubectl and Minikube on Ubuntu 22.04 LTS
Install Prometheus and Grafana on the minikube cluster on EC2 instance in the monitoring namespace
update the EKS versions in different clusters
AI agent session 2024-09-12T09:36:14-07:00 by Sarang Dharmapurikar
Parse EDN content and give a JSON out
Check whether a user is there on Azure AD and if the user account status is enabled
Get the input parameters of a Jenkins pipeline
Filter out EBS Volumes attached to stopped EC2 instances
This is a task focused on identifying Elastic Block Store (EBS) volumes that are connected to Amazon EC2 instances currently in a stopped state by examining the instance-state and corresponding volume mappings.
- 1ZN1jsWHIgLRDLexfM06TDetach and Delete AWS EBS Volumes
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Detach and Delete AWS EBS Volumes
There was a problem that the LLM was not able to address. Please rephrase your prompt and try again.This task involves the removal of Elastic Block Store (EBS) volumes from their associated instances followed by the deletion of these volumes. In this particular task detachment and deletion of EBS volumes is related to stopped EC2 instances. It is executed to free up storage resources, enhance resource allocation efficiency, and optimize costs within the AWS infrastructure.
inputsoutputsimport boto3 import time creds = _get_creds(cred_label)['creds'] access_key = creds['username'] secret_key = creds['password'] def detach_and_delete_ebs_volumes(ec2_client, instance_volume_map): """ Detaches and deletes EBS volumes attached to instances. Args: ec2_client (boto3.client): An EC2 client instance. instance_volume_map (dict): Dictionary with instance IDs as keys and associated volume IDs as values. """ try: for instance_id, volume_ids in instance_volume_map.items(): for volume_id in volume_ids: ec2_client.detach_volume(InstanceId=instance_id, VolumeId=volume_id, Force=True) print(f"Detached EBS volume {volume_id} from instance {instance_id}") time.sleep(5) # Wait for a few seconds to ensure detachment is complete otherwise there is a VolumeInUse error try: ec2_client.delete_volume(VolumeId=volume_id) print(f"Deleted EBS volume {volume_id}") except Exception as e: print(f"Error in deleting EBS volume {volume_id}: {e}") except Exception as e: print(f"Error in detaching and deleting EBS volumes: {e}") #regions = ["us-east-1"] # Add your desired regions here for region in regions: # Create an EC2 client instance for the region ec2_client = boto3.client("ec2", aws_access_key_id=access_key,aws_secret_access_key=secret_key,region_name=region) if not instance_volume_map: print(f"No volumes attached to stopped instances found in region {region}") else: # Detach and delete the identified EBS volumes detach_and_delete_ebs_volumes(ec2_client, instance_volume_map)copied1