agent: | Auto Exec |
What is an "Expert"? How do we create our own expert?
Add credentials for various integrations
Managing workspaces and access control
DagKnows Architecture Overview
Setting up SSO via Azure AD for Dagknows
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(Optionally) Add ubuntu user to docker group and refresh group membership
Deployment of an EKS Cluster with Worker Nodes in AWS
Adding, Deleting, Listing DagKnows Proxy credentials or key-value pairs
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
MSP Usecase: User Onboarding Azure + M365
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How to debug a kafka cluster and kafka topics?
Open VPN Troubleshooting (Powershell)
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
Find AWS ELBs with No Targets or Instances
This task identifies AWS Elastic Load Balancers (ELBs) that have no associated targets or instances. Such ELBs may indicate unused resources, leading to unnecessary costs. Checking and managing these can optimize AWS expenses.
- 1wgbSFWw8JJ8gk64Bc0yDDelete AWS ELBs
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There was a problem that the LLM was not able to address. Please rephrase your prompt and try again.This task deletes Amazon Elastic Load Balancers (ELBs) that are not associated with any targets or instances. These unattached ELBs could be remnants of previously deployed applications or services. By identifying and removing them, organizations can not only free up unused resources but also optimize their AWS infrastructure costs. This task helps maintain a clean and efficient cloud environment while ensuring cost-effectiveness.
inputsoutputsimport boto3 from botocore.exceptions import ClientError creds = _get_creds(cred_label)['creds'] access_key = creds['username'] secret_key = creds['password'] def delete_elbs(load_balancers): """ Deletes the specified Elastic Load Balancers. Args: load_balancers (list): List of dictionaries containing ELB details. Returns: None. """ # Iterate over each ELB to delete for elb in load_balancers: region = elb['region'] elb_type = elb['type'] try: # Handle ELBv2 (Application, Network, Gateway) deletion if elb_type in ['application', 'network', 'gateway']: client = boto3.client('elbv2', aws_access_key_id=access_key,aws_secret_access_key=secret_key, region_name=region) client.delete_load_balancer(LoadBalancerArn=elb['elb_arn']) # Handle Classic ELB deletion elif elb_type == 'classic': client = boto3.client('elb',aws_access_key_id=access_key,aws_secret_access_key=secret_key, region_name=region) client.delete_load_balancer(LoadBalancerName=elb['elb_name']) print(f"Deleted {elb_type} load balancer {elb['elb_name']} in region {region}") # Handle potential client errors during deletion except ClientError as ce: print(f"Client error while deleting {elb_type} load balancer {elb['elb_name']} in region {region}: {ce}") # Handle other exceptions during deletion except Exception as e: print(f"Error while deleting {elb_type} load balancer {elb['elb_name']} in region {region}: {e}") # Specify the AWS regions to check #regions_to_check = ['us-west-1', 'us-east-1'] # Modify this list as needed ''' # Find ELBs with no targets or instances output_status, output_data = aws_find_elbs_with_no_targets_or_instances(regions=regions_to_check) ''' # Print and Delete the identified ELBs if output_status: print("No load balancers found with no targets or instances.") else: for elb in output_data: print(f"ELB Name: {elb['elb_name']}") if 'elb_arn' in elb: print(f"ELB ARN: {elb['elb_arn']}") print(f"Type: {elb['type']}") print(f"Region: {elb['region']}") print("-" * 40) delete_elbs(output_data) print("Load balancers deleted successfully.")copied1