| 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
Enable "Auto Exec" and "Send Execution Result to LLM" in "Adjust Settings" if desired
(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
Post a message to a Slack channel
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
Automated Cost Optimization for Kubernetes Workloads
•Use Case: Optimize the cost of Kubernetes workloads by automating the scaling of pods and nodes based on demand.
•The platform can ensure that resources are provisioned efficiently to meet demand without overprovisioning, thereby optimizing costs.
• Integrating with Kubernetes HPA for automatic pod scaling based on real-time metrics.
• Managing and automating the deployment of Cluster Autoscaler to scale the underlying EC2 nodes.
• Monitoring and optimizing resource allocation using VPA (Vertical Pod Autoscaler).
• Implementing scaling policies and automation workflows to ensure cost-efficient and responsive scaling operations.
• Enabling auto-scaling for serverless workloads with Fargate profiles, reducing the need for manual scaling interventions.