QMCLOUD
  • What is QMCLOUD
  • Overview
    • Component Details
    • Security and RBAC
    • Dependencies
  • Architecture
  • Main features
  • Installation and Configuration
    • QMCLOUD SaaS
      • SaaS Registration
    • AWS Marketplace
    • Self-hosting
  • User Interface and Navigation
    • Main menu
    • Dashboard
    • General action buttons
    • Stack and Canvas
    • Stack Details
  • Getting started
    • Pre-requisites
    • Login to QMCLOUD
    • Create organization
    • Add Role
    • Add User
    • Add Components
    • Add Stack Profile
    • Add Workspace
    • Add Stack
    • Compose Infrastructure Using the Canvas
    • Add AWS Vpc
    • Add Subnets
    • Connect VPC and Subnets
    • Save Canvas State
    • Deploy the Infrastructure
  • AI Copilot
    • Example deployment using AI Copilot
    • AI Copilot pre-defined prompts
  • Additional resources
    • Explainer video
    • Short video on AI Copilot
    • Quick walkthrough videos
    • Walkthrough of deployment of AWS EKS
  • Examples
    • Deploy AWS Firewall and Networking with QMCLOUD
      • Application and landing zone components
      • List of landing zone components
      • Deployment steps
      • VPC configuration details
      • Routing configuration details
      • Firewall configuration
      • Additional components configuration
    • Securing applications in AWS using Palo Alto firewall
  • Templates
    • AWS Landing Zone
    • AWS EKS
    • Azure Web App
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AI Copilot

The AI Copilot is an assistant where you can enter a description of the desired cloud infrastructure you want to deploy and thus reduces the effort required to compose the desired infrastructure.

The AI Copilot extends the No Code technologies-based functionality in QMCLOUD for cloud deployments. Using the AI Copilot assistant, you can enter a description of the desired Cloud infrastructure you want to deploy in the prompt window.

The Copilot will then automatically generate the required configuration. The Copilot will then render the components and connections with appropriate properties on the canvas. The user can then easily deploy the cloud infrastructure.

One of the main use cases for the AI Copilot will be where the user is unsure about all the components required to deploy a service. For example, in AWS EKS, a user will need to compose many components including VPC, Subnets, Routing, Gateways, EKS Cluster, Nodes and IAM roles and policies. The user can enter a description in a prompt and incrementally build the required infrastructure.

As with any generative AI based technology, the more information and context that is provided to the assistant, the more accurate responses will be. The advantage of QMCLOUD AI Copilot is that the assistant will render the desired infrastructure on a canvas where the user can review, make changes if required and validate before deployments.

In summary the AI Copilot further simplifies and reduces the effort required to deploy Cloud infrastructure.

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Last updated 11 months ago

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