Infrastructure as Code and AI - does it fit?

Slides of my lecture at "Grazer Linux Tage"

AI combined with cloud computing and infrastructure as a code - does that fit? Yes, indeed!

Are you curious how the GitHub Copilot could support you in implementing 'Infrastructure as Code' to deploy resources on Azure in an automated way?
This talk reveals my approach to using the AI pair programming tool. Starting from scratch, I will create a working Terraform configuration that can deploy a Kubernetes cluster on Azure, by just providing comments.
What could good practice for that look like?
It shall prove that AI speeds up your development speed and works well for infrastructure as code approaches.

https://pretalx.linuxtage.at/glt24/talk/N73FQV/

Transcript

1. Infrastructure as Code and AI - does it fit? PATRICK KOCH
2. Patrick Koch Email: patrick.koch@avl.com Blog: patrickkoch.dev LinkedIn: patkoch87 GitHub: patkoch Twitter/X: PK_Koch Mastodon: @patkoch@hostux.social Cloud Adoption Engineer, AVL List GmbH Source icons: Microsoft, HashiCorp
3. Source: kleinezeitung.at – 01.04.2024
4. Content What is Infrastructure as Code? Usages of AI tools for Infrastructure as Code Live Demo(s) Conclusion
5. What is Infrastructure as Code?
6. What is Infrastructure as Code?  Infrastructure as Code (IaC) is a method of managing and provisioning computing infrastructure through machine-readable definition files, rather than physical hardware configuration or interactive configuration tools. It's a key practice in DevOps and is used in conjunction with continuous delivery.  IaC allows developers to automate the process of setting up and managing infrastructure, which can lead to faster deployment times, more efficient use of resources, and more reliable and repeatable processes. It can be used to manage a wide range of services, including networks, virtual machines, load balancers, and connection topology. Source: GitHub Copilot
7. Example: Azure Kubernetes Cluster resource "azurerm_resource_group" "example" { name = „glt-24-rg" location = "West Europe" } resource "azurerm_kubernetes_cluster" "example" { name = „glt-24-aks" location = azurerm_resource_group.example.location resource_group_name = azurerm_resource_group.example.name dns_prefix = "exampleaks1" default_node_pool { name = "default" node_count = 1 vm_size = "Standard_D2_v2" } identity { type = "SystemAssigned" } tags = { Environment = "Production" } } Azure AKS Azure Icons: Azure Public Service Icons V14, Terraform Icon: HashiCorp Brand Kit
8. AI and IaC Example useages of AI tools for Infrastructure as Code
9. Code Generation Code Interpretation Trouble Shooting Security Answering questions Giving advice Icon MS Copilot: Microsoft 365 Copilot Icon.svg - Wikimedia Commons Icon Gemini: https://en.m.wikipedia.org/wiki/File:Google_Gemini_logo.svg Icon GitHub Copilot: Microsoft (provided by Maxim Salnikov)
10. Answering questions
13. Code Generation
15. Security
16. resource "azurerm_network_security_group" "sg-rdp- connection" { name = "glt24demonsg" location = azurerm_resource_group.rg.location resource_group_name = azurerm_resource_group.rg.name security_rule { name = "tcptraffic" priority = 100 direction = "Inbound" access = "Allow" protocol = "Tcp" source_port_range = "*" destination_port_range = "*" source_address_prefix = "*" destination_address_prefix = "*" } tags = { environment = "Testing" } }
18. Code Interpretation
19. param registryName string param location string = resourceGroup().location param sku string = 'Basic' resource acr 'Microsoft.ContainerRegistry/registries@2021-06-01-preview' = { name: registryName location: location sku: { name: sku } properties: { adminUserEnabled: true } }
21. Conclusion