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Infrastructure As Code

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peterbamuhigire
infrastructure-as-code

Use when provisioning or changing cloud infrastructure with Terraform or Ansible — modules, remote state with S3 native locking, workspaces vs directory-per-env, common AWS patterns, idempotent Ansible roles for Debian/Ubuntu, GitOps with ArgoCD/Flux, drift detection, and Vault secret injection.

Overview

Publisherpeterbamuhigire
Repositorychwezi-dev-engine
Skill nameinfrastructure-as-code
Stars
29
Forks
6
Bundled files
5
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 5 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by peterbamuhigire on GitHub. Read the source before you install it.

Installation

Install the Infrastructure As Code AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/peterbamuhigire/chwezi-dev-engine/tree/main/skills/devops-cloud/infrastructure-as-code
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/peterbamuhigire/chwezi-dev-engine.git /tmp/chwezi-dev-engine
mkdir -p .claude/skills
cp -r /tmp/chwezi-dev-engine/skills/devops-cloud/infrastructure-as-code .claude/skills/infrastructure-as-code
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Infrastructure As Code in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Infrastructure As Code on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Infrastructure As Code is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Infrastructure as Code

Acknowledgement: Shared by Peter Bamuhigire, techguypeter.com, +256 784 464178.

Use When

  • Provisioning or changing cloud infrastructure with Terraform or Ansible — modules, remote state, workspaces, AWS patterns, idempotent Ansible roles, GitOps with ArgoCD/Flux, drift detection, Vault secret injection.

Do Not Use When

  • Vault PKI, dynamic secrets, or rotation depth is needed — load cicd-devsecops.
  • The work is CI/CD pipeline construction around IaC — load cicd-pipelines or cicd-pipeline-design.
  • The work is Kubernetes object authoring (Deployments, Services, Helm charts) — load kubernetes-platform.

Required Inputs

  • Project context, target cloud (or self-managed Debian/Ubuntu), and the concrete change to make.
  • Confirm deliverable: design, code, review, migration plan, audit, or runbook.

Workflow

  • Read this SKILL.md first, then load only the referenced deep-dive files that the task needs.
  • Apply the ordered guidance, decision rules, and acceptance criteria here instead of cherry-picking snippets.
  • Make assumptions, risks, and follow-up work explicit when they matter.

Quality Standards

  • Outputs are execution-oriented, concise, and consistent with the repository engineering baseline.
  • Preserve existing project conventions unless this skill requires a stronger standard.
  • Prefer deterministic, reviewable steps over tool-specific magic.

Outputs

  • Concrete result fitted to the task: implementation guidance, review findings, ADR-style decisions, templates, or generated artifacts.
  • Explicit assumptions, tradeoffs, or unresolved gaps when context is incomplete.

References

  • references/terraform-modules-state.md — module skeleton, registry conventions, state commands, import, splitting state, backend choice.
  • references/aws-patterns.md — VPC, ECS+ALB, RDS, S3 lifecycle, Terratest.
  • references/ansible-debian.md — inventory, role layout, idempotency patterns, hardening playbook, tags.
  • references/gitops-argocd-flux.md — ArgoCD Application/ApplicationSet, Flux bootstrap, drift wiring.
  • references/iac-tool-selection-and-delivery.md — load when choosing IaC tool categories, deciding Terraform vs OpenTofu (licence verified 2026-09-24), or designing the PR-plan / protected-apply pipeline and state isolation.

Evidence Produced

CategoryArtifactFormatExample
Release evidenceInfrastructure plan and apply evidencePlan output plus change recordreviewed diff, policy checks, state backup, apply result, drift check, and rollback

Why IaC

Inputs

InputRequiredPurpose
Desired resources and environmentyesBound change
Existing state and provider versionsyesPrevent drift damage
Identity and approval policyyesSet execution boundary

Capability contract

Author and validate code by default. Apply, destroy, import, state edits, and secret writes require explicit environment authority and a reviewed plan.

Degraded mode

If credentials or state are unavailable, run static validation and return an unverified plan checklist; never simulate apply results.

Decision rules

ConditionAction
Plan replaces stateful resourceRequire recovery plan
Existing resource lacks state ownershipImport or document exception
Secret would enter source or stateUse external secret boundary

Domain Anti-Patterns

  • Editing remote state manually. Fix: use supported commands with backup.
  • Applying an unreviewed plan. Fix: approve a saved plan.
  • Hardcoding secrets. Fix: inject references at runtime.
  • Copying divergent environment modules. Fix: share versioned modules.
  • Ignoring drift. Fix: schedule read-only plans.

Snowflake servers — hand-configured, undocumented, irreplaceable — cause outages nobody can recover from. IaC puts environments in version-controlled code, making drift a diffable artifact and rebuilds a routine operation.

§1 Terraform Fundamentals

Terraform's core blocks:

BlockRole
terraformrequired_providers, required_version, backend.
providerConfigures a provider (aws, google, kubernetes, helm, vault).
resourceDeclares a managed object (e.g. aws_instance, aws_s3_bucket).
dataReads existing infrastructure without managing it.
variable / outputInput/output contract of a configuration or module.
localsComputed expressions reused inside the config.
moduleComposition: include another configuration.

Pin provider and Terraform versions — a minor provider bump can silently change resource behaviour.

hcl
terraform {
  required_version = ">= 1.11.0" # S3 native locking (use_lockfile) needs Terraform 1.11+ / OpenTofu 1.10+
  required_providers {
    aws = { source = "hashicorp/aws", version = "~> 6.0" } # AWS provider 6.x current as of 2026-09-24
  }
  backend "s3" {
    bucket       = "acme-tfstate"
    key          = "envs/prod/main.tfstate"
    region       = "eu-west-1"
    encrypt      = true
    use_lockfile = true   # native S3 locking — preferred
  }
}

provider "aws" { region = var.region }

variable "region"      { type = string }
variable "environment" { type = string }
variable "project" {
  type        = string
  description = "Project slug used in resource names"
  validation {
    condition     = can(regex("^[a-z0-9-]{3,20}$", var.project))
    error_message = "project must be 3-20 chars, lowercase, digits, or hyphens."
  }
}

module "network" {
  source      = "./modules/network"
  cidr        = "10.20.0.0/16"
  environment = var.environment
}

resource "aws_s3_bucket" "assets" {
  bucket = "acme-${var.environment}-assets"
  tags   = { Project = var.project, Environment = var.environment }
}

output "vpc_id"           { value = module.network.vpc_id }
output "app_bucket_name"  { value = aws_s3_bucket.assets.id }

For a full VPC + ECS + RDS + S3 lifecycle example see references/aws-patterns.md.

§2 State Management

Never commit terraform.tfstate to Git — it stores secrets in plaintext and creates merge conflicts. Use a remote backend with locking.

The HashiCorp S3-backend documentation is explicit on locking:

Locking can be enabled via S3 or DynamoDB. However, DynamoDB-based locking is deprecated. To enable S3 state locking directly, use the use_lockfile argument (set to true).

The legacy dynamodb_table argument requires a table whose partition key is LockID of type String. New configurations should use use_lockfile = true; existing configurations may run both during transition.

Backend choice:

BackendWhenLocking
S3 + use_lockfile = trueAWS-hosted, current best practiceNative S3 conditional writes
S3 + dynamodb_tableLegacy; existing configsDynamoDB partition key LockID (string)
GCSGCP-hosted projectsNative object generation locking
Terraform Cloud / EnterpriseHosted, team workflowsBuilt in

Importing existing infrastructure:

bash
# Bring an existing AWS S3 bucket under Terraform management
terraform import aws_s3_bucket.assets acme-prod-assets
# Then write the resource block to match — terraform plan should show no diff.

terraform state list
terraform state show aws_s3_bucket.assets
terraform state rm aws_s3_bucket.assets       # untrack without destroying

Split state per blast-radius boundary — network/, data/, app/ — and cross-reference outputs through terraform_remote_state. See references/terraform-modules-state.md.

§3 Module Design

A module is a directory of .tf files consumed via module "name" { source = "..." }. Pin to an exact Git tag — main can break you on any push.

Module skeleton:

text
modules/network/
  main.tf          # resources
  variables.tf     # typed, documented inputs
  outputs.tf       # exported values consumers depend on
  versions.tf      # required_providers, required_version
  README.md        # usage example, input/output table

Versioning and registry:

  • Tag modules in Git with semver (v1.2.0); consumers reference by tag.
  • Public modules consumed via the Terraform Registry use source = "namespace/name/provider" and version = "x.y.z".
  • Registry naming convention: terraform-<PROVIDER>-<NAME> for module repositories (e.g. terraform-aws-vpc).
hcl
module "vpc_git" {
  source = "git::https://github.com/acme/tf-modules.git//modules/vpc?ref=v1.2.0"
  name   = "acme-prod"
  cidr   = "10.20.0.0/16"
  azs    = ["eu-west-1a", "eu-west-1b"]
}

module "vpc_registry" {
  source  = "terraform-aws-modules/vpc/aws"
  version = "5.5.1"
  # ...
}

Composability rule of thumb: a module should do one thing — a network, a database, a service. Avoid the "everything module" — it forces consumers to accept defaults they cannot opt out of. Deeper input/output contract patterns in references/terraform-modules-state.md.

§4 Workspaces and Environments

PatternWhen to useTrade-off
terraform workspace (named workspaces, single backend key path)Lightweight per-env separation in the same configurationEasy to apply to the wrong env; small blast radius only.
Directory per environment (envs/dev, envs/staging, envs/prod) with separate backendsStrong isolation; each env has its own stateMore duplication; manage with module composition.
Terragrunt-style stacksMany envs / regions, DRY backend configExtra tool to learn.

For production SaaS, prefer directory-per-env with module composition. For small projects, workspaces are fine:

bash
terraform workspace new prod && terraform workspace select prod
terraform apply -var-file="prod.tfvars"
hcl
locals {
  instance_size = {
    dev = "t3.micro", staging = "t3.small", prod = "m6i.large"
  }[terraform.workspace]
}

When prod must live in a separate AWS account, directory-per-env is mandatory — workspaces share backend credentials.

§5 Ansible for Debian/Ubuntu

The Ansible playbook documentation defines the model:

A playbook consists of one or more "plays" in an ordered list. Each play executes part of the overall goal of the playbook, running one or more tasks. Each task calls an Ansible module.

Each play needs hosts (the targeted managed nodes) and at least one task. Plays and tasks execute top-to-bottom; each task runs against all matched hosts before the next task starts.

Minimum nginx role and inventory:

ini
# inventories/prod/hosts.ini
[web]
web1.example.com
web2.example.com

[debian:children]
web

[debian:vars]
ansible_user=deploy
ansible_python_interpreter=/usr/bin/python3
yaml
# roles/nginx/tasks/main.yml
- name: Ensure nginx is installed
  ansible.builtin.apt:
    name: nginx
    state: present
    update_cache: true
    cache_valid_time: 3600

- name: Deploy nginx site config
  ansible.builtin.template:
    src: site.conf.j2
    dest: /etc/nginx/sites-available/{{ site_name }}.conf
    owner: root
    group: root
    mode: "0644"
  notify: Reload nginx

# roles/nginx/handlers/main.yml
- name: Reload nginx
  ansible.builtin.service: { name: nginx, state: reloaded }

Idempotency rule: running the playbook ten times leaves the system identical to running it once. Ansible modules are idempotent by default; raw shell commands are not — use ansible.builtin.file, apt, template, systemd, and only fall back to command/shell with explicit changed_when and failed_when.

Variable precedence (most-specific wins): -e > task > block > role > play > host > group > role defaults. Dry-run before prod with ansible-playbook -i inventories/prod site.yml --check --diff.

For role layout, dynamic AWS inventory, dependency declarations, and a baseline Ubuntu hardening playbook (ufw, fail2ban, unattended-upgrades, deploy user, SSH keys), see references/ansible-debian.md.

§6 GitOps — ArgoCD and Flux

The Git repo is the single source of truth; a controller continuously reconciles the live cluster to match.

ArgoCD's documented model:

Argo CD continuously monitors running applications and compares the current, live state against the desired target state (as specified in the Git repo). Applications that deviate from this target configuration are flagged as OutOfSync.

ArgoCD syncPolicy fields:

FieldEffect
automated.enabledActivate automated sync.
automated.prune: trueAutomatically delete resources removed from Git.
automated.selfHeal: trueRe-sync when the live cluster state deviates from Git.
automated.allowEmptyPermit applications with empty manifests when pruning.
retry.refreshRefresh on new revisions during sync retries.

ArgoCD also supports PreSync, Sync, and PostSync hooks for blue/green and canary rollouts, plus ApplicationSet for multi-cluster fan-out.

Flux is multi-controller and headless:

ControllerRole
source-controllerWatches Git/OCI/Helm repositories and produces an artifact for other controllers.
kustomize-controllerReconciles Kubernetes resources from Kustomize overlays.
helm-controllerEnsures the state of the Helm release matches what is defined in the resource, performs a release if this is not the case.
notification-controllerManages alerts, events, and outbound webhooks.
Image automation controllersDetect new images and update Git automatically.

Decision rubric:

NeedChoice
First-class web UI for app teamsArgoCD
Tight Helm + Kustomize integration with separable controllersFlux
Image-update-driven promotion across environmentsFlux (image-automation controllers)
ApplicationSet / multi-cluster fan-outArgoCD

Drift detection: ArgoCD flips Application to OutOfSync natively. For Terraform-managed resources, schedule terraform plan -detailed-exitcode every 6 hours and alert on exit code 2. Concrete manifests, bootstrap commands, and notification wiring live in references/gitops-argocd-flux.md.

§7 Terraform vs Ansible Decision Matrix

DimensionTerraformAnsible
Primary purposeProvisioning cloud resources, declarative with a state file.Server configuration and change application — procedural-feeling but idempotent modules.
Lifecycle modelPlan/apply against state; destroy is first-class.Run-to-converge; no state file.
Best at"Make these cloud resources exist.""Make these existing servers look like this."
Worst atImperative, ordered changes on existing servers.Tracking desired vs actual state of cloud resources at scale.
Idempotency modelState file plus provider plan.Module-level idempotency checks.

Rule of thumb: Terraform creates the VPS; Ansible configures it. For Kubernetes, GitOps replaces both — Terraform creates the cluster, ArgoCD or Flux reconciles workloads from Git.

In practice the two cooperate: Terraform creates the EC2 instance and emits its IP into an Ansible inventory; Ansible installs nginx, users, firewall rules.

§8 Secrets at the IaC Boundary

Risks:

  1. Secrets read by Terraform end up in plaintext inside the state file. Treat the state backend as a sensitive store — encrypt at rest, restrict IAM/ACL access, version the bucket.
  2. sensitive = true on a variable or output suppresses console echo but does not encrypt state.
  3. Ansible Vault encrypts variable files at rest, but the playbook process sees plaintext at runtime — secure the runner and the SSH path.

Patterns:

PatternToolingNotes
Pull at apply time from HashiCorp Vaultvault provider in Terraform; community.hashi_vault in AnsibleCentralised rotation; depth in cicd-devsecops.
Pull from cloud KMS / Secrets Manageraws_secretsmanager_secret_version, google_secret_manager_secret_versionAvoids running an additional service.
Encrypt-at-rest var filesAnsible Vault, SOPS, ageUseful when there is no Vault yet.
hcl
provider "vault" { address = "https://vault.acme.internal" }
data "vault_generic_secret" "rds" { path = "secret/data/prod/rds" }

resource "aws_db_instance" "primary" {
  username = data.vault_generic_secret.rds.data["username"]
  password = data.vault_generic_secret.rds.data["password"]
}

For Kubernetes workloads use external-secrets-operator so manifests reference a Vault path, not a literal secret:

yaml
apiVersion: external-secrets.io/v1beta1
kind: ExternalSecret
metadata: { name: api-db, namespace: api-prod }
spec:
  refreshInterval: 15m
  secretStoreRef: { name: vault-backend, kind: ClusterSecretStore }
  target: { name: api-db }
  data:
    - secretKey: password
      remoteRef: { key: prod/rds, property: password }

For Ansible, run a Vault Agent sidecar that renders secrets into /etc/app/db.env and have a systemd unit source it; the playbook installs the agent, never the secret. Cross-reference: cicd-devsecops covers Vault PKI, dynamic secrets, key rotation, and encryption-at-rest. This skill only handles the IaC entry point.

IaC Repository Layout

text
infra/
  modules/{vpc,rds,ecs}/
  envs/
    dev/{main.tf,terraform.tfvars}
    staging/
    prod/
  ansible/{roles,playbooks,inventories}/
  • main mirrors prod — a merge to main is a production change.
  • Feature branches target main via PR; CI runs fmt, validate, plan on every PR and posts the plan as a PR comment.
  • terraform apply against prod runs only from main after PR approval, through a protected workflow with manual approval.
  • Dev and staging apply automatically on merge so feedback cycles stay short.

Companion Skills

  • cloud-architecture — AWS services Terraform modules target.
  • kubernetes-platform — K8s cluster Terraform often provisions and where GitOps reconciles.
  • cicd-pipelines, cicd-pipeline-design — pipelines that run terraform plan/apply.
  • cicd-devsecops — Vault depth, secret scanning, SBOM, IaC linting (tflint, tfsec, checkov).
  • linux-security-hardening — Ansible roles that harden the OS baseline.

Sources

  • Terraform documentation — developer.hashicorp.com/terraform.
  • Terraform S3 backend — developer.hashicorp.com/terraform/language/backend/s3.
  • Terraform GCS backend — developer.hashicorp.com/terraform/language/backend/gcs.
  • Terraform Registry publishing — developer.hashicorp.com/terraform/registry/modules/publish.
  • Ansible playbook intro — docs.ansible.com/ansible/latest/playbook_guide/playbooks_intro.html.
  • Ansible roles — docs.ansible.com/ansible/latest/playbook_guide/playbooks_reuse_roles.html.
  • ArgoCD — argo-cd.readthedocs.io/en/stable/.
  • ArgoCD auto-sync — argo-cd.readthedocs.io/en/stable/user-guide/auto_sync/.
  • Flux concepts — fluxcd.io/flux/concepts/.
  • Terratest — terratest.gruntwork.io.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Infrastructure As Code AI skill do?

Use when provisioning or changing cloud infrastructure with Terraform or Ansible — modules, remote state with S3 native locking, workspaces vs directory-per-env, common AWS patterns, idempotent Ansible roles for Debian/Ubuntu, GitOps with ArgoCD/Flux, drift detection, and Vault secret injection.

Why use Infrastructure As Code on TypingMind?

Because you install it once and use it with any model. Infrastructure As Code is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Infrastructure As Code in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/peterbamuhigire/chwezi-dev-engine/tree/main/skills/devops-cloud/infrastructure-as-code. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Infrastructure As Code?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Infrastructure As Code?

As many as you like. As long as a model supports skills, you can use Infrastructure As Code with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Infrastructure As Code AI skill free?

Yes. It is published on GitHub by peterbamuhigire under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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