MCPInstall

infrastructure-cicd-data-engineering

Deploy data infrastructure changes using CI/CD patterns with GitHub Actions, Terraform, and AWS OIDC authentication

Installs
1.6K
Last 24h
—
Trending rank
—
Security
Not audited

Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/reason-machines/data-skills --skill infrastructure-cicd-data-engineering
  1. 01

    Install

    Run the command in your project. The CLI asks which agents to install for.

  2. 02

    Describe the task

    Ask your agent for something this skill covers. It loads infrastructure-cicd-data-engineering automatically when relevant.

  3. 03

    Review the result

    The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

Infrastructure CI/CD for Data Engineering

Skill by ara.so — Data Skills collection

This project demonstrates practical CI/CD patterns for deploying data infrastructure changes using GitHub Actions, Terraform, and AWS. It uses OpenID Connect (OIDC) for secure, keyless authentication between GitHub Actions and AWS, eliminating the need for long-lived AWS credentials.

What This Project Does

  • Bootstraps infrastructure: Creates S3 backend for Terraform state and OIDC provider for GitHub Actions
  • Automates deployments: Uses GitHub Actions workflows to plan and apply Terraform changes
  • Enforces reviews: Requires manual approval before production deployments
  • Validates code: Runs Terraform formatting and validation checks on PRs

Project Structure

.
├── terraform/
│   ├── bootstrap/          # Initial setup (S3 backend, OIDC)
│   │   └── main.tf
│   └── main/              # Main infrastructure definitions
│       └── main.tf
├── .github/
│   └── workflows/
│       ├── ci.yml         # Format and validation checks
│       └── deploy.yml     # Deployment workflow
└── tear-down.sh           # Cleanup script

Prerequisites

  1. AWS Account with appropriate permissions
  2. Terraform installed locally (v1.0+)
  3. GitHub Account and repository access
  4. AWS CLI configured with credentials
# Verify Terraform installation
terraform version

# Verify AWS credentials
aws sts get-caller-identity

Bootstrap Setup

Step 1: Create S3 Backend and OIDC Provider

The bootstrap process creates:

  • S3 bucket for Terraform state storage
  • DynamoDB table for state locking
  • IAM OIDC provider for GitHub Actions
  • IAM role that GitHub Actions will assume
# Initialize and apply bootstrap configuration
terraform -chdir=terraform/bootstrap init
terraform -chdir=terraform/bootstrap apply

# Capture the outputs
terraform -chdir=terraform/bootstrap output

Expected output:

github_actions_role_arn = "arn:aws:iam::123456789012:role/github-actions-role"
state_bucket_name = "my-terraform-state-bucket"

Step 2: Configure GitHub Repository Secrets

Create a repository secret named AWS_ROLE_ARN:

  1. Navigate to: Settings → Secrets and variables → Actions → New repository secret
  2. Name: AWS_ROLE_ARN
  3. Value: The ARN output from bootstrap (without quotes)
# Example ARN format (don't include quotes when pasting)
arn:aws:iam::123456789012:role/github-actions-role

Step 3: Create GitHub Environment

Set up a production environment with manual approval:

  1. Navigate to: Settings → Environments → New environment
  2. Name: production
  3. Configure protection rules:
    • ✅ Required reviewers (minimum 1)
    • Add yourself or team members as reviewers

Bootstrap Terraform Configuration

terraform/bootstrap/main.tf (simplified example):

terraform {
  required_version = ">= 1.0"
  required_providers {
    aws = {
      source  = "hashicorp/aws"
      version = "~> 5.0"
    }
  }
}

provider "aws" {
  region = var.aws_region
}

# S3 bucket for Terraform state
resource "aws_s3_bucket" "terraform_state" {
  bucket = "${var.project_name}-terraform-state-${var.environment}"
  
  tags = {
    Name        = "Terraform State Bucket"
    Environment = var.environment
    ManagedBy   = "Terraform"
  }
}

resource "aws_s3_bucket_versioning" "terraform_state" {
  bucket = aws_s3_bucket.terraform_state.id
  
  versioning_configuration {
    status = "Enabled"
  }
}

# DynamoDB table for state locking
resource "aws_dynamodb_table" "terraform_locks" {
  name         = "${var.project_name}-terraform-locks"
  billing_mode = "PAY_PER_REQUEST"
  hash_key     = "LockID"
  
  attribute {
    name = "LockID"
    type = "S"
  }
  
  tags = {
    Name        = "Terraform State Lock Table"
    Environment = var.environment
    ManagedBy   = "Terraform"
  }
}

# OIDC provider for GitHub Actions
resource "aws_iam_openid_connect_provider" "github_actions" {
  url = "https://token.actions.githubusercontent.com"
  
  client_id_list = [
    "sts.amazonaws.com"
  ]
  
  thumbprint_list = [
    "6938fd4d98bab03faadb97b34396831e3780aea1"
  ]
}

# IAM role for GitHub Actions
resource "aws_iam_role" "github_actions" {
  name = "github-actions-terraform-role"
  
  assume_role_policy = jsonencode({
    Version = "2012-10-17"
    Statement = [
      {
        Effect = "Allow"
        Principal = {
          Federated = aws_iam_openid_connect_provider.github_actions.arn
        }
        Action = "sts:AssumeRoleWithWebIdentity"
        Condition = {
          StringEquals = {
            "token.actions.githubusercontent.com:aud" = "sts.amazonaws.com"
          }
          StringLike = {
            "token.actions.githubusercontent.com:sub" = "repo:${var.github_org}/${var.github_repo}:*"
          }
        }
      }
    ]
  })
}

# Attach policies to the role
resource "aws_iam_role_policy_attachment" "github_actions_admin" {
  role       = aws_iam_role.github_actions.name
  policy_arn = "arn:aws:iam::aws:policy/AdministratorAccess"
}

# Outputs
output "github_actions_role_arn" {
  value       = aws_iam_role.github_actions.arn
  description = "ARN of the IAM role for GitHub Actions"
}

output "state_bucket_name" {
  value       = aws_s3_bucket.terraform_state.bucket
  description = "Name of the S3 bucket for Terraform state"
}

output "state_lock_table_name" {
  value       = aws_dynamodb_table.terraform_locks.name
  description = "Name of the DynamoDB table for state locking"
}

terraform/bootstrap/variables.tf:

variable "aws_region" {
  description = "AWS region for resources"
  type        = string
  default     = "us-east-1"
}

variable "project_name" {
  description = "Project name for resource naming"
  type        = string
  default     = "data-infra"
}

variable "environment" {
  description = "Environment name"
  type        = string
  default     = "production"
}

variable "github_org" {
  description = "GitHub organization or username"
  type        = string
}

variable "github_repo" {
  description = "GitHub repository name"
  type        = string
}

Main Infrastructure Configuration

terraform/main/main.tf (example data infrastructure):

terraform {
  required_version = ">= 1.0"
  
  backend "s3" {
    bucket         = "data-infra-terraform-state-production"
    key            = "main/terraform.tfstate"
    region         = "us-east-1"
    dynamodb_table = "data-infra-terraform-locks"
    encrypt        = true
  }
  
  required_providers {
    aws = {
      source  = "hashicorp/aws"
      version = "~> 5.0"
    }
  }
}

provider "aws" {
  region = var.aws_region
  
  default_tags {
    tags = {
      Project     = var.project_name
      Environment = var.environment
      ManagedBy   = "Terraform"
      DeployedBy  = "GitHub-Actions"
    }
  }
}

# Example: S3 bucket for data lake
resource "aws_s3_bucket" "data_lake" {
  bucket = "${var.project_name}-data-lake-${var.environment}"
}

resource "aws_s3_bucket_versioning" "data_lake" {
  bucket = aws_s3_bucket.data_lake.id
  
  versioning_configuration {
    status = "Enabled"
  }
}

resource "aws_s3_bucket_server_side_encryption_configuration" "data_lake" {
  bucket = aws_s3_bucket.data_lake.id
  
  rule {
    apply_server_side_encryption_by_default {
      sse_algorithm = "AES256"
    }
  }
}

# Example: Glue database for data catalog
resource "aws_glue_catalog_database" "analytics" {
  name        = "${var.project_name}_analytics_${var.environment}"
  description = "Analytics data catalog database"
}

# Example: IAM role for Glue jobs
resource "aws_iam_role" "glue_job" {
  name = "${var.project_name}-glue-job-role-${var.environment}"
  
  assume_role_policy = jsonencode({
    Version = "2012-10-17"
    Statement = [
      {
        Effect = "Allow"
        Principal = {
          Service = "glue.amazonaws.com"
        }
        Action = "sts:AssumeRole"
      }
    ]
  })
}

resource "aws_iam_role_policy_attachment" "glue_service" {
  role       = aws_iam_role.glue_job.name
  policy_arn = "arn:aws:iam::aws:policy/service-role/AWSGlueServiceRole"
}

# Outputs
output "data_lake_bucket" {
  value       = aws_s3_bucket.data_lake.bucket
  description = "Name of the data lake S3 bucket"
}

output "glue_database" {
  value       = aws_glue_catalog_database.analytics.name
  description = "Name of the Glue catalog database"
}

GitHub Actions Workflows

CI Workflow: Format and Validation

.github/workflows/ci.yml:

name: Terraform CI

on:
  pull_request:
    branches:
      - main
    paths:
      - 'terraform/**'
      - '.github/workflows/ci.yml'

permissions:
  contents: read
  pull-requests: write

jobs:
  terraform-checks:
    name: Terraform Checks
    runs-on: ubuntu-latest
    
    steps:
      - name: Checkout code
        uses: actions/checkout@v4
      
      - name: Setup Terraform
        uses: hashicorp/setup-terraform@v3
        with:
          terraform_version: 1.5.0
      
      - name: Terraform Format Check
        id: fmt
        run: terraform fmt -check -recursive terraform/
        continue-on-error: true
      
      - name: Terraform Init (Main)
        run: terraform -chdir=terraform/main init -backend=false
      
      - name: Terraform Validate (Main)
        run: terraform -chdir=terraform/main validate
      
      - name: Comment PR
        if: steps.fmt.outcome == 'failure'
        uses: actions/github-script@v7
        with:
          script: |
            github.rest.issues.createComment({
              issue_number: context.issue.number,
              owner: context.repo.owner,
              repo: context.repo.repo,
              body: '❌ Terraform formatting check failed. Run `terraform fmt -recursive terraform/` to fix.'
            })
      
      - name: Fail if format check failed
        if: steps.fmt.outcome == 'failure'
        run: exit 1

Deploy Workflow: Plan and Apply

.github/workflows/deploy.yml:

name: Deploy Infrastructure

on:
  push:
    branches:
      - main
    paths:
      - 'terraform/main/**'
  workflow_dispatch:

permissions:
  id-token: write
  contents: read
  pull-requests: write

jobs:
  terraform-plan:
    name: Terraform Plan
    runs-on: ubuntu-latest
    
    steps:
      - name: Checkout code
        uses: actions/checkout@v4
      
      - name: Configure AWS credentials
        uses: aws-actions/configure-aws-credentials@v4
        with:
          role-to-assume: ${{ secrets.AWS_ROLE_ARN }}
          aws-region: us-east-1
      
      - name: Setup Terraform
        uses: hashicorp/setup-terraform@v3
        with:
          terraform_version: 1.5.0
      
      - name: Terraform Init
        run: terraform -chdir=terraform/main init
      
      - name: Terraform Plan
        id: plan
        run: |
          terraform -chdir=terraform/main plan -no-color -out=tfplan
          terraform -chdir=terraform/main show -no-color tfplan > plan.txt
      
      - name: Upload plan
        uses: actions/upload-artifact@v4
        with:
          name: terraform-plan
          path: |
            terraform/main/tfplan
            plan.txt
          retention-days: 5
  
  terraform-apply:
    name: Terraform Apply
    needs: terraform-plan
    runs-on: ubuntu-latest
    environment: production
    
    steps:
      - name: Checkout code
        uses: actions/checkout@v4
      
      - name: Configure AWS credentials
        uses: aws-actions/configure-aws-credentials@v4
        with:
          role-to-assume: ${{ secrets.AWS_ROLE_ARN }}
          aws-region: us-east-1
      
      - name: Setup Terraform
        uses: hashicorp/setup-terraform@v3
        with:
          terraform_version: 1.5.0
      
      - name: Terraform Init
        run: terraform -chdir=terraform/main init
      
      - name: Download plan
        uses: actions/download-artifact@v4
        with:
          name: terraform-plan
          path: terraform/main/
      
      - name: Terraform Apply
        run: terraform -chdir=terraform/main apply -auto-approve tfplan

Common Workflows

Adding New Infrastructure

  1. Create/modify Terraform files in terraform/main/:
# terraform/main/kinesis.tf
resource "aws_kinesis_stream" "events" {
  name             = "${var.project_name}-events-${var.environment}"
  shard_count      = 1
  retention_period = 24
  
  shard_level_metrics = [
    "IncomingBytes",
    "IncomingRecords",
    "OutgoingBytes",
    "OutgoingRecords",
  ]
}

output "kinesis_stream_name" {
  value       = aws_kinesis_stream.events.name
  description = "Name of the Kinesis stream"
}
  1. Format Terraform files:
terraform fmt -recursive terraform/
  1. Validate locally (optional but recommended):
terraform -chdir=terraform/main init -backend=false
terraform -chdir=terraform/main validate
  1. Create a pull request:

    • CI workflow runs format check and validation
    • Review the checks before merging
  2. Merge to main:

    • Deploy workflow runs terraform plan
    • Manual approval required in GitHub UI
    • After approval, terraform apply executes

Checking Deployment Status

# View workflow runs
gh run list --workflow=deploy.yml

# View specific run logs
gh run view <run-id> --log

# Check specific job
gh run view <run-id> --job=<job-id>

Testing Changes Locally

# Initialize with backend
terraform -chdir=terraform/main init

# Plan changes
terraform -chdir=terraform/main plan

# Apply (be careful in production!)
terraform -chdir=terraform/main apply

Environment Variables and Configuration

Required GitHub Secrets

Secret NameDescriptionExample
AWS_ROLE_ARNIAM role ARN for GitHub Actionsarn:aws:iam::123456789012:role/github-actions-role

Terraform Variables

Create terraform/main/terraform.tfvars:

aws_region   = "us-east-1"
project_name = "my-data-platform"
environment  = "production"

# Additional configuration
enable_monitoring = true
data_retention_days = 90

Using Environment-Specific Configurations

terraform/main/environments/dev.tfvars:

environment  = "dev"
project_name = "my-data-platform"
aws_region   = "us-east-1"

# Dev-specific settings
enable_monitoring   = false
data_retention_days = 7

terraform/main/environments/prod.tfvars:

environment  = "production"
project_name = "my-data-platform"
aws_region   = "us-east-1"

enable_monitoring   = true
data_retention_days = 90

Modify workflow to use environment-specific variables:

- name: Terraform Plan
  run: |
    terraform -chdir=terraform/main plan \
      -var-file=environments/${{ github.event.inputs.environment }}.tfvars \
      -out=tfplan

Advanced Patterns

Matrix Deployments for Multiple Environments

jobs:
  terraform-plan:
    strategy:
      matrix:
        environment: [dev, staging, production]
    name: Plan - ${{ matrix.environment }}
    runs-on: ubuntu-latest
    environment: ${{ matrix.environment }}
    
    steps:
      - uses: actions/checkout@v4
      
      - uses: aws-actions/configure-aws-credentials@v4
        with:
          role-to-assume: ${{ secrets[format('AWS_ROLE_ARN_{0}', matrix.environment)] }}
          aws-region: us-east-1
      
      - uses: hashicorp/setup-terraform@v3
      
      - name: Terraform Plan
        run: |
          terraform -chdir=terraform/main plan \
            -var-file=environments/${{ matrix.environment }}.tfvars \
            -out=tfplan-${{ matrix.environment }}

Drift Detection Scheduled Job

.github/workflows/drift-detection.yml:

name: Terraform Drift Detection

on:
  schedule:
    - cron: '0 6 * * *'  # Daily at 6 AM UTC
  workflow_dispatch:

permissions:
  id-token: write
  contents: read
  issues: write

jobs:
  detect-drift:
    name: Detect Infrastructure Drift
    runs-on: ubuntu-latest
    
    steps:
      - uses: actions/checkout@v4
      
      - uses: aws-actions/configure-aws-credentials@v4
        with:
          role-to-assume: ${{ secrets.AWS_ROLE_ARN }}
          aws-region: us-east-1
      
      - uses: hashicorp/setup-terraform@v3
      
      - name: Terraform Init
        run: terraform -chdir=terraform/main init
      
      - name: Terraform Plan
        id: plan
        run: |
          terraform -chdir=terraform/main plan -detailed-exitcode -no-color > plan.txt
        continue-on-error: true
      
      - name: Create Issue on Drift
        if: steps.plan.outputs.exitcode == 2
        uses: actions/github-script@v7
        with:
          script: |
            const fs = require('fs');
            const plan = fs.readFileSync('plan.txt', 'utf8');
            
            await github.rest.issues.create({
              owner: context.repo.owner,
              repo: context.repo.repo,
              title: '⚠️ Infrastructure Drift Detected',
              body: `Drift detected in Terraform state.\n\n\`\`\`\n${plan}\n\`\`\``,
              labels: ['drift', 'infrastructure']
            });

Cost Estimation with Infracost

Add to .github/workflows/ci.yml:

- name: Setup Infracost
  uses: infracost/actions/setup@v2
  with:
    api-key: ${{ secrets.INFRACOST_API_KEY }}

- name: Generate cost estimate
  run: |
    infracost breakdown \
      --path=terraform/main \
      --format=json \
      --out-file=/tmp/infracost.json

- name: Post cost comment
  run: |
    infracost comment github \
      --path=/tmp/infracost.json \
      --repo=$GITHUB_REPOSITORY \
      --github-token=${{ secrets.GITHUB_TOKEN }} \
      --pull-request=${{ github.event.pull_request.number }}

Troubleshooting

"Error: configuring Terraform AWS Provider: failed to get shared config profile"

Solution: Ensure AWS credentials are properly configured in GitHub Actions:

- uses: aws-actions/configure-aws-credentials@v4
  with:
    role-to-assume: ${{ secrets.AWS_ROLE_ARN }}
    aws-region: us-east-1

"Error: Error acquiring the state lock"

Cause: Another Terraform operation is running or a previous operation failed to release the lock.

Solution:

# Force unlock (use with caution)
terraform -chdir=terraform/main force-unlock <LOCK_ID>

"Error: InvalidClientTokenId: The security token included in the request is invalid"

Cause: OIDC provider not configured correctly or role ARN is incorrect.

Solution:

  1. Verify the AWS_ROLE_ARN secret matches bootstrap output
  2. Check OIDC provider trust policy includes your repository
  3. Ensure GitHub Actions has id-token: write permission

Format Check Failing

Error: Terraform files not properly formatted.

Solution:

# Fix formatting locally
terraform fmt -recursive terraform/

# Check what would change
terraform fmt -check -recursive terraform/

# Commit and push
git add terraform/
git commit -m "fix: format terraform files"
git push

State Backend Not Found

Error: "Error: Failed to get existing workspaces: S3 bucket does not exist"

Cause: Backend configuration references a bucket that doesn't exist.

Solution:

  1. Verify bootstrap was applied: terraform -chdir=terraform/bootstrap output
  2. Update backend configuration in terraform/main/main.tf with correct bucket name
  3. Re-run terraform init

Manual Approval Not Showing

Cause: Production environment not configured or reviewers not set.

Solution:

  1. Go to Settings → Environments → production
  2. Enable "Required reviewers"
  3. Add at least one reviewer
  4. Re-run the workflow

Cleanup

Destroy all resources:

# Run the teardown script
./tear-down.sh

# Or manually
terraform -chdir=terraform/main destroy
terraform -chdir=terraform/bootstrap destroy

tear-down.sh example:

#!/bin/bash
set -e

echo "Destroying main infrastructure..."
terraform -chdir=terraform/main destroy -auto-approve

echo "Destroying bootstrap resources..."
terraform -chdir=terraform/bootstrap destroy -auto-approve

echo "Cleanup complete!"

Best Practices

  1. Always run terraform fmt before committing
  2. Use meaningful commit messages that describe infrastructure changes
  3. Review plans carefully before approving deployments
  4. Enable branch protection on main branch
  5. Use separate AWS accounts for dev/staging/production
  6. Monitor state file changes for unauthorized modifications
  7. Implement drift detection to catch manual changes
  8. Version your Terraform providers to ensure consistency
  9. Use workspaces or separate backends for different environments
  10. Document custom modules and complex configurations

FAQ

What does the infrastructure-cicd-data-engineering skill do?

Deploy data infrastructure changes using CI/CD patterns with GitHub Actions, Terraform, and AWS OIDC authentication

How do I install infrastructure-cicd-data-engineering?

Run npx skills add https://github.com/reason-machines/data-skills --skill infrastructure-cicd-data-engineering in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/infrastructure-cicd-data-engineering/ (personal) or .claude/skills/infrastructure-cicd-data-engineering/ (project).

Which AI agents can use infrastructure-cicd-data-engineering?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is infrastructure-cicd-data-engineering safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains infrastructure-cicd-data-engineering?

It is published by reason-machines in reason-machines/data-skills. It has 1,574 recorded installs.

More from reason-machines/data-skills

View all →

apache-airflow-orchestration

reason-machines/data-skills

Expert knowledge of Apache Airflow for building, scheduling, and monitoring data pipelines and workflows

DevOps & Cloud2.4K installs

datatalks-data-engineering-zoomcamp

reason-machines/data-skills

Free 9-week data engineering course covering Docker, Terraform, Kestra, BigQuery, dbt, Spark, and Kafka with hands-on projects

Data & Databases2.4K installs

llm-public-opinion-analytics-assistant

reason-machines/data-skills

Multi-platform hot search crawler and LLM-powered public opinion analysis system with clustering, sentiment analysis, and multi-channel push notifications

AI & Agents2.4K installs

roblox-mm2-analytics-toolkit

reason-machines/data-skills

Analytics and inventory management toolkit for Roblox Murder Mystery 2 gameplay optimization

Data & Databases2.4K installs

mm2-analytics-roblox-tracker

reason-machines/data-skills

Analyze Murder Mystery 2 gameplay data, track inventory, and optimize strategy using this Roblox analytics toolkit

Data & Databases2.4K installs

mm2-roblox-analytics-toolkit

reason-machines/data-skills

Murder Mystery 2 gameplay analytics, inventory tracking, and strategy optimization toolkit for Roblox

Data & Databases2.4K installs

Popular devops & cloud skills

View category →

microsoft-foundry

microsoft/azure-skills

Build, deploy, evaluate, optimize, fine-tune, and manage Microsoft Foundry agents, models, and resources end to end. USE FOR: foundry, azd ai agent, azd provision/deploy, hosted agent scaffold/develop/run/deploy/troubleshoot, prompt agent create, managed harness agent create, GitHub Copilot harness agent, create agent, update agent, add tool to agent, invoke agent, agent insights, evaluate agent, batch eval, continuous eval, continuous monitoring, agent CI/CD, optimize prompt, improve prompt, optimize agent instructions, Agent Optimizer scaffold, dataset curation from traces, deploy model, model fine-tuning (SFT/DPO/RFT), Foundry project, RBAC, role assignment, permissions, quota, capacity, region, deployment failure, AI Services, create Foundry resource, knowledge index, customize deployment, onboard, availability, training-data, grader, distillation, large file upload. DO NOT USE FOR: Azure Functions, App Service, general Azure deploy (use azure-deploy), general Azure prep (use azure

OfficialDevOps & Cloud579.1K installs

azure-diagnostics

microsoft/azure-skills

Debug Azure production issues on Azure using AppLens, Azure Monitor, resource health, and safe triage. WHEN: debug production issues, troubleshoot app service, app service high CPU, app service deployment failure, troubleshoot container apps, container app 503 or target port mismatch, troubleshoot functions, function telemetry missing or stopped after a config/connection-string change, troubleshoot AKS, VM RDP, Linux SSH, VM black screen, can't connect to VM, reset VM password, NSG or firewall blocking, kubectl cannot connect, kube-system/CoreDNS failures, pod pending, crashloop, node not ready, upgrade failures, analyze logs, KQL, insights, image pull failures, cold start issues, health probe failures, resource health, root cause of errors, troubleshoot event hubs, troubleshoot service bus, messaging SDK error, AMQP connection failure, message lock lost, lock renewal during long-running processing, service bus dead letter.

OfficialDevOps & Cloud569.8K installs

azure-prepare

microsoft/azure-skills

Prepare azd-based Azure projects for deployment: generates azure.yaml, infrastructure (Bicep/Terraform), and Dockerfiles for the Azure Developer CLI (azd) workflow. USE ONLY when the user explicitly wants to use azd as the deployment tool, or the project already has an azure.yaml file. DO NOT USE FOR: non-azd deployments, Python App Service code-only deploys (use python-appservice-deploy), or cross-cloud migration (use azure-cloud-migrate). WHEN: prepare app for azd, create azure.yaml, set up azd infrastructure, modernize app for Azure with azd, deploy with azd, function app, timer trigger, service bus trigger, event-driven function, managed identity, generate Bicep, generate Terraform, create and deploy to Azure.

OfficialDevOps & Cloud569K installs

azure-ai

microsoft/azure-skills

Use for Azure AI: Search, Speech, OpenAI, Document Intelligence. Helps with search, vector/hybrid search, speech-to-text, text-to-speech, transcription, OCR. WHEN: AI Search, query search, vector search, hybrid search, semantic search, speech-to-text, text-to-speech, transcribe, OCR, convert text to speech.

OfficialDevOps & Cloud568.8K installs

azure-deploy

microsoft/azure-skills

Execute Azure deployments for ALREADY-PREPARED applications that have existing .azure/deployment-plan.md and infrastructure files. DO NOT use this skill when the user asks to CREATE a new application — use azure-prepare instead. This skill runs azd up, azd deploy, terraform apply, and az deployment commands with built-in error recovery. Requires .azure/deployment-plan.md from azure-prepare and validated status from azure-validate. WHEN: "run azd up", "run azd deploy", "execute deployment", "push to production", "push to cloud", "go live", "ship it", "bicep deploy", "terraform apply", "publish to Azure", "launch on Azure". DO NOT USE WHEN: "create and deploy", "build and deploy", "create a new app", "set up infrastructure", "create and deploy to Azure using Terraform" — use azure-prepare for these.

OfficialDevOps & Cloud568.6K installs

azure-validate

microsoft/azure-skills

Pre-deployment validation for Azure readiness. Run deep checks on configuration, infrastructure (Bicep or Terraform), RBAC role assignments, managed identity permissions, and prerequisites before deploying. WHEN: validate my app, check deployment readiness, run preflight checks, verify configuration, check if ready to deploy, validate azure.yaml, validate Bicep, test before deploying, troubleshoot deployment errors, validate Azure Functions, validate function app, validate serverless deployment, verify RBAC roles, check role assignments, review managed identity permissions, what-if analysis, validate Container Apps deployment.

OfficialDevOps & Cloud568K installs