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Found 168 Skills
Free 9-week data engineering course covering Docker, Terraform, Kestra, BigQuery, dbt, Spark, and Kafka with hands-on projects
This skill should be used when the user asks to "导入阿里云资源到 Terraform", "terraform import 阿里云", "将现有云资源纳入 Terraform 管理", "阿里云资源迁移 Terraform", "生成 terraform state", "import alicloud resources", "阿里云 IaC 迁移", "阿里云 Terraform 导入", or needs to manage existing Alibaba Cloud resources with Terraform. Guides users step-by-step through environment check, authentication, resource discovery, HCL generation, state import, validation, and dependency graph. Supports both one-time migration and incremental sync.
Scaffolds new Terraform modules with standardized structure including main.tf, variables.tf, outputs.tf, versions.tf, and README.md. This skill should be used when users want to create a new Terraform module, set up module structure, or need templates for common infrastructure patterns like VPC, ECS, S3, or RDS modules.
Infrastructure-as-Code with Terraform for data engineering on AWS (S3, EC2, IAM)
Infrastructure-as-Code fundamentals for data engineering using Terraform to provision AWS resources (S3, EC2, IAM)
Infrastructure-as-Code patterns for data engineering with Terraform on AWS (S3, EC2, IAM)
Infrastructure-as-Code fundamentals for data engineers using Terraform to provision AWS resources (S3, EC2, IAM)
Create, amend, remove, and rebase patches for Terraform provider submodules using `./scripts/upstream.sh`. Use when `upgrade-provider` or manual patch work needs owning-patch lookup, patch conflict fixes, patch/hunk removal, or upstream rebase.
Provision GCP infrastructure with Terraform. Configure providers and deploy Google Cloud resources. Use when implementing IaC for GCP.
Architect and provision enterprise Azure infrastructure from workload descriptions. For cloud architects and platform engineers planning networking, identity, security, compliance, and multi-resource topologies with WAF alignment. Generates Bicep or Terraform directly (no azd). WHEN: 'plan Azure infrastructure', 'architect Azure landing zone', 'design hub-spoke network', 'plan multi-region DR topology', 'set up VNets firewalls and private endpoints', 'subscription-scope Bicep deployment'. PREFER azure-prepare FOR app-centric workflows.
Deploy Python (Flask/Django/FastAPI) code to Azure App Service Linux. WHEN: "Flask App Service", "Django App Service", "FastAPI App Service", "deploy Python to App Service". DO NOT USE FOR: Container Apps, Functions, non-Python, Terraform/Bicep/IaC, full infra — use azure-prepare.
Use when setting up CI/CD pipelines, containerizing applications, deploying to Kubernetes, or writing infrastructure as code. DevOps & Deployment covers GitHub Actions, Docker, Helm, and Terraform patterns.