cloud-infrastructure_skill

This skill helps you design multi-cloud architectures and implement IaC with Terraform, optimizing costs and enabling resilient deployments.

Python

2

GitHub Stars

1

Bundled Files

2 months ago

Catalog Refreshed

4 months ago

First Indexed

Readme & install

Copy the install command, review bundled files from the catalogue, and read any extended description pulled from the listing source.

Installation

Preview and clipboard use veilstrat where the catalogue uses aiagentskills.

npx veilstrat add skill 89jobrien/steve --skill cloud-infrastructure

SKILL.md5.0 KB

Overview

This skill provides practical cloud infrastructure design and deployment patterns for AWS, Azure, and GCP. It focuses on multi-cloud architecture, Infrastructure as Code (Terraform), cost optimization, and production-ready high-availability patterns. Use it to plan architecture, implement IaC, reduce costs, and harden cloud deployments.

How this skill works

The skill inspects architecture goals and recommends patterns for compute, storage, databases, networking, and resilience across AWS, Azure, and GCP. It maps use cases (serverless, containers, VMs, batch) to cloud services and supplies Terraform project layout, state management, and module design guidance. It also evaluates cost-saving levers, HA/multi-region strategies, security controls, and monitoring practices.

When to use it

Designing cloud architecture for a new application or service
Implementing Infrastructure as Code with Terraform, CloudFormation, or Pulumi
Planning multi-region or high-availability deployments and DR
Optimizing cloud costs and right-sizing resources
Defining security, compliance, and operational monitoring requirements

Best practices

Structure IaC with reusable, single-responsibility modules and per-environment state
Use remote state with locking and separate state files for dev/staging/prod
Apply least privilege with IAM roles, enable MFA, and run regular access reviews
Deploy across multiple AZs, use load balancers, and replicate databases for failover
Automate cost controls: lifecycle policies, reserved/spot instances, right-sizing and autoscaling

Example use cases

Design an event-driven serverless backend using Lambda/Functions/Cloud Functions with S3/Blob/Cloud Storage for objects
Build a containerized microservices platform on EKS/AKS/GKE with shared file storage and managed databases
Migrate an on-premises database to managed Cloud SQL/RDS/Aurora with automated backups and multi-AZ replication
Create a Terraform repository layout with modules for networking, compute, and databases plus remote state and locking
Implement cost optimization: identify idle resources, switch suitable workloads to spot/preemptible instances, apply lifecycle rules for archives

FAQ

Choose serverless or containers with autoscaling. Serverless for event-driven workloads and minimal ops; containers for long-running microservices requiring fine-grained control.

How should I manage Terraform state across environments?

Use remote state storage (S3/Blob/GCS) with state locking (DynamoDB/blob lease) and separate state per environment. Never commit state files to source control and version modules with tags.