cloud▌

Multi-cloud architecture design, migration planning, cost optimization, and disaster recovery across AWS, Azure, and GCP. \n \n Covers six core workflow stages: discovery, design, security, cost modeling, migration, and operations with validation checkpoints at each phase \n Implements zero-trust security, least-privilege IAM, encryption at rest and in transit, and multi-region redundancy for critical workloads \n Applies the 6Rs migration framework, Well-Architected principles, and FinOps pract

Comprehensive guide for writing and running Terraform tests with assertions, mocking, and module validation. \n \n Write test files using .tftest.hcl syntax with run blocks that execute in plan or apply mode, supporting sequential and parallel execution with optional state isolation \n Assert conditions on resource attributes, outputs, and data sources; use expect_failures to validate that invalid inputs are properly rejected \n Mock providers (Terraform 1.7.0+) simulate infrastructure behavior

When modifying Azure DevOps pipeline files (YAML files in build/azure-pipelines/), you can validate changes locally using the Azure CLI before committing. This avoids the slow feedback loop of pushing changes, waiting for CI, and checking results.

You are a cloud cost optimization expert specializing in reducing infrastructure expenses while maintaining performance and reliability. Analyze cloud spending, identify savings opportunities, and implement cost-effective architectures across AWS, Azure, and GCP.

Category: test

Reusable Terraform modules for AWS, Azure, GCP, and OCI infrastructure with standardized patterns and best practices. \n \n Provides pre-built module templates across four cloud providers covering core services like VPC/VNet, Kubernetes clusters, databases, and object storage \n Enforces consistent module structure with input variables, outputs, documentation, examples, and Terratest-based testing \n Includes validation blocks, conditional resources via count/for_each, and tagging strategies for

Complete Cloudflare platform integration with decision trees for compute, storage, AI, networking, security, and infrastructure-as-code. \n \n Covers 50+ Cloudflare products organized by use case: serverless functions (Workers, Pages), data storage (KV, D1, R2), AI/ML (Workers AI, Vectorize, Agents SDK), networking (Tunnel, Spectrum), and security (WAF, DDoS, Bot Management) \n Includes decision trees to route tasks to the right product based on requirements (e.g., \"run code\" → Workers vs. Pag

Check and manage Azure quotas and usage across regions for deployment planning and capacity validation. \n \n Azure CLI ( az quota ) is the only reliable method for checking quotas; REST API and Portal are unreliable and may show misleading \"No Limit\" values that do not indicate unlimited capacity \n Supports four core workflows: checking specific resource quotas, comparing capacity across regions, requesting quota increases, and listing all quotas for a provider \n Quota resource names do not

Recommend Azure VM sizes, scale sets, and configurations based on workload type, performance needs, and budget. \n \n Analyzes workload requirements (web, database, ML, batch, HPC) and recommends appropriate VM families, sizes, and instance counts without requiring an Azure subscription \n Supports both single VMs and VM Scale Sets (VMSS) with guidance on autoscaling, load balancing, and orchestration modes (Flexible vs Uniform) \n Queries the unauthenticated Azure Retail Prices API to provide c

Fast discovery and inventory of Azure resources across subscriptions using Resource Graph queries. \n \n Queries any Azure resource type (VMs, storage accounts, web apps, container apps, Key Vaults, etc.) across subscriptions and resource groups using KQL \n Identifies orphaned resources, missing tags, and resources in specific states without needing dedicated MCP tools \n Routes single-resource-type queries to specialized MCP tools (compute, storage, cosmos, acr, aks) when available; falls back