google-cloud-solution-architecture

name	google-cloud-solution-architecture
metadata	{"category":"MultiProductSolutions"}
description	Interactively discovers requirements for a specific cloud workload and generates design recommendations and architectural guidance to build a multi-product solution in Google Cloud. Use this skill to generate holistic, end-to-end design recommendations and architectural guidance for complex, multi-product workloads on Google Cloud for specific use cases. Don't use this skill when other specialized skills (e.g., product-specific or google-cloud-recipe-*) directly address the user's workload or use case.

Google Cloud solution-architecture workflow

Overview of the workflow

The workflow consists of the following phases:

• Phase 1: Requirements discovery. Gather detailed requirements related to the cloud workload or use case that the user needs assistance for.
• Phase 2: Solution architecture. Use the requirements that were gathered in Phase 1 to generate a detailed solution architecture for the cloud workload or use case.
• Phase 3: Solution validation. Create a plan to validate the generated solution, generate validation instructions and scripts, and provide them to the user to execute (or perform a dry-run validation with explicit permission from the user).
• Phase 4: Solution packing and presentation. Consolidate the generated content and present the solution.

Important notes about the workflow:

• Strict phase separation: During Phase 1 (Requirements discovery), when you ask the user clarifying questions, don't recommend, propose, or outline any architectural designs, technical decompositions, cloud services, or component mappings. Proposing solutions before functional and non-functional requirements are thoroughly assessed causes confirmation bias and risks anchoring the solution on specific products, features, or tools prematurely.

• Iterative approval & task transitions: For each deliverable in this workflow (technical decompositions, product recommendations, diagrams, architectural descriptions, and deployment scripts), explicitly present your output to the user for approval. If the user requests modifications, iteratively revise the content until approved before progressing to the subsequent task or phase.

• No autonomous execution of code and scripts: Don't run any scripts or code that you generate without explicit, unambiguous permission from the user. Executing scripts autonomously can provision unintended cloud resources (incurring unexpected costs), mutate live infrastructure, or pose security and safety risks. Always offer the option for the user to execute the commands manually.

• When you can skip certain phases: If the user's prompt indicates that a specific phase or task in this workflow is already completed or approved (e.g., "requirements discovery stage is completed", "product selection is approved", or "architecture is confirmed"), don't repeat that phase or task. Instead, skip directly to the requested task (such as generating the technical decomposition, recommending products, or compiling the solution guide).

Phase 1: Requirements discovery

1. Gather the following requirements related to the workload or use case for which the user needs assistance.

   CRITICAL: You MUST NOT generate any architecture designs, product recommendations, or technical decompositions until the user provides these requirements.

   • Functional requirements: Ask the user to describe the business processes, activities, and use cases of their workload.
   • Non-functional requirements: Ask the user to describe requirements for security, privacy, compliance, reliability, disaster recovery, cost, operations, performance, and sustainability.
     • CRITICAL: If non-functional requirements are missing or incomplete, you MUST ask the user to describe the requirements and explicitly explain why they are important (e.g., because they directly dictate operational SLAs, availability tiers, scaling configuration, cost budgets, resource types, and the security posture) when asking the user to supply them.
   • Current state: Ask whether the workload currently runs on other cloud providers or on-premises (if yes, prompt for the architecture of the existing deployment).
   • System dependencies: Ask the user to describe any dependencies between their application and other workloads, products, systems, or tools.

2. Review the input that the user has provided so far, and check whether there are any ambiguities or contradictions (e.g., conflicting goals like complete network isolation with zero internet exposure vs. real-time ingestion from public APIs).

   If you identify any ambiguities or contradictions in the user's requirements, you must:

   • Clearly describe the ambiguities and contradictions.
   • Explain why the contradictory requirements cannot be simultaneously satisfied.
   • Request the user to clarify their trade-off preferences and choices to resolve the ambiguities and contradictions.
     • If the user delegates the choice to you (e.g., the user replies with "do what you think is best" or "you decide"), then provide a clear suggestion to resolve the ambiguity or contradiction, explain your reasoning, and ask the user to approve your suggestion.

   CRITICAL: Until all the ambiguities and contradictions that you identify are resolved, don't recommend or generate any architecture design, technical decomposition, or Google Cloud product recommendations. Ambiguous or contradictory requirements lead to invalid architectural assumptions.

3. Generate a technical decomposition of the components of the workload that breaks down the solution into logical components. Present it to the user and obtain approval before proceeding to Phase 2.

   CRITICAL: Before proceeding to Phase 2, ensure that the user has approved the technical decomposition. Misalignment of the technical decomposition with the user's requirements will invalidate the outputs of the subsequent phases in this workflow.

Phase 2: Solution architecture

Use the approved requirements from Phase 1 to generate a comprehensive solution architecture.

Ground all generated content

For each task in this phase, to ensure that the generated content aligns with the latest and official Google Cloud guidance, you must ground the generated content by using the following resources:

• Google Developer Knowledge MCP server
  • Server: https://developerknowledge.googleapis.com/mcp
  • Tools:
  • developerknowledge:search_documents
  • developerknowledge:get_documents
  • developerknowledge:answer_query
• Relevant skills from https://github.com/google/skills
• Official Google Cloud documentation, including the following:
  • Reference architectures and design guides that are relevant to the technology category of the workload: references/architecture-guides.md
  • Decision-making guides for the products and topics that are relevant to the workload: references/decision-making-guides.md
  • Best-practices guides for the products and topics that are relevant to the workload: references/best-practices-guides.md

For each item in the generated guidance, you must include citations to the relevant official Google Cloud documentation pages.

Task 2.1: Identify Google Cloud products and features required for the workload.

1. Recommend the products and features that are appropriate for each component of the user's workload.

   CRITICAL:

   • Don't recommend any products or features that are deprecated, retired, decommissioned, or unsupported. To check the status of a product or feature, call developerknowledge:answer_query or developerknowledge:search_documents with query strings like: "{product_name} release status".
   • If multiple products or features can be used for a component of the workload, then do the following:
     • Recommend the most appropriate product or feature. When alternative products exist, the relevant product documentation might provide guidance on when to choose each product. Follow that guidance.
     • Mention the available alternative products or features.
     • Explain the pros and cons of each alternative product or feature.

2. Present the generated product recommendations to the user and ask whether any changes are needed.

   CRITICAL: Don't generate anything further (architecture diagrams, descriptions, or deployment configurations) in the same turn. Halt execution immediately after listing the product choices until the user approves the product selections.

3. After the user approves the product selections, proceed to Task 2.2.

Task 2.2: Generate an architecture diagram.

1. Generate an architecture diagram in Mermaid format: https://github.com/mermaid-js/mermaid.
2. Present the generated diagram to the user and obtain approval before proceeding to Task 2.3.

Task 2.3: Generate an architecture description.

1. Generate a description that explains the purpose of each component, the relationships between the components, and the task flow or data flow.
2. Present the generated architecture description to the user and obtain approval before proceeding to Task 2.4.

Task 2.4: Generate design recommendations.

1. Generate design recommendations and best practices to optimally configure each component in the architecture based on the workload's requirements. Important:

   • When generating design recommendations, incorporate the following:
     • Functional requirements that were gathered in Phase 1.
     • Non-functional requirements that were gathered in Phase 1.
   • To generate guidance for non-functional requirements, use the following skills, as appropriate:
     • google-cloud-waf-security
     • google-cloud-waf-reliability
     • google-cloud-waf-cost-optimization
     • google-cloud-waf-operational-excellence
     • google-cloud-waf-performance-optimization
     • google-cloud-waf-sustainability

   If any of the specialized google-cloud-waf-* skills are not available in your current workspace, derive design guidance directly from the documentation references in references/best-practices-guides.md.

2. Present the generated recommendations to the user and obtain approval before proceeding to Task 2.5.

Task 2.5: Generate deployment guidance.

1. Generate deployment guidance, including infrastructure-as-code and instructions to enable the user to deploy the solution.
2. Present the generated deployment guidance to the user and obtain approval before proceeding to Phase 3.

Phase 3: Solution validation

Task 3.1: Pre-deployment validation

1. Create a pre-deployment plan to statically validate the generated solution and verify that it meets the workload's requirements without provisioning live resources:
   • Deployment dry-run: Validate infrastructure syntax and preview the resources that will be provisioned using dry-run commands (e.g., terraform plan or (where supported) gcloud ... --dry-run).
   • Architecture & policy analysis: Perform static verification of network routing topologies, firewall rules, and IAM enforcement against best practices.
2. Present the static validation plan to the user and obtain explicit permission from the user to execute the dry-run commands. If the user gives permission, then run the commands; otherwise, or if the user prefers, provide the exact commands that the user can run manually.
3. Troubleshoot and fix any errors or policy discrepancies identified during dry-run checks until validation succeeds.
4. Proceed to Task 3.2

Task 3.2: Runtime validation (Post-deployment)

1. Ask the user whether they choose to deploy the infrastructure now to perform live runtime verification, or skip directly to Phase 4.
2. If the user chooses to deploy the infrastructure:
   • After the user deploys the infrastructure, generate runtime verification commands (using tools like curl, ping, or gcloud) and provide them to the user to execute, to test live endpoint reachability, networking paths, and load balancer routing.
   • Troubleshoot any deployment or runtime routing issues until checks pass.
3. Proceed to Phase 4.

Phase 4: Solution packaging and presentation

Package all the generated text and code artifacts for final presentation.

1. Consolidate the text artifacts that were generated in Phase 2 and Phase 3 into a single Markdown file named solution-architecture-guide.md, based on the template in assets/output-template.md.
2. Request the user's permission to write the code files in the user's workspace.
3. After the user gives permission, write the code files in the user's workspace.