AutoGineer summary
Written by AutoGineer from the skill’s own files, not by the author
The gcp-to-aws skill provides a deterministic, multi-phase process to migrate Google Cloud Platform (GCP) workloads to AWS. It supports infrastructure migration via Terraform analysis and AI workload migration by mapping models to Amazon Bedrock. The skill enforces a strict state machine, requiring discovery, clarification, design, estimation, and generation phases to ensure a reliable migration path. It includes specific logic for handling hybrid stacks, AI provider transitions, and complex infrastructure clustering.
What it does
- Discovers GCP resources from Terraform, application code, or billing data.
- Clarifies migration requirements through a structured questionnaire.
- Designs AWS architecture based on GCP workload types and AI model requirements.
- Estimates costs for the proposed AWS infrastructure and AI services.
- Generates migration artifacts including Terraform configurations and AI provider adapters.
- Provides specialized guidance for migrating AI workloads from Gemini or OpenAI to Amazon Bedrock.
When to use it
- When you need to migrate existing GCP infrastructure to AWS.
- When you are looking to move AI-driven applications from GCP or OpenAI to Amazon Bedrock.
- When you have Terraform files or billing exports and need a structured migration plan.
- When you require a step-by-step, validated approach to re-platforming cloud services.
Advantages
- Enforces a rigorous, fail-closed state machine to prevent skipped steps.
- Provides intelligent mapping of GCP services to AWS equivalents.
- Includes specific logic for AI workload migration and model compatibility.
- Supports multi-signal discovery using IaC, code, and billing data.
- Ensures consistent artifact generation through a structured 6-phase process.
Usage examples
- “Migrate my GKE and Cloud SQL setup to AWS.”
- The agent initiates the discovery phase, analyzing your Terraform files to identify GKE and Cloud SQL resources, then guides you through the clarification and design phases for EKS and RDS.
- “I need to move my LangChain app from OpenAI to Bedrock.”
- The agent identifies the AI workload, selects the best-fit Bedrock model family, and generates the necessary provider adapters and migration documentation.
Install
Download the skill as a ZIP:
https://autogineer.com/agent-skills/cline/gcp-to-aws/downloadUnzip it into the cross-client skills folder of your project:
mkdir -p .agents/skills && unzip gcp-to-aws.zip -d .agents/skills
Documentation by Cline
GCP-to-AWS Migration Skill
Philosophy
Re-platform by default: Select AWS services that match GCP workload types (e.g., Cloud Run → Fargate, Cloud SQL → RDS).
Dev sizing unless specified: Default to development-tier capacity (e.g., db.t4g.micro, single AZ). Upgrade only on user direction.
No human one-time migration costs: Do not present human labor, professional services, or people-time work as dollar estimates or "one-time migration cost" budget categories. Vendor charges grounded in data (for example GCP data transfer egress in the infra estimate when billing exists) are allowed.
Multi-signal approach: Design phase adapts based on available inputs — Terraform IaC for infrastructure, billing data for service mapping, and app code for AI workload detection.
BigQuery /
google_bigquery_*: The skill does not recommend a specific AWS analytics or warehouse service. During Clarify, if discovery shows BigQuery (IaCgoogle_bigquery_*and/or billing rows for BigQuery), you must surface the specialist advisory before Design (seereferences/phases/clarify/clarify.md). Design output usesDeferred — specialist engagement; keep directing the user to their AWS account team and/or a data analytics migration partner through Design, Estimate, and docs (seereferences/phases/design/design-infra.mdBigQuery specialist gate).
Definitions
"Load" = Read the file using the Read tool and follow its instructions. Do not summarize or skip sections.
$MIGRATION_DIR= The run-specific directory under.migration/(e.g.,.migration/0226-1430/). Set during Phase 1 (Discover).
Context Loading Rules
Each phase loads reference files on demand. To keep per-turn context manageable and prevent instruction-following degradation:
Budget: Each phase should load no more than ~800 lines of instructions (excluding user artifacts like JSON profiles and MCP tool results).
Conditional loading: Reference files with trigger conditions (e.g.,
agentic_profile.is_agentic == true) MUST NOT be loaded unless the condition is met. Do not speculatively load files.No duplication: Model mapping tables, pricing data, and shared warnings exist in one canonical file. Other files reference them; they do not copy them inline.
Progressive depth: Phase orchestrators (
design.md,generate.md) contain short routing logic that points to detailed sub-files. Load the sub-file only when its path is selected.
Conditional reference files (load ONLY when condition is true):
| File | Condition |
|---|---|
design-refs/ai-gemini-to-bedrock.md | ai-workload-profile.json exists AND summary.ai_source = "gemini" or "both" |
design-refs/ai-openai-to-bedrock.md | ai-workload-profile.json exists AND summary.ai_source = "openai" or "both" |
design-refs/ai-anthropic-to-bedrock.md | ai-workload-profile.json exists AND summary.ai_source = "anthropic" |
design-refs/ai.md | ai-workload-profile.json exists AND summary.ai_source = "other" |
design-refs/design-ref-harness.md | agentic_profile.is_agentic == true AND ai_constraints.agentic.migration_approach == "harness" |
design-refs/design-ref-agentic-to-agentcore.md | agentic_profile.is_agentic == true AND ai_constraints.agentic.migration_approach == "strands" |
shared/retarget-gotchas.md | agentic_profile.is_agentic == true AND ai_constraints.agentic.migration_approach == "retarget" |
When adding new reference files, verify the phase's total loaded instructions remain under budget. If a new file would exceed ~800 lines when combined with other loaded refs, split it or make it conditional.
Hybrid stack budget warning:
When both gcp-resource-inventory.json AND ai-workload-profile.json exist, the combined design refs will approach the ~800-line budget. Output this warning to the user before loading the AI design refs:
"⚠️ This is a large hybrid stack (infrastructure + AI workloads). To ensure complete and accurate recommendations, consider running the migration in two separate passes:
Pass 1 — Infrastructure: Run with only your Terraform files to get infra mapping, Terraform generation, and cost estimates.
Pass 2 — AI workloads: Run with only your application code to get Bedrock model recommendations, provider adapters, and AI migration artifacts.
Continue with the combined run? (Y/N)"
If the user chooses to continue, proceed with the combined run. Load AI refs after infra refs to preserve infra instruction fidelity. If the user declines, stop and instruct them to re-run with a single input source type.
This warning is advisory only — it does not block the run.
Prerequisites
User must provide at least one GCP source:
Terraform IaC:
.tffiles (with optional.tfvars,.tfstate)Application code: Source files with GCP SDK or AI framework imports
Billing data: GCP billing/cost/usage export files (CSV or JSON)
If none of the above are found, stop and ask user to provide at least one source type.
State Machine
This is the execution controller. After completing each phase, consult this table to determine the next action.
| Current State | Condition | Next Action |
|---|---|---|
discover | phases.discover != "completed" | Load references/phases/discover/discover.md |
clarify | phases.discover == "completed" AND phases.clarify != "completed" | Load references/phases/clarify/clarify.md |
design | phases.clarify == "completed" AND phases.design != "completed" | Load references/phases/design/design.md |
estimate | phases.design == "completed" AND phases.estimate != "completed" | Load references/phases/estimate/estimate.md |
generate | phases.estimate == "completed" AND phases.generate != "completed" | Load references/phases/generate/generate.md |
complete | phases.generate == "completed" AND phases.feedback == "pending" | Set phases.feedback to "completed" (user had two chances), then migration complete |
complete | phases.generate == "completed" AND phases.feedback == "completed" | Migration planning complete |
How to determine current state (deterministic):
Read
$MIGRATION_DIR/.phase-status.jsonIf
current_phaseexists, use it (must match one of: discover, clarify, design, estimate, generate, complete)Otherwise use ordered phase evaluation:
discover→clarify→design→estimate→generatePick the first phase in that order where
phases.<phase> != "completed"; if none, state iscomplete
Phase gate checks: If prior phase incomplete, do not advance (e.g., cannot enter estimate without completed design).
Clarify is mandatory: Do not load references/phases/design/design.md, references/phases/estimate/estimate.md, or references/phases/generate/generate.md unless $MIGRATION_DIR/.phase-status.json exists and phases.clarify is exactly "completed". A preferences.json file alone is not sufficient proof that Clarify ran. If the user asks to skip Clarify or jump straight to Design, cost estimate, or artifact generation, refuse briefly, then load references/phases/clarify/clarify.md and run Phase 2. There is no exception for "quick" or "obvious" migrations.
Feedback checkpoints: Feedback is not a sequential phase — it is offered at two interleaved checkpoints (after Discover and after Estimate). See the Feedback Checkpoints section below for details.
Handoff Gate Orchestration (Fail Closed)
Load references/shared/handoff-gates.md when executing any phase completion step.
Single
$MIGRATION_DIR: Use one run directory for the entire migration. Do not mix artifacts across.migration/*/sessions.Re-read from disk: Before each phase (and before each handoff gate), Read required artifacts from
$MIGRATION_DIR/. Do not rely on chat memory.Advance only on
HANDOFF_OK: A phase is complete only when its orchestrator emitsHANDOFF_OK | phase=<name> | artifacts=.... Do not load the next phase without it.On
GATE_FAIL: Output the failure line(s) to the user in plain language. Do NOT modify artifacts to pass the gate. Do NOT continue to the next phase. Tell the user which phase to re-run.Re-entry: Re-running an earlier phase after downstream phases completed requires explicit user confirmation; downstream phases must be reset to
"pending". Seehandoff-gates.mdre-entry table.
Generate phase additionally loads references/shared/validate-artifacts.md before writing migration-report.html.
State Validation
When reading $MIGRATION_DIR/.phase-status.json, validate before proceeding:
Multiple sessions: If multiple directories exist under
.migration/, list them with their phase status and ask: [A] Resume latest, [B] Start fresh, [C] Cancel.Invalid JSON: If
.phase-status.jsonfails to parse, STOP. Output: "State file corrupted (invalid JSON). Delete the file and restart the current phase."Unrecognized phase: If
phasesobject contains a phase not in {discover, clarify, design, estimate, generate, feedback}, STOP. Output: "Unrecognized phase: [value]. Valid phases: discover, clarify, design, estimate, generate, feedback."Unrecognized status: If any
phases.*value is not in {pending, in_progress, completed}, STOP. Output: "Unrecognized status: [value]. Valid values: pending, in_progress, completed."Invalid
current_phase(if present): Ifcurrent_phaseis not in {discover, clarify, design, estimate, generate, complete}, STOP. Output: "Unrecognized current_phase: [value]. Valid values: discover, clarify, design, estimate, generate, complete."Out-of-order completion: For ordered phases [discover, clarify, design, estimate, generate], if any later phase is
"completed"while an earlier phase is not"completed", STOP. Output: "Inconsistent phase ordering detected. Reconcile.phase-status.jsonbefore resuming."Multiple active phases: Across core phases {discover, clarify, design, estimate, generate}, at most one phase may be
"in_progress". If >1, STOP. Output: "Multiple phases are in_progress. Keep only one active phase before resuming."
State Management
Migration state lives in $MIGRATION_DIR (.migration/[MMDD-HHMM]/), created by Phase 1 and persisted across invocations.
.phase-status.json schema:
{
"migration_id": "0226-1430",
"last_updated": "2026-02-26T15:35:22Z",
"current_phase": "design",
"phases": {
"discover": "completed",
"clarify": "completed",
"design": "in_progress",
"estimate": "pending",
"generate": "pending",
"feedback": "pending"
}
}Status values: "pending" → "in_progress" → "completed". Never goes backward.
For core phases (discover, clarify, design, estimate, generate), at most one phase may be "in_progress" at any time.
current_phase is optional but recommended; when present it is authoritative.
The .migration/ directory is automatically protected by a .gitignore file created in Phase 1.
Phase Status Update Protocol
Use read-merge-write updates for .phase-status.json:
Read the current file before every update.
Change only the phase keys being advanced and
last_updated.Keep prior completed phases unchanged.
Set
current_phaseto the next deterministic phase (orcompleteafter generate).Write the full file in the same turn as your final phase work message.
Example — after completing the Clarify phase, write $MIGRATION_DIR/.phase-status.json with:
{
"migration_id": "MMDD-HHMM",
"last_updated": "2026-02-26T15:35:22Z",
"current_phase": "design",
"phases": {
"discover": "completed",
"clarify": "completed",
"design": "pending",
"estimate": "pending",
"generate": "pending",
"feedback": "pending"
}
}Replace MMDD-HHMM with the actual migration ID, generate the last_updated ISO 8601 UTC timestamp yourself, and set each phase to its correct status at that point.
Phase Summary Table
| Phase | Inputs | Outputs | Reference |
|---|---|---|---|
| Discover | .tf files, app source code, and/or billing exports (at least one required) | gcp-resource-inventory.json, gcp-resource-clusters.json, ai-workload-profile.json, billing-profile.json, .phase-status.json updated (outputs vary by input) | references/phases/discover/discover.md |
| Clarify | Discovery artifacts (gcp-resource-inventory.json, gcp-resource-clusters.json, ai-workload-profile.json, billing-profile.json — whichever exist) | preferences.json, .phase-status.json updated | references/phases/clarify/clarify.md |
| Design | preferences.json + discovery artifacts | aws-design.json (infra), aws-design-ai.json (AI), aws-design-billing.json (billing-only) | references/phases/design/design.md |
| Estimate | aws-design.json or aws-design-billing.json or aws-design-ai.json, preferences.json | estimation-infra.json or estimation-ai.json or estimation-billing.json, .phase-status.json updated | references/phases/estimate/estimate.md |
| Generate | estimation-infra.json or estimation-ai.json or estimation-billing.json, aws-design.json or aws-design-billing.json or aws-design-ai.json, preferences.json | generation-infra.json or generation-ai.json or generation-billing.json + terraform/, scripts/, ai-migration/, validation-report.json (when infra route active), MIGRATION_GUIDE.md, README.md, .phase-status.json updated | references/phases/generate/generate.md |
| Feedback | .phase-status.json (discover completed minimum), all existing migration artifacts | feedback.json, trace.json, .phase-status.json updated | references/phases/feedback/feedback.md |
MCP Servers
awspricing (for cost estimation):
Provides
get_pricing,get_pricing_service_codes,get_pricing_service_attributestoolsOnly needed during Estimate phase. Discover and Design do not require it.
Primary pricing source:
references/shared/pricing-cache.md(cached 2026 rates, ±5-10% for infrastructure, ±15-25% for AI models). MCP is secondary — used only for services not found in the cache.
Files in This Skill
gcp-to-aws/
├── SKILL.md ← You are here (orchestrator + state machine)
│
├── references/
│ ├── phases/
│ │ ├── discover/
│ │ │ ├── discover.md # Phase 1: Discover orchestrator
│ │ │ ├── discover-iac.md # Terraform/IaC discovery
│ │ │ ├── discover-app-code.md # App code discovery
│ │ │ └── discover-billing.md # Billing data discovery
│ │ ├── clarify/
│ │ │ ├── clarify.md # Phase 2: Clarify orchestrator
│ │ │ ├── clarify-global.md # Category A: Global/Strategic (Q1-Q7)
│ │ │ ├── clarify-compute.md # Categories B+C: Config Gaps + Compute (Q8-Q11)
│ │ │ ├── clarify-database.md # Category D: Database (Q12–Q13b)
│ │ │ ├── clarify-ai.md # Category F: AI/Bedrock (Q14-Q22)
│ │ │ └── clarify-ai-only.md # Standalone AI-only migration flow
│ │ ├── design/
│ │ │ ├── design.md # Phase 3: Design orchestrator
│ │ │ ├── design-infra.md # Infrastructure design (IaC-based)
│ │ │ ├── design-ai.md # AI workload design (Bedrock)
│ │ │ └── design-billing.md # Billing-only design (fallback)
│ │ ├── estimate/
│ │ │ ├── estimate.md # Phase 4: Estimate orchestrator
│ │ │ ├── estimate-infra.md # Infrastructure cost analysis
│ │ │ ├── estimate-ai.md # AI workload cost analysis
│ │ │ └── estimate-billing.md # Billing-only cost analysis
│ │ ├── generate/
│ │ │ ├── generate.md # Phase 5: Generate orchestrator
│ │ │ ├── generate-infra.md # Infrastructure migration plan
│ │ │ ├── generate-ai.md # AI migration plan
│ │ │ ├── generate-billing.md # Billing-only migration plan
│ │ │ ├── generate-artifacts-infra.md # Terraform configurations
│ │ │ ├── generate-artifacts-scripts.md # Migration scripts
│ │ │ ├── generate-artifacts-ai.md # Provider adapter + test harness
│ │ │ ├── generate-artifacts-billing.md # Skeleton Terraform
│ │ │ └── generate-artifacts-docs.md # MIGRATION_GUIDE.md + README.md
│ │ └── feedback/
│ │ ├── feedback.md # Phase 6: Feedback orchestrator
│ │ └── feedback-trace.md # Anonymized trace builder
│ │
│ ├── design-refs/
│ │ ├── index.md # Lookup table: GCP type → design-ref file
│ │ ├── fast-path.md # Deterministic 1:1 mappings (Pass 1)
│ │ ├── compute.md # Compute mappings (Cloud Run, GCE, GKE, etc.)
│ │ ├── database.md # Database mappings (Cloud SQL, Spanner, etc.)
│ │ ├── storage.md # Storage mappings (GCS, Filestore, etc.)
│ │ ├── networking.md # Networking mappings (VPC, LB, DNS, etc.)
│ │ ├── messaging.md # Messaging mappings (Pub/Sub, etc.)
│ │ └── ai.md # AI mappings (Vertex AI → Bedrock)
│ │
│ ├── clustering/terraform/
│ │ ├── classification-rules.md # Primary/secondary classification
│ │ ├── clustering-algorithm.md # Cluster formation rules
│ │ ├── depth-calculation.md # Topological depth calculation
│ │ └── typed-edges-strategy.md # Edge type assignment
│ │
│ └── shared/
│ ├── schema-phase-status.md # .phase-status.json schema (canonical reference)
│ ├── schema-discover-iac.md # gcp-resource-inventory + clusters schemas (loaded by discover-iac.md)
│ ├── schema-discover-ai.md # ai-workload-profile schema (loaded by discover-app-code.md and discover-iac.md Step 7d)
│ ├── schema-discover-billing.md # billing-profile schema (loaded by discover-billing.md)
│ ├── schema-estimate-infra.md # estimation-infra.json schema (loaded by estimate-infra.md at write time)
│ ├── handoff-gates.md # Fail-closed phase handoff protocol (GATE_FAIL / HANDOFF_OK)
│ ├── validate-artifacts.md # Pre-report validation (Generate Step 0; read-only)
│ ├── migration-complexity.md # Complexity tier definitions (small/medium/large) for timeline scaling
│ ├── pricing-cache.md # Cached AWS + source provider pricing (±5-25%, primary source)
│ └── bedrock-quotas.md # Bedrock TPM/RPM quota awareness, burndown rates, capacity planning| Condition | Action |
|---|---|
No GCP sources found (no .tf, no app code, no billing data) | Stop. Output: "No GCP sources detected. Provide at least one source type (Terraform files, application code, or billing exports) and try again." |
.phase-status.json missing phase gate | Stop. Output: "Cannot enter Phase X: Phase Y-1 not completed. Start from Phase Y or resume Phase Y-1." |
| awspricing unavailable after 3 attempts | Display user warning about ±5-25% accuracy. Use pricing-cache.md. Add pricing_source: "cached_fallback" to the applicable estimation-*.json file. |
| User skips questions or says "use defaults for the rest" | Apply documented defaults for remaining questions in the current batch and all subsequent batches. Phase 2 completes either way. |
aws-design.json missing required clusters | Stop Phase 4. Output: "Re-run Phase 3 to generate missing cluster designs." |
Defaults
IaC output: Terraform configurations, migration scripts, AI migration code, and documentation
Region:
us-east-1(unless user specifies, or GCP region → AWS region mapping suggests otherwise)Sizing: Development tier (e.g.,
db.t4g.microfor databases, 0.5 CPU for Fargate)Migration mode: Adapts based on available inputs (infrastructure, AI, or billing-only)
Cost currency: USD
Timeline assumption: 2-16 weeks depending on migration complexity — small (2-6 weeks), medium (6-12 weeks), large (12-18 weeks). See
references/shared/migration-complexity.mdfor tier definitions.
Workflow Execution
When invoked, the agent MUST follow this exact sequence:
Load phase status: Read
.phase-status.jsonfrom.migration/*/.If missing: Initialize for Phase 1 (Discover)
If exists: Determine current phase using deterministic rules in State Machine
Determine phase to execute:
If
current_phaseexists: execute that phase.Otherwise execute the first non-completed phase in ordered list: discover → clarify → design → estimate → generate.
If all ordered phases are completed: migration is complete (with feedback finalization rule).
Read phase reference: Load the full reference file for the target phase.
Execute ALL steps in order: Follow every numbered step in the reference file. Do not skip, optimize, or deviate.
Validate outputs: Confirm all required output files exist with correct schema before proceeding. Phase orchestrators run Completion Handoff Gate checks per
shared/handoff-gates.md.Handoff gate: Emit
HANDOFF_OKorGATE_FAILpershared/handoff-gates.md. OnGATE_FAIL, stop — do not update phase status or load the next phase.Update phase status: Only after
HANDOFF_OK. Use the Phase Status Update Protocol (read-merge-write) in the same turn as the phase's final output message.Feedback checkpoint: After a phase completes, check if feedback is due (see rules below). This runs before advancing to the next phase.
After Discover (if
phases.feedbackis"pending"): Output to user: "Would you like to share quick feedback (5 optional questions + anonymized usage data) to help improve this tool? Your data never includes resource names, file paths, or account IDs. [A] Send feedback now [B] Wait until after the Estimate phase"If user picks A → Load
references/phases/feedback/feedback.md, execute it, then continue to Clarify.If user picks B → Continue to Clarify (feedback stays
"pending").
After Estimate (if
phases.feedbackis"pending"): Output to user: "Would you like to share quick feedback now? (5 optional questions + anonymized usage data) [A] Yes, share feedback [B] No thanks, continue to Generate"If user picks A → Load
references/phases/feedback/feedback.md, execute it, then continue to Generate.If user picks B → Use the Phase Status Update Protocol to set
phases.feedbackto"completed". Continue to Generate.
After Generate: No feedback offer. If
phases.feedbackis still"pending", use the Phase Status Update Protocol to set it to"completed"(user had two chances and chose to defer/skip).
Display summary: Show user what was accomplished, highlight next phase, or confirm migration completion.
Critical constraint: Agent must strictly adhere to the reference file's workflow. If unable to complete a step, stop and report the exact step that failed.
User can invoke the skill again to resume from current_phase (or deterministic ordered evaluation when current_phase is absent).
Scope Notes
v1.0 includes:
Terraform infrastructure discovery
App code scanning (AI workload detection)
Billing data import from GCP
User requirement clarification (adaptive questions by category)
Multi-path Design (infrastructure, AI workloads, billing-only fallback)
AWS cost estimation (from pricing API or fallback)
Migration artifact generation (Terraform, scripts, AI adapters, documentation)
Optional feedback collection with anonymized telemetry
Files
- ATTRIBUTION.mdAdded by AutoGineer826 B
- LICENSELicence file added by AutoGineer10.5 KiB
- SKILL.md29.6 KiB
- data/sdk-capability-map.json1.1 KiB
- references/clustering/terraform/classification-rules.md6.5 KiB
- references/clustering/terraform/clustering-algorithm.md7.9 KiB
- references/clustering/terraform/depth-calculation.md4.5 KiB
- references/clustering/terraform/typed-edges-strategy.md4.6 KiB
- references/design-refs/ai-anthropic-to-bedrock.md2.9 KiB
- references/design-refs/ai-gemini-to-bedrock.md15.4 KiB
- references/design-refs/ai-openai-to-bedrock.md17.5 KiB
- references/design-refs/ai.md3.4 KiB
- references/design-refs/compute.md6.8 KiB
- references/design-refs/database.md9.1 KiB
- references/design-refs/design-ref-agentic-to-agentcore.md18.8 KiB
- references/design-refs/design-ref-harness.md7.9 KiB
- references/design-refs/fast-path.md10.3 KiB
- references/design-refs/index.md6.2 KiB
- references/design-refs/messaging.md3.5 KiB
- references/design-refs/networking.md5.5 KiB
- references/design-refs/security.md3.8 KiB
- references/design-refs/storage.md4.7 KiB
- references/phases/clarify/clarify-ai-only.md16.4 KiB
- references/phases/clarify/clarify-ai.md57.7 KiB
- references/phases/clarify/clarify-compute.md10.0 KiB
- references/phases/clarify/clarify-database.md10.8 KiB
- references/phases/clarify/clarify-global.md23.7 KiB
- references/phases/clarify/clarify.md50.5 KiB
- references/phases/design/design-ai.md29.6 KiB
- references/phases/design/design-billing.md12.7 KiB
- references/phases/design/design-infra.md12.8 KiB
- references/phases/design/design.md4.5 KiB
- references/phases/discover/discover-app-code.md41.7 KiB
- references/phases/discover/discover-billing.md7.2 KiB
- references/phases/discover/discover-iac.md33.0 KiB
- references/phases/discover/discover-preview.md19.9 KiB
- references/phases/discover/discover.md11.5 KiB
- references/phases/estimate/estimate-ai.md17.2 KiB
- references/phases/estimate/estimate-billing.md12.4 KiB
- references/phases/estimate/estimate-infra.md46.6 KiB
- references/phases/estimate/estimate.md8.1 KiB
- references/phases/feedback/feedback-trace.md4.5 KiB
- references/phases/feedback/feedback.md3.2 KiB
- references/phases/generate/generate-ai.md13.5 KiB
- references/phases/generate/generate-artifacts-ai.md33.6 KiB
- references/phases/generate/generate-artifacts-billing.md6.1 KiB
- references/phases/generate/generate-artifacts-docs.md21.0 KiB
- references/phases/generate/generate-artifacts-infra.md43.2 KiB
- references/phases/generate/generate-artifacts-report.md40.1 KiB
- references/phases/generate/generate-artifacts-scripts.md14.5 KiB
- references/phases/generate/generate-billing.md16.5 KiB
- references/phases/generate/generate-infra.md22.0 KiB
- references/phases/generate/generate.md7.9 KiB
- references/shared/ai-migration-guardrails.md6.6 KiB
- references/shared/ai-model-lifecycle.md8.8 KiB
- references/shared/bedrock-quotas.md7.1 KiB
- references/shared/handoff-gates.md4.7 KiB
- references/shared/migration-complexity.md11.0 KiB
- references/shared/pricing-cache.md41.2 KiB
- references/shared/pricing-fallback.md1.5 KiB
- references/shared/retarget-gotchas.md10.9 KiB
- references/shared/schema-discover-ai.md16.7 KiB
- references/shared/schema-discover-billing.md5.0 KiB
- references/shared/schema-discover-iac.md6.9 KiB
- references/shared/schema-estimate-infra.md15.6 KiB
- references/shared/schema-phase-status.md1.2 KiB
- references/shared/terraform-validation.md10.4 KiB
- references/shared/validate-artifacts.md6.2 KiB
references/phases/generate/generate-artifacts-infra.md
Generate Phase: Infrastructure Artifact Generation
Loaded by generate.md when generation-infra.json and aws-design.json exist.
Execute ALL steps in order. Do not skip or optimize.
Overview
Transform the design (aws-design.json) and migration plan (generation-infra.json) into deployable Terraform configurations. Migration scripts are generated separately by generate-artifacts-scripts.md.
Prerequisites
Read from $MIGRATION_DIR/:
aws-design.json(REQUIRED) — AWS architecture design with cluster-level resource mappingsgeneration-infra.json(REQUIRED) — Migration plan with timeline and service assignmentspreferences.json(REQUIRED) — User preferences including target region, sizing, compliancegcp-resource-clusters.json(REQUIRED) — Cluster dependency graph for ordering
Reference files (read as needed): references/design-refs/index.md and domain-specific files (compute.md, database.md, storage.md, networking.md, messaging.md, security.md, ai.md).
If any REQUIRED file is missing: STOP. Output: "Missing required artifact: [filename]. Complete the prior phase that produces it."
Output Structure
Generate $MIGRATION_DIR/terraform/ with only the files needed for domains that have resources in aws-design.json:
| File | Domain | Contains |
|---|---|---|
main.tf | core | Provider config, backend, data sources |
variables.tf | core | All input variables with types and defaults |
outputs.tf | core | Resource outputs and migration summary |
baseline.tf | security baseline | Account-wide security baseline: alternate contacts, password policy, S3 PAB, EBS encryption, Access Analyzer, IMDSv2 default, CloudTrail + S3 log bucket, AWS Budget, GuardDuty. Plus a compliance-conditional section (Config + Security Hub + standards) when preferences.json.compliance contains soc2/pci/hipaa/fedramp. Always emitted; users who want to skip it can delete this file before terraform apply. |
vpc.tf | networking | VPC, subnets, NAT, security groups, route tables |
security.tf | security | IAM roles, policies, KMS keys, Secrets Manager |
storage.tf | storage | S3 buckets, EFS, backup vaults |
database.tf | database | RDS/Aurora instances, parameter groups |
compute.tf | compute | Fargate/ECS, Lambda, EC2 |
monitoring.tf | monitoring | CloudWatch dashboards, alarms, log groups |
README.md | core | Cost tiers vs this Terraform (one stack; Balanced-aligned) |
Step 0: Plan Generation Scope
Build a generation manifest: read all resources from aws-design.json clusters, assign each to its target .tf file by aws_service:
| AWS Service | Target File |
|---|---|
| Account Alternate Contacts, IAM Account Password Policy, S3 Account Public Access Block, EBS Default Encryption, IAM Access Analyzer (ACCOUNT), EC2 Instance Metadata Defaults, CloudTrail, AWS Budgets, GuardDuty Detector, S3 buckets for CloudTrail and Config logs, AWS Config recorder/delivery/role, AWS Security Hub + standards | baseline.tf |
| VPC, Subnet, NAT Gateway, Security Group, Route Table | vpc.tf |
| IAM Role, IAM Policy, KMS Key, Secrets Manager | security.tf |
| S3, EFS, Backup Vault | storage.tf |
| RDS, Aurora, DynamoDB, ElastiCache | database.tf |
| Fargate, ECS, Lambda, EC2 | compute.tf |
| CloudWatch, SNS (for alarms) | monitoring.tf |
baseline.tfis always emitted. It is NOT driven byaws-design.jsonclusters — the resources are workload-independent account controls. The compliance-conditional subset (Config + Security Hub) is emitted within the same file whenpreferences.json.compliancecontains soc2/pci/hipaa/fedramp. Theaws_budgets_budgetresource readsestimation-infra.jsonto set itslimit_amount. See Step 1.5 below. Users who want to skip the baseline can deleteterraform/baseline.tfbeforeterraform apply.
BigQuery / specialist-deferred: If aws_service is Deferred — specialist engagement, do not generate Terraform for that resource (no Glue, Athena, Redshift, or EMR modules from the plugin). Optionally add terraform/README-BIGQUERY-DEFERRED.md with a short checklist: engage AWS account team and/or data analytics migration partner before implementing analytics infrastructure.
Step 1: Generate main.tf
Requirements:
File header comment block (first lines in
main.tf, beforeterraform {): Explain that (1) this directory implements the single architecture inaws-design.json; (2) the migration report’s Premium / Balanced / Optimized figures are three pricing scenarios fromestimation-infra.jsonfor that same map — not three separate generated stacks; (3) this Terraform is aligned with the Balanced cost scenario (default sizing/HA posture used for the middle estimate); (4) Premium = higher HA / higher $ model; Optimized = cost-optimization assumptions — users must edit IaC or add modules to realize those postures. Point readers toterraform/README.mdand themigration_summaryoutput.terraformblock:required_version >= 1.5.0,hashicorp/aws ~> 5.80, active S3 backend (see Step 1a below — do NOT comment it out)provider "aws"block:region = var.aws_region,default_tagswith Project, Environment, ManagedBy, MigrationIdData sources:
aws_caller_identity,aws_region,aws_availability_zones
Step 1a: Remote state backend
Always emit an active (not commented-out) S3 backend block in main.tf. Local state is not safe for production — terraform.tfstate stores resource metadata and sensitive values in plaintext on the local filesystem.
Emit the following backend block inside the terraform {} block in main.tf:
backend "s3" {
# Bootstrap: these resources are created by baseline.tf.
# First run: terraform init -backend=false && terraform apply \
# -target=aws_s3_bucket.tfstate \
# -target=aws_s3_bucket_versioning.tfstate \
# -target=aws_s3_bucket_server_side_encryption_configuration.tfstate \
# -target=aws_s3_bucket_public_access_block.tfstate \
# -target=aws_dynamodb_table.tfstate_lock
# Then re-run: terraform init (migrates local state to S3)
bucket = "<project_name>-<environment>-tfstate-<account_id>" # TODO: substitute values
key = "migration/terraform.tfstate"
region = "<aws_region>" # TODO: substitute target region
dynamodb_table = "<project_name>-<environment>-tfstate-lock" # TODO: substitute values
encrypt = true
}Also emit the following resources in baseline.tf (append after the always-on resources):
# Remote state backend infrastructure
resource "aws_s3_bucket" "tfstate" {
bucket = "${var.project_name}-${var.environment}-tfstate-${data.aws_caller_identity.current.account_id}"
tags = merge(local.baseline_tags, { Component = "terraform-state" })
}
resource "aws_s3_bucket_versioning" "tfstate" {
bucket = aws_s3_bucket.tfstate.id
versioning_configuration { status = "Enabled" }
}
resource "aws_s3_bucket_server_side_encryption_configuration" "tfstate" {
bucket = aws_s3_bucket.tfstate.id
rule {
apply_server_side_encryption_by_default {
sse_algorithm = "aws:kms"
}
}
}
resource "aws_s3_bucket_public_access_block" "tfstate" {
bucket = aws_s3_bucket.tfstate.id
block_public_acls = true
block_public_policy = true
ignore_public_acls = true
restrict_public_buckets = true
}
resource "aws_dynamodb_table" "tfstate_lock" {
name = "${var.project_name}-${var.environment}-tfstate-lock"
billing_mode = "PAY_PER_REQUEST"
hash_key = "LockID"
attribute {
name = "LockID"
type = "S"
}
tags = merge(local.baseline_tags, { Component = "terraform-state" })
}Add a Bootstrap section to terraform/README.md explaining the two-step init process.
Step 1b: Generate terraform/README.md
Always create $MIGRATION_DIR/terraform/README.md when generating Terraform (same pass as Step 1).
Required sections:
What this directory is — Implements one deployable baseline from
aws-design.json(andgeneration-infra.json/preferences.jsonas applicable).Cost tiers in the migration report — Premium, Balanced, and Optimized are monthly cost scenarios in
estimation-infra.jsonfor the same service mapping; order is high → mid → low estimate.Which scenario this Terraform matches — Balanced (primary comparison to GCP; default migration posture in the advisor model). Premium and Optimized are not auto-generated as alternate roots.
If you need Premium or Optimized in production — Manually adjust instance classes, Multi-AZ, Spot mix, Reserved Instances / Savings Plans, storage classes, etc., then re-estimate.
Artifacts — Reference
estimation-infra.json,migration-report.html/MIGRATION_GUIDE.mdfor full tier tables.
Keep it under one screen of text.
Step 1.5: Generate baseline.tf
Always emitted. The baseline applies account-wide security controls that should be in place on any new AWS account. Users who do not want the baseline can delete terraform/baseline.tf before terraform apply.
Compute retention. Read
preferences.json.compliance(array of strings; may be absent or empty). Computecloudtrail_retention_daysusing this mapping, takingmax()across all declared values (use 90 if the array is empty or absent):absent /
[]→ 90soc2→ 365pci→ 365hipaa→ 2190fedramp→ 1095gdpr→ 365
Compute budget limit. Read
estimation-infra.json.projected_costs.breakdown.total.mid(or the canonical equivalent). Computebudget_limit = max(50, ceil(total_mid * 1.2)). Ifestimation-infra.jsonis missing or unreadable, use50and emit an inline comment noting that the projection was unavailable.Choose file-header variant. If
compliancecontains any ofsoc2,pci,hipaa,fedramp, emit the compliance-expansion header. Otherwise emit the base header. Both variants include a two-sentence provenance note stating per-unit rates were verified against the AWS Pricing API for us-east-1 on 2026-05-04. Substitute the resolvedcloudtrail_retention_daysvalue into the header.Emit
baseline.tfstarting with the file-header comment block and alocalsblock containing the resolvedcloudtrail_retention_daysinteger:locals { cloudtrail_retention_days = <N> }Append the always-on resources, in this order. Each resource carries the plugin's standard four default tags plus
Component = "security-baseline":aws_account_alternate_contact.operations(ACCT.01, TODO-email placeholder)aws_account_alternate_contact.billing(ACCT.01, TODO-email placeholder)aws_account_alternate_contact.security(ACCT.01, TODO-email placeholder)aws_iam_account_password_policy.baseline(ACCT.06;minimum_password_length = 14,password_reuse_prevention = 24,max_password_age = 90, all four character-class requirementstrue,hard_expiry = false)aws_s3_account_public_access_block.baseline(ACCT.08; all four flagstrue)aws_ebs_encryption_by_default.baseline(defense-in-depth;enabled = true)aws_accessanalyzer_analyzer.baseline(ACCT.11;type = "ACCOUNT")aws_ec2_instance_metadata_defaults.baseline(defense-in-depth;http_tokens = "required",http_put_response_hop_limit = 2)aws_cloudtrail.baseline(ACCT.07; multi-region, management events only,enable_log_file_validation = true)aws_s3_bucket.cloudtrail_logsplusaws_s3_bucket_public_access_block,aws_s3_bucket_server_side_encryption_configuration,aws_s3_bucket_versioning,aws_s3_bucket_lifecycle_configuration(transitions driven bylocal.cloudtrail_retention_daysper item 7), andaws_s3_bucket_policyrestricting the CloudTrail service principal byaws:SourceArnaws_budgets_budget.monthly_spend(ACCT.10;limit_amount = "<budget_limit>"from item 2; threenotificationblocks at 50/80/100%ACTUAL; TODO-email placeholders)aws_guardduty_detector.baseline(defense-in-depth;enable = true,finding_publishing_frequency = "FIFTEEN_MINUTES")
If
compliancecontains any ofsoc2,pci,hipaa,fedramp, append the compliance-conditional section, wrapped in########## Compliance-Conditional ##########/########## End Compliance-Conditional ##########dividers:aws_iam_role.config+aws_iam_role_policy_attachmentfor the managed policyAWSConfigRoleaws_config_configuration_recorder.baselinewithrecording_group { all_supported = true, include_global_resource_types = true }aws_config_delivery_channel.baselinepointing at the Config S3 bucketaws_config_configuration_recorder_status.baselinewithis_enabled = trueaws_s3_bucket.config_logsplus PAB, SSE, versioning, lifecycle (samelocal.cloudtrail_retention_days), and a bucket policy allowing theconfig.amazonaws.comservice principalaws_securityhub_account.baselineaws_securityhub_standards_subscription.fsbp(always emitted in this section)aws_securityhub_standards_subscription.pci_dss(only ifcompliancecontainspci)
Do NOT emit an NIST 800-53 standards subscription, even if
compliancecontainshipaaorfedramp. Security Hub does not provide a HIPAA-specific standard; FedRAMP attestation is out-of-band.Lifecycle rule adjustment. Omit the
STANDARD_IAtransition block when the resolved retention is less than 90 days. Omit theGLACIERtransition block when retention is less than 365 days. Both rules apply to both the CloudTrail log bucket and (when emitted) the Config log bucket.Attach inline HCL comments:
On each
aws_account_alternate_contact.*: a TODO-email warning.On
aws_cloudtrail.baseline: a collision warning for users who already have a trail in the region.On
aws_budgets_budget.monthly_spend: a TODO-email warning plus the limit-rationale comment (max(50, ceil(total_mid * 1.2)); $50 floor prevents alert noise; users may editlimit_amountdirectly post-apply).On
aws_guardduty_detector.baseline: a cost disclosure noting the 30-day free trial and ~$2–25/mo post-trial.On
aws_config_configuration_recorder.baseline: a cost disclosure ($0.003/CI continuous; $0.012/daily-CI as an opt-in for cost-sensitive users).On
aws_securityhub_account.baseline: a cost disclosure noting the 30-day free trial and ~$1–15/mo post-trial.On every defense-in-depth resource (EBS encryption, IMDSv2 account default, GuardDuty, Config, Security Hub): the literal token
defense-in-depthin the inline comment.
compute.tf modification (runs during Step 3 compute domain, not here): every
aws_launch_templateemitted for ECS-EC2, EKS node groups, or bare EC2 receives IMDSv2 enforcement unconditionally — the security baseline is always applied:metadata_options { http_tokens = "required" http_put_response_hop_limit = 1 http_endpoint = "enabled" instance_metadata_tags = "enabled" }Fargate, Lambda, and App Runner do not emit launch templates and are unaffected (no synthetic launch template is created). Hop limit
1here is intentionally different from the account-level default2inaws_ec2_instance_metadata_defaults.baseline— strict on templates the plugin owns, permissive at the account default.
Emission conditions:
Emit
baseline.tfeven whenaws-design.jsoncontains only AI or billing-only resources (no infrastructure clusters). The baseline is workload-independent.Do NOT probe for existing account resources (CloudTrail trails, Config recorders, Security Hub enrollment). Collision risk is surfaced by the inline comments listed in item 8.
Step 2: Generate variables.tf
Global variables (always include): aws_region (from preferences.json target_region), project_name, environment (from preferences.json), migration_id.
Per-cluster variables: Extract configurable values from aws_config in aws-design.json. Infer types (string, number, bool, list(string), map(string)). Use aws_config values as defaults. Deduplicate shared variables. Add GCP source as comment (e.g., # GCP source: db-custom-2-7680).
Step 2b: Generate terraform.tfvars.example and .gitignore
Always emit $MIGRATION_DIR/terraform/terraform.tfvars.example alongside variables.tf. Populate it with actual values from aws-design.json, preferences.json, and estimation-infra.json where available. Use descriptive placeholder strings (not empty values) for anything that cannot be inferred. Format:
# Copy this file to terraform.tfvars and fill in the values before running terraform plan.
# Do NOT commit terraform.tfvars to source control — it may contain sensitive values.
aws_region = "<target_region>" # from preferences.json target_region
project_name = "<your-project>" # TODO: set your project name
environment = "production" # TODO: dev | staging | production
migration_id = "<MMDD-HHMM>" # from migration run ID
# One entry per variable in variables.tf, with source annotation as commentAlso emit $MIGRATION_DIR/terraform/.gitignore with:
# Never commit actual variable values — may contain sensitive data
terraform.tfvars
*.tfvars
!terraform.tfvars.example
.terraform/
*.tfstate
*.tfstate.backupStep 3: Generate Per-Domain .tf Files
For each domain with resources in the generation manifest:
General rules:
Consult
references/design-refs/*.mdfor AWS configuration best practicesA single GCP resource may map to multiple AWS resources (1:Many expansion)
Use
gcp_configvalues fromaws-design.jsonto populate resource attributesFor
confidence: "inferred"resources, add comment:# Tailored to your setup — verify configuration (JSON confidence: inferred)For
confidence: "deterministic"resources, optional comment:# Standard pairing (fixed mapping list)Include
secondary_resourcesfrom the cluster (IAM roles, security groups)Tag every resource: Project, Environment, ManagedBy, MigrationId
Domain-specific rules:
| Domain | Key Rules |
|---|---|
| Networking | At least 2 AZs; public + private subnets; NAT gateway for private subnet internet; internet-facing ALB must terminate TLS on 443 and HTTP 80 must redirect to HTTPS; when preferences.json.compliance contains pci, hipaa, or fedramp, emit aws_flow_log for the VPC targeting a CloudWatch log group — add inline cost disclosure comment: # VPC Flow Logs: ~$0.50/GB ingested. Enabled for compliance. Disable if cost is a concern and compliance posture allows. — omit for non-compliance stacks |
| Security | Least-privilege IAM (specific ARNs, never wildcards); per-service roles for Fargate/Lambda; Secrets Manager resources with no plaintext defaults; when preferences.json.compliance contains soc2, pci, hipaa, or fedramp, emit a companion aws_secretsmanager_secret_rotation block for every aws_secretsmanager_secret resource with automatically_after_days = 30 and a TODO comment for the rotation Lambda ARN — omit the rotation block for non-compliance stacks to keep the generated Terraform immediately applyable; when preferences.json.compliance contains pci, hipaa, or fedramp, generate a customer-managed KMS key (aws_kms_key) and reference it via kms_key_id on every aws_secretsmanager_secret — omit for non-compliance stacks (AWS-managed key is sufficient) |
| Storage | Versioning enabled; SSE-S3 or SSE-KMS encryption; block public access by default; lifecycle policies; if public content is required use CloudFront/OAC instead of public bucket policy; when preferences.json.compliance contains pci, hipaa, or fedramp, emit aws_s3_bucket_logging for every application S3 bucket (not the CloudTrail/Config log buckets themselves) targeting a dedicated access-log bucket — add inline cost disclosure comment: # S3 access logging: ~$0.023/GB stored. Enabled for compliance. Disable if cost is a concern and compliance posture allows. — omit for non-compliance stacks |
| Database | Private subnets; subnet group + parameter group + security group; backups; encryption at rest (storage_encrypted = true); deletion_protection = true by default; publicly_accessible = false always — never emit publicly_accessible = true unless the user has explicitly requested it via a compliance exception in preferences.json; never emit a security group rule allowing ingress on port 5432 or 3306 from 0.0.0.0/0 — database ports must only allow ingress from the application security group CIDR or security group ID; if GCP Cloud SQL authorized_networks contains 0.0.0.0/0, emit a warnings[] entry in aws-design.json: "Cloud SQL authorized_networks includes 0.0.0.0/0 — mapped to private RDS with no public access" (add inline comment: # Set to false only when intentionally destroying this cluster); never use master_password = var.database_master_password — instead generate the master password into Secrets Manager and reference it via data source: emit aws_secretsmanager_secret + aws_secretsmanager_secret_version (with secret_string = jsonencode({password = random_password.db_master.result})) and resource "random_password" "db_master", then set master_password = jsondecode(data.aws_secretsmanager_secret_version.db_master.secret_string)["password"] on the cluster — this keeps the password out of terraform.tfvars and Terraform state plaintext |
| Compute | Fargate in private subnets; task definitions from aws_config CPU/memory; auto-scaling; for EKS clusters set endpoint_private_access = true and endpoint_public_access = false by default — add inline comment: # Public endpoint disabled. To enable kubectl access from outside the VPC set endpoint_public_access = true and restrict public_access_cidrs to known CIDRs.; every aws_ecr_repository resource must include image_scanning_configuration { scan_on_push = true } — ECR basic scanning is free and catches known CVEs before images reach production |
| Monitoring | Log groups per service; dashboard with key metrics; alarms from generation-infra.json success_metrics; 30-day log retention |
Step 4: Generate outputs.tf
Output identifiers for key resources (VPC ID, database endpoint, ECS cluster name, etc.) plus a migration_summary output (object) including at minimum:
| Key | Type / example | Purpose |
|---|---|---|
aws_region | string | From var.aws_region |
environment | string | From var.environment |
migration_id | string | From var.migration_id |
service_count | number | Count of primary logical services / resources represented |
aligned_with_estimate_tier | string | Always "balanced" for this advisor — generated IaC matches the Balanced scenario in estimation-infra.json |
cost_scenarios_modeled_in_terraform | string | e.g. "design_baseline_only" — only one stack generated; Premium/Optimized exist as pricing scenarios in estimates, not as additional Terraform trees |
Add VPC ID or other IDs when known from resources. Descriptions on every output.
Example shape:
output "migration_summary" {
description = "Migration run metadata and cost-tier alignment (Balanced baseline)"
value = {
aws_region = var.aws_region
environment = var.environment
migration_id = var.migration_id
service_count = <number>
aligned_with_estimate_tier = "balanced"
cost_scenarios_modeled_in_terraform = "design_baseline_only"
}
}Step 5: Self-Check
Verify these quality rules before reporting completion:
[ ] [ ] No wildcard IAM policies (
"Action": "*"or"Resource": "*")[ ] [ ] No default VPC references — all resources use the created VPC
[ ] [ ] No hardcoded credentials in any .tf file
[ ] [ ] Tags on every resource (Project, Environment, ManagedBy, MigrationId)
[ ] [ ] Encryption at rest on all storage (S3, EBS, RDS)
[ ] [ ] Databases and internal services use private subnets
[ ] [ ] All RDS/Aurora resources have
publicly_accessible = false[ ] [ ] No security group rule allows ingress on port 5432 or 3306 from
0.0.0.0/0[ ] [ ] ALB listeners enforce HTTPS (443) and HTTP (80) only redirects to HTTPS
[ ] [ ] No S3 bucket policy with
Principal = "*"unless explicitly approved by user requirements[ ] [ ] No
0.0.0.0/0ingress except ALB port 443[ ] [ ] Every variable has
typeanddescription[ ] [ ] Every output has
description[ ] [ ] Region from
var.aws_region, never hardcoded[ ] [ ]
terraform/README.mdexists with cost-tier vs Terraform explanation[ ] [ ]
main.tfbegins with the required cost-tier / Balanced alignment comment block[ ] [ ]
migration_summaryoutput includesaligned_with_estimate_tierandcost_scenarios_modeled_in_terraform[ ] [ ]
baseline.tfexists.[ ] [ ]
baseline.tfcontainsaws_account_alternate_contactfor each of OPERATIONS, BILLING, SECURITY, plusaws_iam_account_password_policy,aws_s3_account_public_access_block,aws_ebs_encryption_by_default,aws_cloudtrail,aws_guardduty_detector,aws_accessanalyzer_analyzer,aws_ec2_instance_metadata_defaults, andaws_budgets_budget.[ ] [ ]
baseline.tfcontains alocalsblock withcloudtrail_retention_daysset to a positive integer, and the lifecycleexpiration.daysonaws_s3_bucket_lifecycle_configuration.cloudtrail_logsequalslocal.cloudtrail_retention_days.[ ] [ ]
aws_budgets_budget.monthly_spend.limit_amountequalsmax(50, ceil(estimation-infra.json.projected_costs.breakdown.total.mid * 1.2))as a string.[ ] [ ] If
compute.tfcontains anyaws_launch_template, every such launch template hasmetadata_options { http_tokens = "required", http_put_response_hop_limit = 1 }— this applies unconditionally (the security baseline is always emitted).[ ] [ ] Every
aws_ecr_repositoryincompute.tfhasimage_scanning_configuration { scan_on_push = true }.[ ] [ ] If
compliancecontains soc2/pci/hipaa/fedramp,baseline.tfcontainsaws_config_configuration_recorder,aws_config_delivery_channel,aws_config_configuration_recorder_status,aws_securityhub_account,aws_securityhub_standards_subscriptionfor FSBP.[ ] [ ] If
compliancecontains pci, an additionalaws_securityhub_standards_subscriptionfor PCI DSS exists.[ ] [ ]
baseline.tfdoes NOT contain anyaws_securityhub_standards_subscriptionwhosestandards_arnreferencesnist-800-53, regardless of compliance values.[ ] [ ] If
complianceis empty, absent, or contains only gdpr,baseline.tfdoes NOT contain anyaws_config_*oraws_securityhub_*resources.[ ] [ ]
baseline.tfdoes NOT contain any invented SSB control IDs. Search forACCT.IAM,ACCT.S3,ACCT.EBS,ACCT.CT,ACCT.GD,ACCT.CFG,ACCT.SH,WKLD.EC2.01— all MUST have zero matches. Only bareACCT.01throughACCT.13identifiers are permitted.[ ] [ ]
baseline.tfdoes NOT mention "Trusted Advisor" anywhere (Trusted Advisor is docs-action only and out of scope).[ ] [ ] Security Hub subscribes to FSBP (always when the compliance-conditional section is emitted) and PCI DSS (only when
compliancecontainspci). No other standards subscriptions.
Phase Completion
Report generated files to the parent orchestrator. Do NOT update .phase-status.json — the parent generate.md handles phase completion.
Before reporting completion, enforce artifact output gate:
terraform/directory exists.At minimum:
terraform/main.tf,terraform/variables.tf, andterraform/outputs.tfexist.At least one domain file exists among:
vpc.tf,security.tf,storage.tf,database.tf,compute.tf,monitoring.tf.terraform/baseline.tfMUST exist (baseline is always emitted).
If this gate fails: STOP and output: "generate-artifacts-infra did not produce required Terraform artifacts; do not complete Generate Stage 2."
Generated terraform artifacts:
- terraform/README.md
- terraform/main.tf
- terraform/variables.tf
- terraform/outputs.tf
- terraform/[domain].tf (for each domain with resources)
- validation-report.json (status: <validation_status>)
Total: [N] Terraform files
Validation: <validation_status> (attempts=<N>, errors_fixed=<N>)
TODO markers: [N] items requiring manual configurationRequirements and compatibility
Written for: Claude Code
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- cline/skills · skills/gcp-to-aws · commit 2637846
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- Apache License 2.0 (redistribution allowed)
- LICENSE (added by AutoGineer from LICENSE)
- ATTRIBUTION.md (written by AutoGineer)
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