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APEX turns Azure platform engineering requirements into verified, deploy-ready IaC — powered by GitHub Copilot agents, real-time pricing, and built-in compliance.

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APEX

Agentic Platform Engineering eXperience for Azure.

APEX is a multi-agent workflow that turns Azure platform engineering requirements into deployable Bicep or Terraform with human approval gates across the lifecycle.

Workflow

New projects use the practical workflow: reuse captured decisions, batch authorized routine repairs, bound review closure, and check policy feasibility early. Specialists, production support and the lifecycle approval gates shown below remain. Existing projects retain their legacy contract until explicitly adopted.

%%{init: {'theme':'neutral'}}%%
sequenceDiagram
  autonumber
  participant U as User
  participant C as Orchestrator
  participant R as Requirements
  participant X as Challenger
  participant A as Architect
  participant G as Governance
  participant IaC as IaC Plan
  participant Gen as IaC Code
  participant D as Deploy
  participant W as As-Built

  Note over C: ORCHESTRATION LAYER<br/>AI prepares. Humans decide.

  U->>C: Describe infrastructure intent
  C->>R: Translate intent into structured requirements
  R-->>C: 01-requirements.md (includes iac_tool selection)
  C->>X: Challenge requirements
  X-->>C: challenge-findings-requirements.json
  C->>U: Present requirements + challenge findings

  rect rgba(255, 200, 0, 0.15)
  Note over U,C: HUMAN APPROVAL GATE
  U-->>C: Approve requirements
  end

  C->>A: Assess architecture (WAF + Cost)
  Note right of A: cost-estimate-subagent<br/>handles pricing queries
  A-->>C: 02-architecture-assessment.md + 03-des-cost-estimate.md
  C->>X: Challenge architecture
  X-->>C: challenge-findings-architecture.json
  C->>X: Independently review cost feasibility
  X-->>C: challenge-findings-cost-estimate.json
  C->>U: Present architecture + challenge findings

  rect rgba(255, 200, 0, 0.15)
  Note over U,C: HUMAN APPROVAL GATE
  U-->>C: Approve architecture
  end

  C->>G: Discover policy constraints
  G-->>C: 04-governance-constraints.json and Markdown
  C->>X: Reconcile constraints with approved architecture
  X-->>C: challenge-findings-governance-constraints-pass1.json
  C->>U: Review governance constraints and confirmations
  U-->>C: Approve governance
  C->>IaC: Create implementation plan using approved inputs
  Note right of IaC: Unified IaC Planner (05)<br/>routes based on decisions.iac_tool
  IaC-->>C: 04-implementation-plan.md
  C->>X: Challenge implementation plan
  X-->>C: challenge-findings-plan.json
  C->>U: Present plan + challenge findings

  rect rgba(255, 200, 0, 0.15)
  Note over U,C: HUMAN APPROVAL GATE
  U-->>C: Approve plan
  end

  C->>Gen: Generate IaC templates (AVM-first)
  Note right of Gen: Bicep codegen or Terraform codegen
  Gen-->>C: infra/bicep/{project} or infra/terraform/{project}

  rect rgba(0, 150, 255, 0.08)
  Note over C,Gen: Validation loop
  alt Validation passes
    C->>U: Present templates for deployment
    rect rgba(255, 200, 0, 0.15)
    Note over U,C: HUMAN APPROVAL GATE
    U-->>C: Approve for deployment
    end
  else Validation fails
    C->>Gen: Revise with feedback
  end
  end

  C->>D: Execute deployment
  Note right of D: what-if or terraform plan preview first
  D-->>C: 06-deployment-summary.md
  C->>U: Present deployment summary

  rect rgba(255, 200, 0, 0.15)
  Note over U,D: HUMAN VERIFICATION
  U-->>C: Verify deployment
  end

  C->>W: Generate workload documentation
  Note right of W: Reads prior artifacts and deployed resource state
  W-->>C: 07-*.md documentation suite
  C->>U: Present as-built docs

  Note over U,W: AI orchestrated. Human governed. Azure ready.
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Start Here

For new projects, start from the Accelerator template rather than cloning this repository directly:

  1. Create a repository from the Accelerator template.
  2. Open that repository in VS Code and reopen it in the dev container.
  3. Follow the published documentation.

What This Repository Contains

  • Agent definitions, skills, and instruction files for the VS Code Copilot workflow engine
  • Reference implementations for Bicep and Terraform tracks
  • Validation scripts, MCP configuration, and sample agent outputs
  • apex-recall CLI for session state and recall across agent-output/ projects
  • Runtime references, artifact templates, and Architecture Explorer graph metadata

See AGENTS.md for contributor setup, conventions, and validation commands, and CHANGELOG.md for recent changes.

License

MIT. See LICENSE.

About

APEX turns Azure platform engineering requirements into verified, deploy-ready IaC — powered by GitHub Copilot agents, real-time pricing, and built-in compliance.

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