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Agentic Architecture - Container Migration Solution Accelerator

Based on your actual implementation, here's the comprehensive agentic architecture that mirrors the style of your reference image:

Architecture Overview

graph TB
    subgraph "Entry Layer"
        WEB[Web App/Queue]
        SERVICE[Migration Service]
    end

    subgraph "Process Engine"
        PROC[Process Orchestrator<br/>Semantic Kernel]
    end

    subgraph "Migration Steps"
        ANALYSIS[Analysis Step<br/>Platform Discovery]
        DESIGN[Design Step<br/>Azure Architecture]
        YAML[YAML Step<br/>Configuration Transform]
        DOCS[Documentation Step<br/>Report Generation]
    end

    subgraph "AI Agents (7 Specialists)"
        AGENTS[Multi-Agent System<br/>• Technical Architect<br/>• Azure Expert<br/>• EKS/GKE Experts<br/>• QA Engineer<br/>• Technical Writer<br/>• YAML Expert]
    end

    subgraph "Tool Layer"
        MCP[MCP Servers<br/>• Blob Storage<br/>• Microsoft Docs<br/>• DateTime Utils]
    end

    subgraph "Storage Layer"
        STORAGE[Azure Services<br/>• Blob Storage<br/>• Cosmos DB<br/>• OpenAI GPT o3]
    end

    %% Main Flow
    WEB --> SERVICE
    SERVICE --> PROC
    PROC --> ANALYSIS
    ANALYSIS --> DESIGN
    DESIGN --> YAML
    YAML --> DOCS

    %% AI Integration
    ANALYSIS -.-> AGENTS
    DESIGN -.-> AGENTS
    YAML -.-> AGENTS
    DOCS -.-> AGENTS

    %% Tool Access
    AGENTS -.-> MCP
    MCP -.-> STORAGE

    %% Styling for better readability
    classDef entryLayer fill:#e3f2fd,stroke:#1976d2,stroke-width:3px,color:#000
    classDef processLayer fill:#fff3e0,stroke:#f57c00,stroke-width:3px,color:#000
    classDef stepLayer fill:#f3e5f5,stroke:#7b1fa2,stroke-width:3px,color:#000
    classDef agentLayer fill:#e8f5e8,stroke:#388e3c,stroke-width:3px,color:#000
    classDef toolLayer fill:#fce4ec,stroke:#c2185b,stroke-width:3px,color:#000
    classDef storageLayer fill:#e1f5fe,stroke:#0288d1,stroke-width:3px,color:#000

    class WEB,SERVICE entryLayer
    class PROC processLayer
    class ANALYSIS,DESIGN,YAML,DOCS stepLayer
    class AGENTS agentLayer
    class MCP toolLayer
    class STORAGE storageLayer
Loading

Agent Specialization by Phase

Analysis Phase Agents

  • Technical Architect: Leads overall analysis strategy and coordination
  • EKS Expert: Identifies AWS EKS-specific patterns and configurations
  • GKE Expert: Identifies Google GKE-specific patterns and configurations

Design Phase Agents

  • Technical Architect: Defines migration architecture patterns
  • Azure Expert: Designs Azure service mappings and optimizations
  • EKS Expert: Provides source platform context for AWS workloads
  • GKE Expert: Provides source platform context for GCP workloads

YAML Conversion Phase Agents

  • YAML Expert: Performs configuration transformations and syntax optimization
  • Azure Expert: Ensures Azure service integration and compliance
  • QA Engineer: Validates converted configurations and tests
  • Technical Writer: Documents conversion decisions and generates reports

Documentation Phase Agents

  • Technical Architect: Provides architectural documentation and migration summary
  • Azure Expert: Documents Azure-specific configurations and optimizations
  • EKS/GKE Experts: Document source platform analysis and transformation logic
  • QA Engineer: Provides validation reports and testing documentation
  • Technical Writer: Creates comprehensive migration documentation

Data Flow Architecture

Input Processing

  1. Queue Service receives migration requests from web app or direct API
  2. Migration Service processes queue messages and initiates migration process
  3. Process Orchestrator manages step-by-step execution with event routing

Step Execution Pattern

Each step follows this pattern:

execution pattern

Storage Integration

  • Source Files: Read from Azure Blob Storage via MCP Blob Operations
  • Working Files: All processing files managed through Azure Blob Storage
  • Output Files: Generated configurations and reports saved to Azure Blob Storage
  • Telemetry: Agent interactions and process metrics stored in Azure Cosmos DB

MCP Server Integration

All agents have access to Model Context Protocol (MCP) servers via Semantic Kernel plugin:

  • Blob Operations: File reading/writing to Azure Blob Storage
  • Microsoft Docs: Azure documentation lookup and best practices
  • DateTime Utilities: Timestamp generation and time-based operations

Key Architectural Principles

Single Responsibility

Each step has a focused objective:

  • Analysis: Platform detection and file discovery
  • Design: Azure architecture and service mapping
  • YAML: Configuration transformation and validation
  • Documentation: Comprehensive report generation

Event-Driven Orchestration

Steps communicate through Semantic Kernel events:

  • StartMigration → Analysis Step
  • AnalysisCompleted → Design Step
  • DesignCompleted → YAML Step
  • YamlCompleted → Documentation Step

Multi-Agent Collaboration

Within each step, specialized agents collaborate through GroupChat orchestration:

  • Structured conversation patterns
  • Domain expertise contribution
  • Consensus building on decisions
  • Quality validation and review

Tool-Enabled Intelligence

Agents access external capabilities through MCP servers:

  • Cloud storage integration
  • Documentation lookup
  • Time-based operations

Observability & Monitoring

Comprehensive tracking throughout the process:

  • Agent interaction telemetry
  • Process execution metrics
  • Error handling and recovery
  • Performance optimization data

File Location Mapping

src/
├── main_service.py                    # Queue Service Entry Point
├── services/migration_service.py      # Migration Orchestration
├── libs/processes/
│   └── aks_migration_process.py       # Process Framework Definition
├── libs/steps/
│   ├── analysis_step.py               # Analysis Step Implementation
│   ├── design_step.py                 # Design Step Implementation
│   ├── yaml_step.py                   # YAML Step Implementation
│   └── documentation_step.py          # Documentation Step Implementation
├── libs/steps/orchestration/
│   ├── analysis_orchestration.py      # Analysis Agent Orchestration
│   ├── design_orchestration.py        # Design Agent Orchestration
│   ├── yaml_orchestration.py          # YAML Agent Orchestration
│   └── documentation_orchestration.py # Documentation Agent Orchestration
├── agents/
│   ├── technical_architect/agent_info.py
│   ├── azure_expert/agent_info.py
│   ├── eks_expert/agent_info.py
│   ├── gke_expert/agent_info.py
│   ├── qa_engineer/agent_info.py
│   ├── technical_writer/agent_info.py
│   └── yaml_expert/agent_info.py
└── plugins/mcp_server/
    ├── MCPBlobIOPlugin.py             # Azure Blob Storage MCP Server
    ├── MCPMicrosoftDocs.py            # Microsoft Docs MCP Server
    └── MCPDatetimePlugin.py           # DateTime Utilities MCP Server

Summary

This architecture implements a sophisticated agentic system that combines:

  • Semantic Kernel Process Framework for structured workflow execution
  • Multi-Agent GroupChat Orchestration for domain expertise collaboration
  • Model Context Protocol (MCP) for tool integration and external system access
  • Azure Cloud Services for scalable storage and data management
  • Event-Driven Architecture for loose coupling and reliability

The result is a robust, scalable, and extensible migration solution that leverages the collective intelligence of specialized AI agents working in concert to solve complex container migration challenges.