Skip to main content

Migration Planning with nOps Discovery

Overview​

Migration Planning is a sophisticated capability within nOps Discovery that transforms raw workload analysis into a comprehensive, actionable migration strategy. Going beyond traditional assessment tools, nOps provides a dynamic, AI-driven migration planning system that balances business requirements, technical constraints, and risk tolerance to create optimal migration waves and landing zone architectures.

Network Dependency Mapping​

Graph-Based Dependency Analysis​

nOps Discovery employs advanced graph theory to model your entire IT estate as an interconnected network:

  • Complete Topology Visualization: All workloads represented as nodes with connections as edges
  • Connection Frequency Analysis: Edge weights determined by communication frequency and volume
  • Protocol and Port Mapping: Detailed analysis of communication methods and security requirements
  • Latency Requirements: Identification of latency-sensitive connections between workloads

Identifying Network Patterns​

Our graph analysis identifies critical network patterns that inform migration strategy:

  • Hyper-Connectors: Services with an unusually high number of connections that represent critical infrastructure
  • Natural Separation Points: Logical boundaries where applications can be segmented with minimal disruption
  • Communication Clusters: Groups of services with heavy internal communication but limited external dependencies
  • Service Hierarchies: Parent-child relationships and dependency chains

Dependency Visualization​

Migration planners can interact with dependency maps through:

  • Dynamic Visualization: Interactive dependency graphs that can be filtered and explored
  • Hierarchy Views: Parent-child relationships between services
  • Heat Maps: Visual representation of connection frequency and criticality
  • Scenario Modeling: What-if analysis of separating different components

AI-Driven Risk Assessment​

Configurable Risk Tolerance​

nOps Discovery's AI engine allows organizations to define their risk tolerance on a sliding scale:

  • Conservative (20%): Prioritizes stability and minimal disruption over migration speed
  • Balanced (50%): Moderate approach balancing risk and migration velocity
  • Aggressive (80%): Accelerated migration accepting higher potential for minor disruptions

Risk Modeling Factors​

Our AI analyzes multiple dimensions to calculate migration risk:

  • Service Criticality: Importance of workloads to business operations
  • Dependency Complexity: Number and nature of inter-service dependencies
  • Historical Stability: Past performance and stability metrics of services
  • Data Consistency Requirements: Transactional and data integrity needs
  • User Impact Assessment: Potential impact on end-users during migration

Risk Mitigation Strategies​

Based on your risk tolerance settings, the system recommends specific risk mitigation approaches:

  • Extended Testing Periods: Longer testing cycles for critical workloads
  • Parallel Running: Maintaining source and target environments concurrently during transition
  • Rollback Plans: Detailed rollback procedures for each migration step
  • Cutover Windows: Optimal timing for service transitions based on usage patterns
  • Incremental Migration: Breaking complex workloads into smaller, safer migration components

Interactive Migration Planning​

nOps Discovery provides both conversational and form-based interfaces for migration planning, ensuring both flexibility and structure:

Conversational Interface​

The AI-powered conversational interface allows migration teams to:

  • Ask Natural Language Questions: "What are the highest risk components in wave 2?"
  • Provide Context: "Our payment processing system has a 99.99% uptime requirement"
  • Request Alternatives: "Show me a more conservative approach for the database tier"
  • Explain Reasoning: "Why was this application placed in wave 3?"
  • Simulate Scenarios: "What would happen if we moved the authentication service first?"

Form-Based Configuration​

Structured forms enable precise control over migration parameters:

  • Application Prioritization: Adjust the relative importance of different applications
  • Wave Construction Criteria: Define the criteria for grouping applications into waves
  • Testing Requirements: Specify testing depth for different application types
  • Timeline Constraints: Set time-based constraints on migration activities
  • Resource Allocation: Define available resources for migration activities

Key Customization Options​

The migration plan can be customized across several dimensions:

Modernization Aggressiveness​

  • Container Adoption Level: Adjust the threshold for recommending containerization

    • Conservative: Only COTS applications with official container support
    • Moderate: Well-suited custom applications and supported COTS
    • Aggressive: Most stateless applications with high confidence scores

  • Container Platform Preference:

    • EKS-First: Prefer Amazon EKS for most containerized applications
    • Fargate-First: Prefer AWS Fargate for simplified management
    • Balanced: Let nOps recommend the optimal platform for each workload

  • Serverless Adoption Level: Control criteria for recommending serverless architecture

    • Minimal: Consider only the most obvious serverless candidates
    • Balanced: Recommend serverless for suitable workloads with high confidence
    • Maximal: Aggressively identify serverless opportunities

Contextual Requirements​

  • Regulatory Compliance: Specify regulatory frameworks affecting workloads

    • PCI-DSS, HIPAA, GDPR, FedRAMP, etc.
    • Data residency requirements
    • Audit and logging requirements

  • Security Requirements: Define security controls for workloads

    • Encryption standards
    • Network isolation requirements
    • Authentication mechanisms

  • SLA/SLO Requirements: Specify performance and availability needs

    • Uptime requirements
    • Performance thresholds
    • Recovery time objectives (RTO)
    • Recovery point objectives (RPO)

Business Continuity Planning​

  • Disaster Recovery Tiers: Assign DR classifications to applications
    • Critical: Zero/near-zero downtime tolerance
    • Important: Brief downtime acceptable
    • Standard: Default recovery approach
  • Backup Strategy: Define backup requirements
    • Frequency and retention periods
    • Storage requirements
    • Testing procedures

Infrastructure Optimization​

  • Single Points of Failure: Identification and remediation strategies

    • Auto-detected SPOFs with remediation recommendations
    • Impact assessment of potential failures
    • Redundancy recommendations

  • Unused Services: Options for handling potentially dead services

    • Confirmation workflow for service decommissioning
    • Monitoring period before decommissioning
    • Archival requirements for data retention

Service Modernization​

  • Technology Replacement: Options for modernizing outdated components

    • Licensed to open-source alternatives
    • Legacy to cloud-native replacements
    • End-of-life software replacement recommendations

  • Architecture Evolution: Recommendations for architectural improvements

  • Microservice Conversion Approach:

    • Comprehensive: Full monolith decomposition with domain-driven design
    • Incremental: Strangler fig pattern with gradual extraction
    • Tactical: Extract only high-value components while preserving core monolith

Landing Zone Generation​

nOps Discovery's migration planning process culminates in the automatic generation of infrastructure-as-code for your AWS landing zone through our Infrastructure as Code Generation capability:

Data-Driven Infrastructure Design​

The landing zone code is generated based on actual workload data:

  • Telemetry-Based Sizing: Resources sized according to actual utilization metrics
  • Dependency-Aware Architecture: Infrastructure components arranged to support application dependencies
  • Right-Sized Security: Security controls tailored to observed traffic patterns
  • Cost-Optimized Resources: Resource selection based on utilization patterns and business requirements

Collaborative Infrastructure Development​

The generated code is designed for team collaboration:

  • Version Control Integration: Seamless integration with Git-based workflows
  • Evolutionary Design: Progressive refinement as more telemetry data is collected
  • Team Collaboration Features: Supports multi-team infrastructure development
  • Change Management: Detailed tracking and documentation of infrastructure evolution

For complete details on the Infrastructure as Code Generation capability, see the dedicated documentation.

Migration Wave Planning​

The culmination of all analysis is a comprehensive migration wave plan, powered by our Move Group Generation capability:

Intelligent Wave Construction​

  • Dependency-Aware Grouping: Applications organized based on:

    • Network dependency analysis using graph theory
    • Identification of hyper-connectors and natural separation points
    • Business criticality and operational constraints
    • Configurable risk tolerance settings (20%-80%)

  • Optimized Migration Sequence: Scientifically determined ordering

    • Minimized business disruption
    • Efficient resource utilization
    • Balance of technical and business priorities

For complete details on the advanced algorithms and visualization capabilities, see the Move Group Generation documentation.

Detailed Wave Documentation​

Each migration wave includes comprehensive documentation:

  • Preparation Checklist: Pre-migration requirements

    • Infrastructure readiness
    • Testing environment setup
    • Team training needs

  • Execution Plan: Step-by-step migration procedures

    • Component-level instructions
    • Automation opportunities
    • Manual intervention points

  • Testing Strategy: Comprehensive validation approach

    • Functional testing requirements
    • Performance validation
    • Integration testing
    • Business acceptance criteria

  • Rollback Procedures: Detailed contingency plans

    • Trigger conditions for rollback
    • Step-by-step rollback instructions
    • Recovery time estimates

How to Access Migration Planning​

  1. Complete the Workload Analysis process
  2. Navigate to "Discovery" → "Migration Planning" in your nOps dashboard
  3. Adjust your risk tolerance using the slider (20%-80%)
  4. Use the conversational or form interface to refine migration parameters
  5. Review the generated migration waves and landing zone design
  6. Export or commit the Terraform/OpenTofu code to your repository