Wave Planning

Wave Planning groups your treated applications into sequenced migration waves. It integrates application sizing and the Cloud Accelerate Factory so each wave reflects real effort, dependencies and delivery resourcing. Complete 6R treatments first so the planner has accurate inputs.

The left sub-nav has three areas: Wave Plan, App Complexity and Wave Settings.

Why it matters: grouping applications into waves controls risk, balances resource constraints and manages dependencies. Smaller waves reduce downtime and let teams apply lessons learned to later waves.

The Wave Plan showing a Gantt-style view of migration waves and their applications across the planned date range.
The Wave Plan, with waves and their applications laid out across the planned date range.

Wave Plan

The Wave Plan is the working view of the schedule. Set the overall window with Edit Start Date, and read the headline metrics from the tiles (counts illustrative):

Tile What it shows
Waves Number of waves, across N applications.
Duration Total planned duration, in weeks.
Teams / Squads Number of parallel migration teams working the plan.

Two toggles control how the plan behaves: Auto Planning Enabled lets Dr Migrate group and sequence waves automatically, and Recalculate Wave Plan re-runs the planner against the latest data and settings.

The plan itself is a Gantt-style view of waves and their applications. Use Collapse All / Expand All to control detail, and Add Wave to create a new wave. Narrow the view with the filters: Wave, Select App, Complexity, Treatment and CAF Assigned. You can export the plan to XLS.

Move applications between waves by dragging them; any application you remove drops into Unassigned until you place it. Where a wave is CAF-assigned, the plan can surface the savings Microsoft covers, because the Cloud Accelerate Factory provides the resourcing for those workloads.

App Complexity

Application Sizing & Complexity Analysis classifies each application into a sizing band, which feeds the effort and duration of every wave. The AI evaluates workload scale, integrations, environments and migration-coordination signals to place each app in one of five bands:

Band Indicative effort
LowSmallest, simplest applications.
MediumModerate scale and integration.
HighLarger footprint or more dependencies.
Very HighSubstantial scale and coordination needs.
UnratedApplications or servers not yet classified, typically those not yet associated with an application workload. This is a catch-all category rather than a complexity tier.
The Application Sizing & Complexity Analysis screen with sizing rules, duration estimation and applications grouped by sizing band.
App Complexity: how each application is sized, and the signals that drive its band.

The screen also shows the inputs and outputs behind the bands:

  • Sizing Rules: the thresholds that define each band.
  • Duration Estimation: how a band translates into estimated migration effort and duration.
  • Largest Server Footprint: the applications with the heaviest infrastructure.
  • Most App-to-App Dependencies: the most interconnected applications.
  • Applications by Sizing Band: the spread of the estate across the five bands.

App Complexity replaces the old standalone Application Sizing page; sizing now lives directly inside Wave Planning, where it drives wave effort and duration.

Wave Settings

Wave Sizing controls how the planner builds waves. Set the three core limits to match your delivery capacity:

Setting Recommended What it controls
Applications per Wave 5–15 How many applications a single wave can contain.
Max Servers per Wave 50–200 The upper bound on servers in any one wave.
Parallel Migration Teams 1–5 How many teams (squads) run waves concurrently.

These settings determine whether waves run sequentially (one after another with a single team) or in parallel, where multiple teams work concurrent waves to shorten the overall timeline. More parallel teams compress the schedule but raise the resourcing required at any moment.

The Wave Settings screen showing applications per wave, servers per wave, parallel teams, planning preferences and the duration planning model.
Wave Settings: sizing limits, planning preferences and the duration planning model.

Planning Preferences

Two toggles shape how the plan is sequenced:

  • Prioritise Landing Zone Foundation: sequence the foundational work first, setting up identity, networking, security, monitoring and platform services before application waves begin.
  • Microsoft Cloud Accelerate Factory: optimise wave planning for CAF delivery, so CAF-aligned applications are grouped and sequenced to suit the factory.

Duration Planning Model

The Duration Planning Model sets the duration factors applied per complexity band, so wave durations reflect how much effort each band of application actually takes.

When you've adjusted settings, use Save settings to store them, or Save & Recalculate to apply them and rebuild the wave plan in one step.

Wave Grouping

Wave Grouping controls which attributes the planner weighs when deciding how to group and sequence applications into waves. Each attribute has an adjustable weight slider; higher weight means the planner favours keeping applications with the same value together. A running Total Weight indicator shows the sum across all attributes, and a Reset to Default action restores the original weighting. Attributes available:

  • App Criticality
  • App Function
  • App Owner
  • Business Unit
  • Complexity Rating
  • CPU Usage
  • Data Center
  • PII Data
  • Inherent Risk
  • Materiality
  • Memory Usage
  • Migration Strategy
  • Affinity Group (Recommended)

Advanced Settings

Two additional controls fine-tune the planner's behaviour:

  • Shared Services Sensitivity: a numeric input (0–100). Higher values make the planner more sensitive to shared services, keeping tightly coupled dependencies together. Default is 70.
  • Limit Strategy: a dropdown that determines how the planner handles waves that exceed the configured size limits. For example, Soft Limits allows network affinity groups larger than the limit to remain intact rather than being broken across waves.

Best practice: start with automatic planning to set a baseline, review the timeline and metrics against your business windows and resource constraints, adjust size limits and team counts incrementally with a recalculate after each change, then share the schedule with stakeholders and revisit as new data emerges.

Cloud Accelerate Factory (CAF)

The Cloud Accelerate Factory (previously the Microsoft Migration Factory, now integrated directly into wave planning) is a Microsoft programme that covers the resourcing for qualifying migrations. Dr Migrate auto-identifies candidate applications that meet Microsoft's criteria and folds them into the plan.

Candidate applications move through a series of states:

  • Auto-identified: Dr Migrate flags applications that meet the CAF criteria.
  • Nominated: you or the customer put applications forward for consideration.
  • CAF-aligned: confirmed for factory delivery.

CAF-aligned applications flow straight into wave planning, and their waves can show the savings Microsoft covers because the factory provides the migration resourcing. Filter the Wave Plan by CAF Assigned to see them in context.

On the roadmap: targeted CAF sessions (guided, scoped engagements to move CAF-aligned waves through the factory) are planned for a future release.

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