Google Cloud Migration Center Tutorial: Architecture, Pricing, Use Cases, and Hands-On Guide for Migration

1. Introduction

Migration Center is Google Cloud’s service for discovering, assessing, planning, and tracking migrations to Google Cloud. It is designed to help you build a reliable inventory of your current environment (on‑premises or other clouds), understand what you have, decide what should move, and organize the work into a migration plan.

In simple terms: Migration Center is your “migration command center”—a place to collect infrastructure and application data and turn it into a migration plan with clear groupings and waves, so teams can execute migrations with fewer surprises.

Technically, Migration Center provides a central inventory model, ingestion mechanisms (collectors/import), asset normalization, and analysis/planning constructs to organize migrations. It integrates with other Google Cloud migration services (such as VM and database migration tools) but is not the tool that performs the actual data plane migration in most cases—it’s the place where you prepare and manage the migration journey.

The problem it solves: most migrations fail or slow down because teams don’t have a trustworthy inventory, don’t understand dependencies, don’t have a consistent way to prioritize, and can’t track progress across many teams and tools. Migration Center addresses this by creating a consistent migration dataset and a shared plan.

Service name check: This tutorial uses Migration Center as the exact primary service name in Google Cloud. If you notice naming differences in your console (due to UI updates), verify in official docs.

2. What is Migration Center?

Migration Center is a Google Cloud service whose official purpose is to help organizations discover assets, assess readiness, plan migrations, and track progress as they move workloads to Google Cloud.

Core capabilities (what it’s meant to do)

Discovery / inventory: Ingest asset data (VMs/servers and related metadata) from on‑prem or other clouds using supported methods (collectors and/or imports).
Normalization and central view: Provide a consistent inventory view so teams can work from a single dataset instead of multiple spreadsheets.
Assessment and planning: Organize assets into logical groups (for example, by application, environment, or business unit) and plan migration waves.
Tracking: Track migration progress of planned work items (capabilities vary; verify in official docs for your edition/feature set).

Major components (typical building blocks)

Migration Center commonly includes: – Migration Center UI in Google Cloud Console: The main place to view assets, groups, and plans. – Migration Center APIs (where available): Programmatic access for importing, updating, and managing inventory data (verify API name and availability in your project/region). – Data ingestion mechanisms: – Collectors (agentless and/or agent-based depending on source): Used to gather machine and environment details. – Imports (for example, CSV import templates) to bring inventory data from existing CMDBs or spreadsheets. – Planning constructs: – Asset groupings (for example, “applications” or “business services”) – Migration waves or phases (organize execution over time)

Service type and scope

Service type: Managed Google Cloud service (control-plane) for discovery/assessment/planning.
Scope: Typically project-scoped, with organization-level governance possible through IAM and resource hierarchy. Some resources may be “global” or “location-based” depending on the underlying API model (verify location behavior in official docs).
Data sensitivity: It holds metadata about your environment (hostnames, IPs, OS versions, CPU/memory sizing, sometimes installed software depending on ingestion method). Treat it as sensitive operational data.

How it fits into the Google Cloud ecosystem

Migration Center is commonly used alongside: – VM migration tools (for executing the move of VMs into Compute Engine)
– Database Migration Service (for migrating databases to managed services) – Storage Transfer Service / Transfer Appliance (for bulk data transfer) – Cloud Monitoring / Cloud Logging (post-migration operations) – Cloud Asset Inventory (for governance/inventory in Google Cloud—different purpose, but complementary)

Migration Center sits in the planning and governance layer of your migration program. You use it to decide what to move and when, then hand off execution to the appropriate migration tooling.

Official docs (start here): https://cloud.google.com/migration-center/docs

3. Why use Migration Center?

Business reasons

Faster time-to-plan: Reduces the time spent assembling inventories from spreadsheets and disparate tools.
Better prioritization: Helps identify high-value, low-risk migrations first to show progress and ROI.
Program visibility: Enables a migration office (or platform team) to see what’s migrating, when, and by whom.
Reduced migration risk: Fewer surprises from missing servers, unknown dependencies, or inaccurate sizing assumptions.

Technical reasons

Central inventory model: A consistent dataset of assets and attributes is foundational for any migration.
Assessment at scale: Helpful when you have dozens/hundreds/thousands of machines and need a scalable approach.
Standardized grouping and wave planning: Gives teams a repeatable method for organizing migration execution.

Operational reasons

Single pane of glass: A shared view for platform teams, app owners, and operations.
Repeatability: Encourages consistent processes across teams (discovery → grouping → waves → execution).
Better handoffs: Inventory and plan data can be used to coordinate with execution teams and change management.

Security/compliance reasons

Controlled access to sensitive inventory via IAM.
Auditability: Actions in Google Cloud can be audited using Cloud Audit Logs (depending on service integration; verify).
Data governance: Aligns with organization resource hierarchy, allowing centralized governance.

Scalability/performance reasons

Scales better than manual discovery when environments are large and frequently changing.
Helps identify candidates for modernization (for example, move from VM to container or managed service) based on inventory characteristics.

When teams should choose Migration Center

Choose Migration Center when: – You are planning or executing a structured migration program. – You need a trusted inventory of on‑prem/other-cloud assets. – You want a consistent place to define migration groups/waves and align stakeholders. – You need to integrate discovery/assessment with Google Cloud migration execution tools.

When teams should not choose it

Migration Center may not be the right first step when: – You are migrating a single small workload and can plan manually. – You need a full CMDB replacement (Migration Center is migration-focused, not a general ITSM/CMDB platform). – You need deep application performance monitoring (APM) or runtime tracing—use Cloud Operations suite or third-party APM. – You want a tool that directly performs every migration step end-to-end; Migration Center is primarily for discovery/assessment/planning, not a universal migration engine.

4. Where is Migration Center used?

Industries

Financial services (regulated, complex dependency landscapes)
Healthcare (compliance-heavy, legacy infrastructure)
Retail/e-commerce (seasonal capacity planning, multi-tier apps)
Manufacturing (plant systems, mixed OS, long-lived servers)
Media and entertainment (high storage/data movement needs)
SaaS companies modernizing from colo to cloud

Team types

Cloud Center of Excellence (CCoE)
Platform engineering teams
Migration factories / migration program offices
DevOps/SRE teams supporting workload transitions
Security and governance teams reviewing asset posture
App owners and technical product owners

Workloads and architectures

Traditional 3-tier enterprise apps (web/app/db)
Batch processing and scheduler-driven workloads
COTS applications on Windows and Linux VMs
Mixed environments with VMware vSphere on-prem plus AWS/Azure footprints
Large VM estates that need wave-based migration execution

Real-world deployment contexts

Pre-migration assessment: Inventory and grouping before any changes.
Parallel planning and execution: Continue discovering while early waves migrate.
M&A/portfolio rationalization: Consolidate inventories across acquired environments.

Production vs dev/test usage

Production usage: Most valuable in production migration programs; assets are real and the planning drives change windows and risk.
Dev/test usage: Useful for validating ingestion methods (collectors/imports), defining naming/grouping conventions, and rehearsing reporting before the main discovery phase.

5. Top Use Cases and Scenarios

Below are realistic scenarios where Migration Center is commonly used. Each includes the problem, why Migration Center fits, and a short example.

1) Build a single inventory for a multi-datacenter VM estate

Problem: Teams have separate spreadsheets per datacenter, inconsistent fields, and outdated host data.
Why Migration Center fits: Centralizes inventory ingestion and normalizes asset attributes.
Example: A bank consolidates 2,500 VMs from three vSphere clusters into one Migration Center project for planning.

2) Prioritize migrations by business service and environment

Problem: App owners don’t agree on what should migrate first; “lift-and-shift everything” is unrealistic.
Why it fits: Supports grouping assets into logical units and planning waves.
Example: An e-commerce company groups assets into “checkout,” “catalog,” and “analytics,” then schedules waves around peak season.

3) Create migration waves aligned to change windows

Problem: Operations needs migrations to occur in controlled maintenance windows.
Why it fits: Wave planning organizes execution into phases that map to change management.
Example: A manufacturer schedules Wave 1 for dev/test systems, Wave 2 for internal apps, Wave 3 for ERP.

4) Migrate from VMware to Compute Engine with consistent tracking

Problem: VM migrations are executed by one tool, but tracking is done elsewhere.
Why it fits: Migration Center can serve as the system of record for “what’s in scope” and progress.
Example: A university uses Migration Center inventory to define scope, then executes VM moves with a VM migration service.

5) Portfolio rationalization: retire, retain, or replace

Problem: Many servers exist “because they always have”; no owner, unknown purpose.
Why it fits: Centralized inventory enables stakeholder review and classification.
Example: A retailer identifies 15% of servers with no recent usage and flags them for retirement before migration.

6) Consolidate inventory across AWS, Azure, and on‑prem

Problem: A company operates in multiple clouds after acquisitions; there is no central view.
Why it fits: Migration Center is designed to unify discovery inputs for migration planning to Google Cloud.
Example: A SaaS company ingests inventories from AWS and on‑prem, then chooses what moves into Google Cloud.

7) Create a migration factory workflow

Problem: Hundreds of apps must migrate with repeatable steps and governance gates.
Why it fits: Provides shared datasets and planning constructs (groups/waves) that can integrate with a migration factory process.
Example: A consulting team uses Migration Center as the “intake” step for every app.

8) Validate sizing before moving to Compute Engine

Problem: Teams routinely overprovision in the cloud due to poor on‑prem sizing info.
Why it fits: Inventory data can support rightsizing decisions and reduce cost (exact assessment features depend on configuration; verify).
Example: An insurance company identifies many 16-vCPU VMs running at low utilization and plans smaller machine types.

9) Plan modernization candidates (VM → containers / managed services)

Problem: Not all workloads should stay as VMs; modernization opportunities are missed.
Why it fits: A central inventory helps identify patterns (OS, middleware, dependencies) to pick modernization paths.
Example: A fintech finds stateless API tiers and targets them for containerization while migrating stateful workloads as VMs first.

10) Compliance-driven migration reporting

Problem: Auditors require evidence of scope, timing, approvals, and controls for migrations.
Why it fits: Central planning/tracking helps produce consistent reporting (capabilities vary; verify).
Example: A healthcare provider exports inventory and wave plans to support change control documentation.

11) Disaster recovery and business continuity planning during migration

Problem: Migration execution can temporarily weaken DR coverage if not planned carefully.
Why it fits: Inventory and grouping help you map replication/backup requirements by tier.
Example: A media company groups apps by RPO/RTO and plans pre-migration backup and post-migration DR.

12) Establish a baseline inventory before implementing governance

Problem: Governance policies (labels, IAM, OS patching requirements) can’t be applied without knowing what exists.
Why it fits: Creates an inventory baseline that feeds governance workstreams.
Example: A global enterprise uses Migration Center data to define naming and tagging standards before wave execution.

6. Core Features

Migration Center’s exact feature set can evolve. The features below reflect the common, current capabilities described in Google Cloud documentation and typical Migration Center workflows. Where a feature depends on your configuration, ingestion method, or product updates, it is clearly noted.

1) Centralized asset inventory (single dataset)

What it does: Stores discovered/imported assets (typically servers/VMs) and related metadata.
Why it matters: A migration plan is only as good as the inventory behind it.
Practical benefit: Eliminates “spreadsheet drift” and inconsistent fields between teams.
Caveats: Inventory quality depends on discovery/import completeness and freshness.

2) Multiple ingestion paths (collectors and imports)

What it does: Enables you to bring in data from different environments and sources.
Why it matters: Enterprises rarely have a single source of truth.
Practical benefit: You can start quickly with imports (CSV) and later mature into automated discovery.
Caveats: Collector capabilities and supported sources can vary—verify supported sources/versions in official docs.

3) Asset normalization and consistent attributes

What it does: Maps incoming data to a consistent schema (host identifiers, CPU/memory, OS, etc.).
Why it matters: Consistency is required for filtering, grouping, and reporting.
Practical benefit: Enables organization-wide planning standards.
Caveats: If your source data is incomplete, normalization won’t “fix” missing values.

4) Grouping assets by application or business service

What it does: Lets you group assets into logical units (for example, “SAP ECC,” “CRM,” “Payments API”).
Why it matters: Migrations succeed at the application boundary, not the server boundary.
Practical benefit: App owners can validate scope and dependencies per group.
Caveats: Grouping is a human process; automate where possible but validate with owners.

5) Migration waves / phased planning

What it does: Organizes execution into waves/phases to control risk and align with change windows.
Why it matters: Large migrations need sequencing to avoid business disruption.
Practical benefit: Supports migration factory patterns and repeatable delivery.
Caveats: “Wave plans” are only useful if they stay updated; define ownership.

6) Filtering, search, and inventory exploration

What it does: Enables teams to search assets and filter by key attributes.
Why it matters: You need to quickly answer questions like “which servers run Windows Server 2012?” or “which assets belong to app X?”
Practical benefit: Faster scoping and risk identification.
Caveats: Requires good tagging/metadata completeness.

7) Integrations with migration execution services (conceptual and/or direct)

What it does: Helps connect planning to execution tools (for example, VM/database migration services).
Why it matters: Planning without execution coordination often breaks down.
Practical benefit: Reduces handoff friction across teams.
Caveats: The depth of integration varies—verify which tools integrate directly vs via process/manual mapping.

8) Reporting/export (where supported)

What it does: Enables reporting and/or exporting inventory data for stakeholders.
Why it matters: Most migration programs need reporting for leadership, finance, and audit.
Practical benefit: Supports consistent dashboards and status reviews.
Caveats: Export destinations and formats depend on product features—verify current export options.

9) Role-based access control via IAM

What it does: Controls who can view, edit, import, and administer migration inventory.
Why it matters: Inventory data can expose sensitive infrastructure details.
Practical benefit: Least-privilege access for app owners vs migration admins.
Caveats: Role names and granularity can change; validate role definitions in IAM docs.

10) Auditability via Google Cloud logging (where integrated)

What it does: Supports auditing of actions and changes through Google Cloud’s audit logging mechanisms.
Why it matters: Governance and compliance require traceability.
Practical benefit: Helps incident response and compliance evidence.
Caveats: Audit coverage depends on service integration; verify audit log entries for your use cases.

7. Architecture and How It Works

High-level architecture

Migration Center is a control-plane service. It receives inventory data (from collectors or imports), stores it in a managed backend, and presents it via the Cloud Console (and optionally APIs). The discovery process usually runs outside Google Cloud (for on‑prem or other clouds) and sends metadata to Google Cloud.

Request/data/control flow (typical)

Discovery collection happens in the source environment: – Collector gathers asset metadata (hostnames, CPU/memory, OS, etc.).
Collector or import process sends data to Migration Center in your Google Cloud project.
Migration Center stores inventory and makes it available for: – filtering/search – grouping – wave planning – reporting/export (where supported)
Migration teams use the plan to execute migrations with dedicated migration tools (VM/database/data transfer).
Tracking is updated during execution (manually or via integrations, depending on setup).

Integrations with related services (common in real projects)

Compute Engine: target landing zone for VM-based migrations.
VPC / Cloud VPN / Cloud Interconnect: connectivity to sources during discovery and migration.
Cloud IAM: access control.
Cloud Logging / Cloud Audit Logs: governance and investigation.
Migration execution services:
VM migration tooling for moving VM workloads to Compute Engine
Database Migration Service for database moves
Storage Transfer Service / Transfer Appliance for data movement

Important boundary: Migration Center primarily helps you plan and coordinate. For data-plane movement, use the appropriate migration service.

Dependency services

At minimum: – A Google Cloud project with billing enabled – IAM permissions – Network egress from collector environment to Google Cloud endpoints (if using collectors) – Storage/compute in your source environment to run collectors (costs are external to Google Cloud)

Security/authentication model

Users authenticate with Google identities (Cloud IAM).
Collectors/import tools typically authenticate using a Google identity (user credentials) or a service account depending on the ingestion method (verify ingestion authentication options).
Use least-privilege IAM roles and isolate projects by environment (dev vs prod).

Networking model

Migration Center is accessed over the public Google APIs endpoints.
If using collectors:
Outbound HTTPS from your environment to Google APIs is typically required.
Ensure proxy/firewall rules allow required endpoints.
Consider Private Google Access or private connectivity patterns where applicable (implementation depends on collector and environment; verify).

Monitoring/logging/governance considerations

Use Cloud Audit Logs to monitor administrative actions (create imports, modify assets, etc.).
Consider exporting logs to SIEM via Log sinks.
Use organization policies to restrict who can create projects, service accounts, or external IPs in migration landing zones.
Establish naming/tagging conventions early so inventory aligns to your governance model.

Simple architecture diagram (Mermaid)

flowchart LR
  A[On-prem / Other cloud assets] --> B[Collector or CSV import]
  B -->|HTTPS to Google APIs| C[Migration Center (Google Cloud)]
  C --> D[Inventory view in Cloud Console]
  D --> E[Groups & migration waves]
  E --> F[Execution tools (VM/DB/Data migration)]

Production-style architecture diagram (Mermaid)

flowchart TB
  subgraph Source["Source environments"]
    V[vSphere / Physical / Other cloud VMs]
    CMDB[CMDB / Spreadsheets]
    COL[Discovery collector(s)]
  end

  subgraph GCP["Google Cloud Project: migration-assessment-prod"]
    MC[Migration Center]
    IAM[IAM / Org Policies]
    LOG[Cloud Logging & Audit Logs]
    NET[VPC / VPN / Interconnect (for execution)]
    EXEC[Migration execution services\n(VM migration, DMS, data transfer)]
    OPS[Cloud Monitoring (post-migration)]
  end

  V --> COL
  CMDB -->|CSV import| MC
  COL -->|Authenticated HTTPS| MC

  IAM --> MC
  MC --> LOG
  MC --> EXEC
  NET --> EXEC
  EXEC --> OPS

8. Prerequisites

Account/project requirements

A Google Cloud account with access to the Cloud Console
A Google Cloud project dedicated to migration assessment/planning (recommended)
Billing enabled on the project (even if the core service has no direct SKU, dependent services/logging may incur costs)

Permissions / IAM roles

For a learning lab, the simplest is: – Project Owner on the project

For production, use least privilege: – Migration program admins: permissions to configure Migration Center, manage imports/collectors, and manage assets/groups/waves – App owners: read-only access to relevant inventory and planning views – Security/audit: read-only access to logs and configuration

Role names can vary by product evolution. In IAM, search for roles related to “Migration Center”. Verify exact predefined roles and permissions in official docs.

Tools

Web browser for Google Cloud Console
Optional:
gcloud CLI for project setup and enabling APIs (if applicable)
A text editor for preparing CSV inventory imports

Install gcloud: https://cloud.google.com/sdk/docs/install

Region availability

Migration Center availability can depend on location and rollout stage.
– Verify availability in your regions using official docs and your Cloud Console.

Quotas/limits

Potential limits include: – Number of assets per project – Import job size and frequency – API request quotas (if using programmatic imports)

These limits can change—verify quotas in the product documentation and in the Quotas page for your project.

Prerequisite services (common)

IAM enabled (default)
Cloud Logging/Audit Logs (default at the org/project level)
If using collectors: network egress to Google APIs and any required endpoints

9. Pricing / Cost

Migration Center pricing can be nuanced because: – Some Google Cloud planning/control-plane services do not have a prominent standalone SKU. – The largest costs often come from the migration execution (compute, storage, networking) and from running collectors (outside GCP) or storing exports in GCP services.

Pricing dimensions (what can cost money)

You should evaluate costs across:

Migration Center service charges – Check the official pricing page for Migration Center or related migration offerings. – If no explicit SKU is listed, that does not mean “zero cost overall”—it may mean the service is included at no additional charge, while dependent services cost money. – Verify current pricing in official sources.
Inventory ingestion costs – Collector runtime: If you run collectors on a VM (on-prem or cloud), you pay for that environment (not Google Cloud unless you run collectors on Google Cloud compute). – Network egress: Sending inventory metadata to Google Cloud usually involves minimal data, but enterprise environments with frequent updates may increase traffic (still typically small compared to data migrations). – API calls: If the ingestion uses APIs with billable requests (uncommon for basic Google APIs, but depends), verify.
Storage and analytics costs (indirect) – If you export inventory to: – Cloud Storage (storage + operations) – BigQuery (storage + query processing) – Logging sinks (log volume) Then those services have their own pricing.
Migration execution costs (often the dominant costs) – Compute Engine instances – Persistent Disks – Snapshots and backups – Network egress/ingress (especially cross-region or to internet) – Database services (Cloud SQL, AlloyDB, etc.) – Interconnect/VPN charges

Free tier

Migration Center itself may not have a “free tier” in the classic sense; instead it may be included without explicit per-unit cost. Treat this as “verify”:
– Verify in official docs/pricing: https://cloud.google.com/products/calculator and the Migration Center docs/pricing references.

Key cost drivers

Size of the migration (number of assets and how often you refresh discovery)
How you store and analyze exports (BigQuery query patterns can become a major cost)
Migration execution architecture (rehosting vs replatforming vs refactoring)
Network design (cross-region traffic, hybrid connectivity, data transfer)

Hidden or indirect costs to watch

Overprovisioning in the target cloud due to poor sizing decisions
Extended dual-run periods where you pay for on-prem and cloud simultaneously
Logging and monitoring volume post-migration
Third-party licenses (OS, databases, monitoring agents)
IP address management and DNS changes (operational costs, not direct cloud bills)

Network/data transfer implications

Inventory metadata transfer is usually modest.
The migration itself (VM images, databases, object data) is where data transfer costs matter:
On-prem to Google Cloud ingress is often free, but verify current policy and any partner charges.
Egress from other clouds (AWS/Azure) can be expensive and is charged by the source cloud.

How to optimize cost

Start with imports (CSV) for quick planning without running heavy collectors everywhere.
Refresh discovery selectively (critical apps first).
Use right-sizing practices before migrating (avoid “lift-and-over-shift”).
Minimize long dual-run windows.
Use budgets and alerts in Google Cloud Billing from day one.

Example low-cost starter estimate (no fabricated prices)

A low-cost starter lab typically includes: – A single Google Cloud project with Migration Center enabled – A small CSV inventory import – No data-plane migration – Minimal or no additional services

Expected costs: – Potentially near zero for the Migration Center planning activity itself (if no SKU applies) – Small or zero costs for logging/audit (depends on org configuration) – Your time is the main cost

Verify any direct charges by checking: – Google Cloud Pricing Calculator: https://cloud.google.com/products/calculator – Billing reports after running the lab

Example production cost considerations

A realistic production program cost profile includes: – Hybrid connectivity (VPN/Interconnect) – Target landing zone (shared VPC, firewalls, NAT) – Compute/storage for migrated workloads – Backup/DR tooling – Security services (Security Command Center, KMS, etc.) – Migration tooling and potential third-party licenses – Ongoing operations (Monitoring, Logging, incident response)

10. Step-by-Step Hands-On Tutorial

This lab is designed to be safe and low-cost, focusing on using Migration Center to build an inventory and plan a simple migration wave using a CSV import. It avoids running collectors (which may require additional infrastructure and permissions).

Objective

Create a Migration Center inventory using a CSV import, then organize assets into a group and a migration wave so you have a simple, repeatable workflow for migration planning.

Lab Overview

You will: 1. Create/select a Google Cloud project and open Migration Center 2. Prepare a small inventory file using the official CSV template from Migration Center 3. Import assets into Migration Center 4. Create a group (representing an application) 5. Create a wave (representing a migration phase) 6. Validate the inventory and plan 7. Clean up imported resources (where applicable)

Note: The Migration Center UI can change. Follow the intent of each step and verify exact button names in your console.

Step 1: Create or select a Google Cloud project

Goal: Have a dedicated project for migration assessment.

Open the Google Cloud Console: https://console.cloud.google.com/
In the top project selector, either: – Select an existing project, or – Click New Project, and create one (example: migration-center-lab)

Expected outcome – A project exists and is selected in the Console.

Optional (CLI) If you prefer CLI project creation:

# Set variables
export PROJECT_ID="migration-center-lab-$(date +%Y%m%d)"
export BILLING_ACCOUNT_ID="YOUR_BILLING_ACCOUNT_ID"

# Create project
gcloud projects create "$PROJECT_ID" --name="migration-center-lab"

# Link billing (requires permission on billing account)
gcloud billing projects link "$PROJECT_ID" --billing-account="$BILLING_ACCOUNT_ID"

# Set default project
gcloud config set project "$PROJECT_ID"

If you cannot link billing from CLI, link it in the Console: Billing → Link a billing account.

Step 2: Open Migration Center and confirm access

Goal: Confirm you can access Migration Center in your project.

In the Console, use the search bar and search for Migration Center.
Open Migration Center.
If prompted, accept any initial setup prompts.

Expected outcome – You can see the Migration Center landing page (inventory/overview area).

Verification – You can navigate to sections related to assets/inventory and imports (names vary).

Common issue – If you see “API not enabled” or permission errors: – Ensure you are in the correct project. – Ensure you have sufficient permissions (Project Owner is enough for this lab). – If prompted, enable the required API(s). If you want to pre-enable APIs, verify the exact API name in official docs or the enable prompt.

Step 3: Download the official CSV import template

Goal: Use the exact CSV schema expected by Migration Center.

In Migration Center, find the workflow for adding data. Look for something like: – Add data, Import, Upload file, or Import inventory
Choose CSV import (or “File import”).
Download the CSV template provided by Migration Center.

Expected outcome – You have a CSV template file on your machine.

Why this step matters – CSV schemas are strict. Using the official template prevents errors due to missing/incorrect column names.

Step 4: Populate the CSV with two sample assets

Goal: Create a tiny “on‑prem inventory” dataset.

Open the downloaded CSV template in a spreadsheet editor or text editor.
Add two assets that represent typical servers, for example: – payapp-web-01 (Linux, web tier) – payapp-db-01 (Linux or Windows, database tier)

Guidance – Fill only the required columns and any sizing fields (CPU, memory, disk) the template includes. – Use realistic but small values. – Avoid sensitive real hostnames or IPs for a public lab.

Example (illustrative only) Your template columns may not match this example. Do not copy this blindly—use the template’s real columns.

asset_name,hostname,os,cpu_count,memory_mb,source
payapp-web-01,payapp-web-01,linux,2,4096,onprem-lab
payapp-db-01,payapp-db-01,linux,4,8192,onprem-lab

Save the file as something like migration-center-inventory.csv.

Expected outcome – A valid CSV file matching the Migration Center template schema.

Step 5: Create a source (if required) and run the import

Goal: Import your CSV into Migration Center.

Return to Migration Center → Import/Upload section.
If Migration Center asks you to define a Source (a logical origin like “On-prem DC1”), create one: – Name: onprem-lab – Type: on‑prem (or generic)
Create an Import job (wording varies), then upload your CSV file.
Start the import.

Expected outcome – Import job completes successfully (status like “Completed”). – Assets appear in the inventory list.

Verification – Go to the Assets/Inventory view. – Confirm your two assets are listed. – Open an asset and confirm key fields (name, OS, CPU, memory) are visible.

Common errors and fixes – Invalid CSV schema: Re-download the template and ensure you didn’t rename columns. – Wrong delimiter/encoding: Use UTF-8, comma delimiter, and quote fields with commas. – Permission denied: Use a role with admin/edit permissions for the project or Migration Center-specific permissions.

Step 6: Create an “Application Group” for the assets

Goal: Represent a workload boundary (application) rather than individual servers.

In Migration Center, navigate to a section like Groups, Applications, or Organize assets.
Create a new group: – Name: payapp – Description: “Payment application (lab)”
Add both assets (payapp-web-01, payapp-db-01) to the group.

Expected outcome – A group exists with 2 assets.

Verification – Open the group view and confirm asset membership. – Check that you can filter assets by group.

Step 7: Create a migration wave (phase plan)

Goal: Define a simple phased approach.

Navigate to Waves, Phases, or Migration plan (label varies).
Create a wave: – Name: wave-01-lab – Scope: group payapp – Target: “Google Cloud” (or your target landing zone notes) – Planned date: pick a date/time window (even if just illustrative)
Save the wave.

Expected outcome – A wave exists that includes the payapp group (2 assets).

Verification – Open the wave and confirm assets/groups are attached. – Confirm you can update wave metadata (owner, status, notes—depending on UI).

Validation

Use this checklist:

[ ] Migration Center opens in the correct project
[ ] Import job shows “Completed” (or similar success status)
[ ] Inventory shows exactly 2 imported assets
[ ] Group payapp includes both assets
[ ] Wave wave-01-lab includes the group/assets

If all checks pass, you’ve completed a realistic “inventory → grouping → wave planning” workflow.

Troubleshooting

Issue: “Migration Center is not available” or cannot be found in console

Verify your project billing is enabled.
Verify your account permissions.
Verify product availability in your region/org (some services have rollout constraints).
Check the official docs: https://cloud.google.com/migration-center/docs

Issue: Import fails with schema/validation errors

Use the official template downloaded from the UI.
Confirm required columns are populated.
Avoid special characters and ensure consistent datatypes (numbers in numeric columns).

Issue: Assets import but fields are blank

Your CSV may not include optional sizing fields.
Confirm you populated the right columns from the template.
If you need richer data, consider a supported collector method (requires more setup; verify).

Issue: Permission denied when importing

For lab simplicity, use Project Owner.
In production, assign Migration Center-specific roles to a service account or group; verify role names in IAM.

Cleanup

To avoid leaving test data:

In Migration Center, delete the lab wave (wave-01-lab) if supported.
Delete the group (payapp) if supported.
Delete imported assets or the import job/source if the UI supports deletion.
Optionally delete the entire project (most reliable cleanup):

gcloud projects delete "$PROJECT_ID"

Project deletion is irreversible and removes all resources in that project. Use only for labs.

11. Best Practices

Architecture best practices

Start with an inventory baseline: Define a “data cutoff date” and refresh cadence (weekly/biweekly) for discovery updates.
Model around applications: Group assets into application boundaries with owners, SLAs, and change windows.
Use waves to control risk: Start with low-risk internal apps, then expand.
Treat planning as iterative: Inventory and wave plans evolve as you learn dependencies.

IAM/security best practices

Least privilege: Give app owners read-only access; restrict imports/edits to migration admins.
Use groups, not individuals for permissions (Google Groups / Cloud Identity).
Separate environments: Use separate projects for dev/test planning vs production planning if governance requires it.
Protect exports: If you export inventory to storage/analytics, apply strict IAM and retention.

Cost best practices

Avoid over-collecting early: Start with top apps; expand discovery later.
Minimize dual-run time: Use wave planning to shorten overlap where you pay for both on-prem and cloud.
Right-size before migrating: Use inventory to identify oversizing patterns and reduce target compute costs.
Budget early: Set Cloud Billing budgets/alerts for migration landing zones and shared services.

Performance best practices

Prefer reliable ingestion: Automated discovery/collector approaches (when validated) reduce manual errors.
Use consistent identifiers: Standardize naming/IDs to prevent duplicates during imports.
Validate data quality: Spot-check assets per business unit to ensure discovery is accurate.

Reliability best practices

Assign ownership: Each group/application should have a named owner responsible for validation.
Change management alignment: Ensure wave schedules match actual maintenance windows and dependency sequencing.
Document assumptions: What fields are missing? What dependencies are unknown? Make risk explicit.

Operations best practices

Establish an operating rhythm: weekly inventory refresh, biweekly wave review, monthly executive reporting.
Log/audit review: Confirm audit logs meet your compliance needs (and retain them appropriately).
Integrate with ticketing: Even if Migration Center doesn’t integrate directly, maintain references (wave ID ↔ change tickets).

Governance/tagging/naming best practices

Use naming standards for:
sources (onprem-dc1, aws-prod, azure-eu)
groups (app-payments-prod, app-crm-dev)
waves (wave-01-dev, wave-02-internal, wave-03-prod)
Keep a consistent taxonomy:
Business unit
Environment (dev/test/prod)
Data classification (public/internal/confidential)
Owner/team

12. Security Considerations

Identity and access model

Migration Center access is governed by Cloud IAM.
Use:
Admin roles only for migration program administrators
Viewer roles for app owners and auditors
Prefer group-based IAM bindings and avoid assigning broad permissions to individuals.

Encryption

Data stored in Google Cloud is encrypted at rest by default.
Data in transit to Google APIs is protected by TLS.
If you export data to other services (Cloud Storage, BigQuery), ensure those are configured securely and consider CMEK if required.
For compliance-specific encryption requirements, verify Migration Center CMEK support (if needed) in official docs.

Network exposure

Treat inventory data as sensitive. It can include hostnames, IP addresses, OS versions, and sizing.
If using collectors, ensure:
Outbound connectivity is restricted to required endpoints
Proxies and firewall rules are locked down
Collector hosts are hardened and patched

Secrets handling

If collectors require credentials to connect to virtualization platforms or servers:
Store secrets in a secure vault (e.g., Secret Manager or enterprise vault) where supported by your process.
Do not embed credentials in scripts or spreadsheets.
Rotate credentials after discovery phases.

Audit/logging

Use Cloud Audit Logs to track admin actions.
Export logs to a centralized logging/SIEM platform as required.
Define retention based on compliance needs.

Compliance considerations

Inventory data may be considered sensitive operational data.
Ensure your use complies with internal policies:
data residency requirements (verify where Migration Center stores/operates)
access control and separation of duties
retention and deletion policies

Common security mistakes

Using broad Owner access for all engineers long-term
Uploading real production inventories into a shared sandbox project
Exporting inventory to unsecured storage buckets
Leaving discovery collectors running with excessive permissions after discovery

Secure deployment recommendations

Use a dedicated, secured project for migration planning.
Apply Org Policies where possible (restrict service account key creation, restrict external IP usage, etc.).
Implement least-privilege IAM and periodic access reviews.
Document and approve ingestion methods and credential handling.

13. Limitations and Gotchas

Because Migration Center evolves, treat these as common limitations to evaluate and verify for your environment.

Known limitations (typical)

Not a migration execution engine: You still need the appropriate migration services to move workloads and data.
Discovery depth depends on ingestion method: CSV imports can be shallow; collectors can be richer.
Data freshness: If you don’t refresh discovery regularly, inventory becomes stale.

Quotas and scale considerations

Limits on:
number of assets
import size
number of sources/import jobs
API quotas (if using programmatic ingestion)
Verify quotas in Google Cloud Console Quotas and product docs.

Regional constraints

Some Google Cloud services have limited regional support or are “global” in control-plane behavior.
Verify:
where the service is available
how location affects compliance requirements

Pricing surprises

Migration Center planning itself may not be your cost driver; the surprises often come from:
BigQuery exports and heavy querying
long dual-run periods
cross-region networking
source-cloud egress fees (AWS/Azure)

Compatibility issues

Collector support for certain hypervisor versions or OS types may vary.
Older OS versions can pose migration challenges (drivers, boot modes, licensing).
Application dependencies are often not fully captured by basic inventory; you may need additional tooling/process.

Operational gotchas

Duplicate assets from repeated imports with inconsistent IDs
Naming drift (same server appears under multiple hostnames)
Lack of ownership: groups created without accountable owners become stale quickly
Teams treat wave plans as “set and forget,” leading to inaccurate execution tracking

Vendor-specific nuances

AWS/Azure egress and migration tooling differences can affect your planning and cost.
VMware environments often require careful network/IP/DNS planning when rehosting.

14. Comparison with Alternatives

Migration Center is in the “migration planning and tracking” category. Below is a practical comparison.

Option	Best For	Strengths	Weaknesses	When to Choose
Google Cloud Migration Center	Planning migrations to Google Cloud with a central inventory	Native to Google Cloud ecosystem; central inventory; grouping/waves; integrates with Google Cloud migration services	Not a full CMDB; execution depends on other tools; feature depth depends on ingestion	You need a Google Cloud-aligned migration planning hub
Google Cloud VM migration tools (execution services)	Moving VMs into Compute Engine	Performs data-plane migration; supports cutover workflows	Doesn’t replace discovery/planning; may not provide portfolio-wide inventory	When you already know what to migrate and need execution tooling
Google Cloud Database Migration Service (DMS)	Migrating supported databases to Google Cloud	Managed migration workflows; replication/cutover	Focused on databases only	When database migration is the primary workstream
AWS Migration Hub	Planning/tracking migrations to AWS	AWS-native tracking; integrates with AWS discovery tools	Cloud-specific; not for Google Cloud targets	Choose when target is AWS and you want AWS-native tracking
Azure Migrate	Discovery/assessment and migration to Azure	Strong Azure-native assessment and tooling	Cloud-specific; not for Google Cloud targets	Choose when target is Azure
ServiceNow CMDB + custom migration process	Organizations with mature ITSM/CMDB	Enterprise workflow, approvals, ownership	Requires customization; not migration-specific; can be slow to implement	If CMDB is the authoritative inventory and you need strict ITSM governance
Open-source discovery + spreadsheets	Very small environments or constrained budgets	Low direct cost; flexible	Low accuracy, hard to maintain, poor governance	Only for small one-off migrations with minimal complexity

15. Real-World Example

Enterprise example: global manufacturer migrating VMware estates

Problem A global manufacturer has ~4,000 VMs across multiple datacenters, inconsistent inventories per region, and limited visibility into which apps are critical. They need to migrate to Google Cloud over 18 months with strict change windows and audit requirements.

Proposed architecture – Migration Center in a dedicated Google Cloud project for assessment and planning – Discovery via supported collectors for core datacenters, plus CSV imports from the CMDB for edge sites – Asset grouping by business service (ERP, MES, analytics, intranet) – Waves aligned to quarterly release trains and plant maintenance windows – Execution: – VM migrations to Compute Engine for rehost candidates – Database Migration Service for supported databases – Storage Transfer Service/Transfer Appliance for large datasets where needed – Governance: – IAM least privilege (admins vs app owners vs auditors) – Audit logs exported to a SIEM – Standardized naming and labeling

Why Migration Center was chosen – They need a Google Cloud-native “system of record” for migration scope and sequencing. – They need consistent grouping and wave planning across regions. – They want a shared inventory dataset across infrastructure and application teams.

Expected outcomes – A single, auditable inventory for migration scope – Reduced rework from incomplete discovery – More predictable wave execution and fewer change-window failures – Better cost control through improved sizing discipline

Startup/small-team example: SaaS company moving from colo to Google Cloud

Problem A startup runs 60 VMs in a colocation facility and wants to move to Google Cloud quickly, but doesn’t have a strong inventory. The team is small and needs an organized approach without heavy tooling overhead.

Proposed architecture – Migration Center used with a simple CSV import to bootstrap an inventory – Group assets by product components (API, workers, database, monitoring) – Define 3 waves: 1. Non-production and tooling 2. Stateless services 3. Stateful services and databases – Execution: – VM rehosting for initial move – Later modernization to managed databases and containers

Why Migration Center was chosen – Lightweight way to create a shared inventory and migration plan without building internal tooling. – Fits naturally into Google Cloud as they adopt more managed services.

Expected outcomes – Faster planning with fewer missed servers – Clear sequencing and ownership, despite a small team – Reduced downtime risk by migrating in controlled waves

16. FAQ

1) Is Migration Center the tool that migrates my VMs?

Migration Center is primarily for discovery, assessment, planning, and tracking. VM data-plane migration is typically handled by dedicated VM migration tools. Use Migration Center to decide what to migrate and when.

2) What kind of data does Migration Center store?

Typically inventory metadata: hostnames, OS, CPU/memory sizing, and other attributes depending on ingestion method. Treat it as sensitive operational data.

3) Can I start with spreadsheets?

Yes. A common path is to use a CSV import to bootstrap inventory, then adopt collectors later for richer and fresher data.

4) Does Migration Center replace our CMDB?

Generally no. Migration Center is migration-focused. Many enterprises keep CMDB as the system of record and use Migration Center for migration planning.

5) Can multiple teams use the same Migration Center project?

Yes, but manage access carefully with IAM and define ownership conventions. In large orgs, a dedicated planning project with strict controls is common.

6) How do I prevent duplicate assets when importing repeatedly?

Use consistent unique identifiers and a consistent schema. If the UI/API offers de-duplication or update behavior, configure it appropriately (verify in docs).

7) Does Migration Center support application dependency mapping?

Some migration programs require dependency mapping; the level of dependency insight in Migration Center depends on ingestion and product capabilities. Verify current dependency features in official docs.

8) Is there an API for Migration Center?

Google Cloud commonly provides APIs for managed services, but availability and names can change. Verify the Migration Center API reference from the official docs.

9) Can I integrate Migration Center with CI/CD or ticketing systems?

Direct integrations may be limited. Many teams integrate indirectly by exporting inventory/plans and referencing wave IDs in tickets and pipelines.

10) Is Migration Center regional or global?

The UI is global, but the underlying resources may have location semantics. Verify location/region behavior in official docs and your project.

11) What’s the recommended org structure for Migration Center?

A common approach: – One central planning project per org (or per major division) – Separate execution projects/landing zones per environment (dev/test/prod) This supports governance and separation of duties.

12) How often should we refresh discovery?

It depends on change rate. Weekly or biweekly refreshes are common in active environments. Define a refresh SLA per business unit.

13) What’s the quickest way to show value?

Import a baseline inventory for a handful of critical apps, create groups and waves, and use that to drive the first migration sprint.

14) What are the biggest risks if we skip migration planning?

Common failures: – missing servers – incorrect sequencing – downtime due to unknown dependencies – cost overruns from overprovisioning – security gaps due to untracked assets

15) How do we secure access for external partners/consultants?

Use: – dedicated groups for partners – time-bound access (where possible) – least-privilege roles – separate projects for sensitive environments – audit log monitoring and reviews

16) Can we use Migration Center for modernization planning (not just rehosting)?

Yes—inventory and grouping support modernization planning. You still need service-specific modernization assessments and architecture work.

17) How do we measure migration progress using Migration Center?

Define what “progress” means (planned vs discovered vs migrated) and ensure the plan is updated. The exact tracking features depend on current Migration Center capabilities—verify in the UI/docs.

17. Top Online Resources to Learn Migration Center

Resource Type	Name	Why It Is Useful
Official documentation	Migration Center docs — https://cloud.google.com/migration-center/docs	Primary, up-to-date reference for features, ingestion methods, and workflows
Official pricing	Google Cloud Pricing Calculator — https://cloud.google.com/products/calculator	Estimate costs for dependent services used during migration and operations
Official migration guidance	Google Cloud Migration to Google Cloud overview — https://cloud.google.com/architecture/migration-to-google-cloud	Framework and best practices for planning and executing migrations
Architecture Center	Google Cloud Architecture Center — https://cloud.google.com/architecture	Reference architectures for landing zones, networking, security, and operations
Networking for hybrid	Cloud VPN docs — https://cloud.google.com/network-connectivity/docs/vpn	Common hybrid connectivity option used during migrations
Networking for hybrid	Cloud Interconnect docs — https://cloud.google.com/network-connectivity/docs/interconnect	Dedicated connectivity patterns for enterprise migrations
VM platform docs	Compute Engine docs — https://cloud.google.com/compute/docs	Target platform for many rehost (VM) migrations
Database migration docs	Database Migration Service — https://cloud.google.com/database-migration/docs	Execution tooling for migrating supported databases
Data transfer docs	Storage Transfer Service — https://cloud.google.com/storage-transfer/docs	Managed service for transferring object data into Google Cloud
Training labs	Google Cloud Skills Boost — https://www.cloudskillsboost.google	Hands-on labs (search for migration and assessment labs; availability varies)
Videos	Google Cloud Tech (YouTube) — https://www.youtube.com/@googlecloudtech	Product updates and best practices (search “Migration Center” and “migration”)
Community learning	Google Cloud Community — https://www.googlecloudcommunity.com/	Practical discussions and troubleshooting (validate against official docs)

Tip: For anything operational (permissions, ingestion prerequisites, API names), prefer the Migration Center docs first.

18. Training and Certification Providers

The following are training providers/platforms. Details like exact course titles and delivery modes can change—check each website.

DevOpsSchool.com – Suitable audience: DevOps engineers, SREs, cloud engineers, platform teams – Likely learning focus: Cloud operations, DevOps practices, tooling, and cloud migration foundations – Mode: Check website (online/corporate/self-paced/live) – Website: https://www.devopsschool.com/
ScmGalaxy.com – Suitable audience: Engineers and teams learning software configuration management and DevOps-oriented practices – Likely learning focus: SCM/DevOps fundamentals, automation, process-oriented training – Mode: Check website – Website: https://www.scmgalaxy.com/
CLoudOpsNow.in – Suitable audience: Cloud operations practitioners, system administrators transitioning to cloud – Likely learning focus: Cloud operations, reliability, and operational readiness – Mode: Check website – Website: https://www.cloudopsnow.in/
SreSchool.com – Suitable audience: SREs, operations engineers, reliability-focused platform teams – Likely learning focus: SRE practices, monitoring/incident management, production readiness – Mode: Check website – Website: https://www.sreschool.com/
AiOpsSchool.com – Suitable audience: Operations and platform engineers exploring AIOps and automation – Likely learning focus: AIOps concepts, automation, operational analytics – Mode: Check website – Website: https://www.aiopsschool.com/

19. Top Trainers

These are trainer-related sites and platforms. Offerings and specialization can vary—review each site directly.

RajeshKumar.xyz – Likely specialization: DevOps/cloud training and guidance (verify current offerings) – Suitable audience: Beginners to intermediate engineers seeking practical coaching – Website: https://rajeshkumar.xyz/
devopstrainer.in – Likely specialization: DevOps training and consulting-style coaching (verify current offerings) – Suitable audience: DevOps engineers and teams – Website: https://www.devopstrainer.in/
devopsfreelancer.com – Likely specialization: DevOps freelancing services and training resources (verify current offerings) – Suitable audience: Teams seeking short-term expertise and enablement – Website: https://www.devopsfreelancer.com/
devopssupport.in – Likely specialization: DevOps support and training resources (verify current offerings) – Suitable audience: Operations/DevOps teams needing practical support – Website: https://www.devopssupport.in/

20. Top Consulting Companies

These organizations may provide consulting services related to DevOps, cloud, and migration programs. Confirm capabilities, references, and scope directly with each company.

cotocus.com – Likely service area: Cloud/DevOps consulting and engineering services (verify exact service catalog) – Where they may help: Migration planning, cloud adoption, DevOps implementation – Consulting use case examples: – Build a migration assessment and wave plan using Migration Center – Design a secure landing zone and connectivity for migration execution – Website: https://cotocus.com/
DevOpsSchool.com – Likely service area: Training and consulting services across DevOps and cloud practices – Where they may help: Team enablement, migration factory setup, CI/CD and operations readiness – Consulting use case examples: – Define migration operating model (intake → assess → plan → execute) – Build runbooks for migration waves and cutovers – Website: https://www.devopsschool.com/
DEVOPSCONSULTING.IN – Likely service area: DevOps and cloud consulting (verify exact scope) – Where they may help: DevOps transformation, automation, cloud operations support for migration – Consulting use case examples: – Implement governance/IAM patterns for migration projects – Integrate migration tracking with operational dashboards and processes – Website: https://www.devopsconsulting.in/

21. Career and Learning Roadmap

What to learn before Migration Center

To use Migration Center effectively, you should know: – Google Cloud fundamentals – Projects, billing accounts, IAM, resource hierarchy – Compute basics – VMs, storage, networking, DNS, firewall rules – Migration fundamentals – Rehost/replatform/refactor/retire/retain strategies (“6 Rs”) – Inventory and CMDB concepts – Asset identity, ownership, environments, lifecycle – Basic security – least privilege, audit logs, sensitive metadata handling

What to learn after Migration Center

Once you can discover and plan, deepen execution skills: – Landing zone design – org structure, Shared VPC, IAM model, network segmentation – Hybrid networking – VPN/Interconnect, DNS, routing, firewalling, NAT – Execution tooling – VM migration tooling (for rehosting) – Database Migration Service – Storage Transfer Service / Transfer Appliance – Operations – Cloud Monitoring, Logging, incident response – backup/DR design – FinOps – budgeting, cost allocation, rightsizing, commitment planning

Job roles that use Migration Center

Cloud solutions architect
Migration architect / migration factory lead
Platform engineer
DevOps engineer / SRE (migration execution and operational readiness)
Cloud security engineer (governance and audit)
Technical program manager for cloud migration

Certification path (if available)

Migration Center itself is not typically a standalone certification topic, but it aligns with: – Associate Cloud Engineer (ACE) – Professional Cloud Architect (PCA) – Professional Cloud DevOps Engineer – Professional Cloud Security Engineer

Verify current Google Cloud certification paths: https://cloud.google.com/learn/certification

Project ideas for practice

Inventory normalization project: Import assets from two sources (CSV + another system export) and create a unified grouping taxonomy.
Wave planning simulation: Create 5 waves across 3 apps with different maintenance windows and dependencies.
Governance exercise: Implement IAM roles for migration admins vs app owners; validate audit logs for key actions.
Cost-awareness exercise: Use inventory sizing to propose a target Compute Engine sizing plan and compare cost scenarios in the Pricing Calculator.
Migration factory runbook: Write SOPs for intake, assessment, wave readiness, cutover checklist, rollback plan.

22. Glossary

Asset: A discovered or imported resource to be considered for migration (often a VM/server).
Assessment: Evaluation of assets for readiness, sizing, risk, and migration approach.
Collector: A tool/process that gathers inventory metadata from an environment and sends it to Migration Center.
CMDB: Configuration Management Database, a system for tracking IT assets and relationships.
Group (Application group): A logical set of assets representing an application or business service.
Hybrid connectivity: Network connectivity between on‑prem/other clouds and Google Cloud (VPN or Interconnect).
IAM: Identity and Access Management; controls permissions to Google Cloud resources.
Import job: A workflow that ingests inventory data (for example, via CSV).
Inventory: The dataset of assets and attributes used for planning and tracking migrations.
Landing zone: The foundational Google Cloud environment (org, projects, network, security) where workloads land.
Least privilege: Security principle of granting only the minimal permissions required.
Migration wave: A planned phase of migration that groups a set of assets/apps to migrate together in a timeframe.
Rehost: “Lift-and-shift” migration of workloads with minimal changes.
Replatform: Migration with some optimization (for example, moving to managed services where possible).
Refactor: Significant application changes to cloud-native architectures.
RPO/RTO: Recovery Point Objective / Recovery Time Objective for disaster recovery requirements.
Wave readiness: A gate/checklist ensuring prerequisites (networking, IAM, runbooks, rollback) are ready for a migration wave.

23. Summary

Migration Center in Google Cloud is a migration planning service that helps you discover assets, build a trustworthy inventory, assess and organize workloads, and plan migration waves. It fits into the broader Google Cloud Migration ecosystem as the control center for scope and coordination, while data-plane moves are performed by dedicated migration execution services.

From a cost perspective, your biggest cost drivers are usually execution (compute/storage/network) and indirect analytics/logging costs—not the planning UI itself. Security-wise, treat inventory metadata as sensitive, enforce least-privilege IAM, and ensure audit logging and export destinations are properly secured.

Use Migration Center when you need a structured, repeatable way to plan migrations at scale. As a next step, pair your Migration Center plan with a landing zone design and the execution tooling required for your workloads (VM, database, and data transfer migrations), then run a pilot wave to validate your approach.

Official docs to continue: https://cloud.google.com/migration-center/docs

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