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Migration

As explained in Google Anthos in Action

Migration is the process of moving workloads or applications from one execution environment or deployment model to another.

Migration moves workloads from virtual machines or other execution environments into containers and deploys the resulting artifacts on a compatible GKE or Anthos cluster. It offers an incremental modernization path when rewriting legacy applications is impractical or too expensive. section 2.4.6 section 16.6

Prioritize workloads with these characteristics:

  • Stateless web frontends that benefit from lightweight, independently scalable containers. section 15.2
  • Multitier web applications, middleware, and commercial software that can be separated into independent containers. section 15.2
  • Medium-to-large databases whose data layer can be separated from compute, including MySQL, Postgres, and Redis. section 15.2
  • Bursty, low-duty-cycle, development, training, and lab workloads where rapid provisioning matters. section 15.2

A practical migration has three phases: setup, migration, and optimization. Setup creates a processing cluster, registers a migration source, establishes the cloud landing zone, and discovers candidate workloads. Migration generates container images, a Dockerfile, data volumes, and deployment YAML; data is moved and synchronized automatically. Optimization tests and adjusts the generated artifacts before deployment. section 15.3.1

Containerizing an Apache VM

A GCE VM running Apache can be registered as a migration source, converted into container artifacts by a separate Kubernetes processing cluster, and deployed to GKE. The operational sequence creates source credentials, installs Migrate for Anthos, creates and validates a migration plan, generates and downloads artifacts, then applies the deployment specification with kubectl. The resulting service can expose the migrated web server through a load balancer. section 15.4.2

Windows workloads follow the same migctl workflow, with a Windows workload type and artifacts staged in Cloud Storage. The downloaded package includes a Dockerfile and deployment specification that can be expanded, built, and pushed to Container Registry. section 15.4.4

Figure 15.1 Setup and Migrate for Anthos
15-01

Use the workflow diagram to track setup, migration, and optimization as a connected operational process. section 15.3.1

How Google Anthos in Action covers it

How deep it goes
Explains workload selection, three operational phases, generated artifacts, credentials, validation, deployment, and Windows variations.
Examples
Demonstrates Apache on a GCE VM, Linux and Windows migrations, generated artifacts, and load-balanced Kubernetes deployment.
What it assumes
Requires a configured landing zone, processing cluster, source access, identity permissions, network settings, security, and billing.
What you can do after
Apply via migctl: register sources, create migration plans, generate artifacts, inspect status, and deploy containerized workloads.
How it connects
Connects virtual machines, containers, Kubernetes clusters, cloud landing zones, service accounts, Dockerfiles, and deployment YAML.

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