Spring framework Petclinic application is a Java application built with Spring Framework and Maven.

In this tutorial you will deploy this application into a Tomcat server running on a Google Compute Engine (GCE) VM and connect it to a PostgreSQL database running on a GCE VM.

You'll then modernize this application by using Migrate to Containers (M2C) to migrate it to run in a container on a Google Kubernetes Engine (GKE) cluster and generate Day2 artifacts to support modern CI/CD operations for your application.

In this tutorial you’ll do the following:

• Prepare your Google Cloud environment
• Create a PostgreSQL Ubuntu VM on GCE and prepare the Petclinic database
• Build and deploy Petclinic application into Tomcat on a GCE vm
• Install and configure M2C
• Qualify the workloads for migration using the migration center discovery client CLI (mcdc CLI)
• Migrate Petclinic database vm to a container
• Migrate Petclinic vm to a container
• Deploy the migrated database and application to your GKE cluster
• Clean up by deleting the project

For this reference guide, you need a Google Cloud project. You can create a new one, or select a project you already created:

1. Select or create a Google Cloud project.
   GO TO THE PROJECT SELECTOR PAGE

2. Enable billing for your project.
   ENABLE BILLING

3. Enable the Service Management API, Service Control API, Cloud Resource Manager API, Compute Engine API, Kubernetes Engine API, Google Container Registry API, Cloud Build API.
   ENABLE THE APIS

Your migration journey consist of a number of steps:

1. Prepare - In this step you will prepare your environment by installing PostgresSQL and Tomcat VMs, building and deploying the application and then installing Migrate to Containers.
2. Assess - In the assess step, you will run the Migration Center discovery client CLI and assess whether or not your PostgreSQL and Tomcat workloads are fit for containerization.
3. Migrate - In the migrate step you will migrate both of your VMs into containers and generate Day2 artifacts which can later be used in modern CI/CD pipelines.
4. Deploy - In the deploy step you will deploy your migrated workloads into a GKE cluster and verify that your application is working as expected.
5. Optimize - In the optimize step you will learn how to manually and automatically scale your migrated workloads and how to roll out application updated.

The simplest way to avoid any unexpected billing charges is to delete your GCP project. You can do so by running the command below in cloud shell:

gcloud projects delete $PROJECT_ID