Google Cloud

Java – Configure MySQL for Google Appengine (Standard)

In this post, you will learn about how to configure MySQL properties in your Spring Boot application for deploying it on Google AppEngine (Standard) environment. This article assumes that the MySQL database is set up as part of Google Cloud SQL fully-managed database service. The following will be covered:

  • Configuration properties in Application.properties
  • Configure POM entries in pom.xml file

Configuration properties in Application.properties

In application.properties file, while working with Spring Boot app with JPA repository, you need to have following configuration properties in application.properties file. The below assumes that you have a MySQL database with name as dbname and username/password as root/root.

spring.cloud.gcp.sql.database-name=dbname
spring.cloud.gcp.sql.instance-connection-name=dbname:region:instance-id
spring.cloud.gcp.sql.database-type=mysql
spring.datasource.username=someUsername
spring.datasource.password=somePassword

In above properties, the instance connection name can be obtained from the project Cloud SQL page whose link could look like https://console.cloud.google.com/sql/instances?project=projectName

While working in local environment, you could comment above properties and use the following:

spring.datasource.url=jdbc:mysql://localhost:3306/dbname
spring.datasource.username=root
spring.datasource.password=root

POM entry in POM.xml file

The following POM entry needs to be put in pom.xml file.

<dependency>
    <groupId>org.springframework.cloud</groupId>
    <artifactId>spring-cloud-gcp-starter-sql</artifactId>
    <version>1.0.0.M1</version>
</dependency>

While working in the local environment, one could comment above and rather use following POM entry:

<dependency>
    <groupId>mysql</groupId>
    <artifactId>mysql-connector-java</artifactId>
    <scope>runtime</scope>
</dependency>

References

Summary

In this post, you learned about how to configure MySQL properties in Spring Boot app for deploying it on Google App Engine (Standard) environment.

Did you find this article useful? Do you have any questions or suggestions about this article? Leave a comment and ask your questions and I shall do my best to address your queries.

Ajitesh Kumar

I have been recently working in the area of Data analytics including Data Science and Machine Learning / Deep Learning and BI. I would love to connect with you on Linkedin. Check out my books titled as Designing Decisions, and First Principles Thinking.

Recent Posts

The Watermelon Effect: When Green Metrics Lie

We’ve all been in that meeting. The dashboard on the boardroom screen is a sea…

2 weeks ago

Coefficient of Variation in Regression Modelling: Example

When building a regression model or performing regression analysis to predict a target variable, understanding…

3 months ago

Chunking Strategies for RAG with Examples

If you've built a "Naive" RAG pipeline, you've probably hit a wall. You've indexed your…

3 months ago

RAG Pipeline: 6 Steps for Creating Naive RAG App

If you're starting with large language models, you must have heard of RAG (Retrieval-Augmented Generation).…

3 months ago

Python: List Comprehension Explained with Examples

If you've spent any time with Python, you've likely heard the term "Pythonic." It refers…

3 months ago

Large Language Models (LLMs): Four Critical Modeling Stages

Large language models (LLMs) have fundamentally transformed our digital landscape, powering everything from chatbots and…

6 months ago