docs(memorystore): added valkey caching demo application

[dackers86]

Description

Fixes #

Note: Before submitting a pull request, please open an issue for discussion if you are not associated with Google.

Checklist

• I have followed Sample Format Guide
• pom.xml parent set to latest shared-configuration
• Appropriate changes to README are included in PR
• These samples need a new API enabled in testing projects to pass (let us know which ones)
• These samples need a new/updated env vars in testing projects set to pass (let us know which ones)
• Tests pass: mvn clean verify required
• Lint passes: mvn -P lint checkstyle:check required
• Static Analysis: mvn -P lint clean compile pmd:cpd-check spotbugs:check advisory only
• This sample adds a new sample directory, and I updated the CODEOWNERS file with the codeowners for this sample
• This sample adds a new Product API, and I updated the Blunderbuss issue/PR auto-assigner with the codeowners for this sample
• Please merge this PR for me once it is approved

[code-review-assist]

Hi @dackers86 and reviewers,

I'm currently reviewing this pull request and will post my full review in a few minutes. In the meantime, here's a quick summary of the changes for you and other reviewers to get up to speed:

This pull request adds a new demo application that showcases Valkey caching with a Spring Boot application. The application interacts with a PostgreSQL database and uses Valkey as an in-memory cache to improve performance.

Here's a breakdown of the changes:

• New directory: memorystore/valkey/caching/demo added, containing the complete demo application.
• README.md: A comprehensive README file was added, detailing how to run the application locally using Docker Compose, and how to deploy it to Google Cloud Run (both with a solo API and a web app + API).
• .gitignore: A comprehensive .gitignore file was added to the app directory to ignore various build artifacts and IDE-specific files.
• Dockerfile: A Dockerfile was added to the app directory to build a Docker image for the application.
• docker-compose.yaml: A docker-compose.yaml file was added to the app directory to simplify the local development setup.
• init.sql: An init.sql script was added to the app directory to create the necessary database tables.
• pom.xml: The pom.xml file was updated to include dependencies for Spring Boot, Jedis (Redis client), PostgreSQL JDBC driver, and other necessary libraries.
• Java files: Several Java files were added or modified, including DataController, HomeController, Item, ItemController, ItemsRepository, JdbcConfig, JedisConfig, and Main, implementing the core logic of the caching demo application.
• static/script.js: A JavaScript file was added to the static directory to handle the frontend interactions with the API.
• templates/index.html: An HTML template was added to the templates directory to provide a user interface for the application.
• sample-data directory: A sample-data directory was added, containing a Dockerfile, docker-compose.yaml, and pom.xml to create sample data for the application.

The checklist in the PR description indicates that all required tests and lint checks have passed.

I'll provide a more detailed review shortly.

And now, a little haiku to brighten your day:

Cache speeds up the code,
Data flows with graceful ease,
Reviews now are fun!

[code-review-assist]

This pull request adds a demo application showcasing Valkey caching with Memorystore. The documentation and code are well-structured and cover various aspects of setup and deployment. However, there are a few minor improvements that can enhance clarity and user experience.

I've summarized the Google Java Style Guide elements used in this review below:

• Javadoc: Ensured Javadoc comments are present for classes and public methods, providing clear descriptions of their purpose and usage.
• Naming Conventions: Checked for consistent and descriptive names for classes, methods, and variables.
• Constant Variables: Verified the use of uppercase with underscores for constant variables.
• Comments: Recommended adding comments to explain complex logic or non-obvious code segments.
• Error Handling: Suggested improvements for error handling and validation to prevent unexpected behavior.