December 2020
Intermediate to advanced
200 pages
4h 59m
English
Content preview from Building Serverless Applications with Google Cloud Run
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Chapter 4. Working with a Relational Database
By now, you should have a good idea of what Cloud Run is and how you can use it to run and scale your container-based applications. However, Cloud Run needs data in order to be interesting; whether that data comes from blob storage, a database, or another API, even a serverless container needs data. In this chapter, I’ll show you how to use a relational database with Cloud Run.
A relational database is the most common way to store data for your application. I want to show you how to work with Cloud SQL, a managed relational database on Google Cloud. As a managed service, Cloud SQL takes a lot of operational tasks off your plate. It supports MySQL, PostgreSQL, and SQL Server, common database engines you can run anywhere. If you ever decide to migrate to another vendor, you’ll have a way out.
In this chapter, I’ll help you get started with Cloud SQL, show you how to deploy my to-do list demo application, and explore the various ways to connect a Cloud Run service to Cloud SQL.
Cloud Run can potentially scale up to one thousand (or more) containers very quickly. This can create performance bottlenecks in downstream systems, such as your Cloud SQL database. In the final part of this chapter, I’ll explain why and show the various controls you have available to keep your database running when a traffic burst comes.
Introducing the Demo Application
The demo application for this chapter and the next is a to-do list. It has a browser-based ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.