Cloud SQL; an Introduction

Cloud SQL is a fully managed database service that stands out from its peers due to high performance, seamless integration, and impressive scalability. In this quest you will receive hands-on practice with the basics of Cloud SQL and quickly progress to advanced features, which you will apply to production frameworks and application environments. From creating instances and querying data with SQL, to building Deployment Manager scripts and connecting Cloud SQL instances with applications run on GKE containers, this quest will give you the knowledge and experience needed so you can start integrating this service right away.

Key features

1. Fully managed: Cloud SQL automatically ensures your databases are reliable, secure, and scalable so that your business continues to run without disruption. Cloud SQL automates all your backups, replication, encryption patches, and capacity increases-while ensuring greater than 99.95% availability, anywhere in the world.

2. Integrated: Access Cloud SQL instances from just about any application. Easily connect from App Engine, Compute Engine, Google Kubernetes Engine, and your workstation. Open up analytics possibilities by using BigQuery to directly query your Cloud SQL databases.

3. Reliable: Easily configure replication and backups to protect your data. Go further by enabling automatic failover to make your database highly available. Your data is automatically encrypted, and Cloud SQL is SSAE 16, ISO 27001, and PCI DSS compliant and supports HIPPA compliance.

3. Easy migrations to Cloud SQL: Database Migration Service (DMS) makes it easy to migrate your production databases to Cloud SQL with minimal downtime. This serverless offering eliminates the hassle of manually provisioning, managing, and monitoring migration-specific resources. DMS leverages the native replication capabilities of MySQL, PostgreSQL, SQL Server and Oracle to maximize the fidelity and reliability of your migration. And it's available at no additional charge for migrations to Cloud SQL.

Extensive instance configurations options

In Cloud SQL, we have the option of a detailed instance configuration for each database system. The configuration of the service for the application requirements will translate into performance, but also price.

When creating an instance, we can choose:

1. region and location of the new instance.

2. virtual machine type, its memory and CPU; we can choose shared-core machines or high memory machines;

3. disc: SSD with higher speed and higher QPS (query per second), or HDD with lower price;

4. capacity (data storage) ranging from 10 to 30720 GB; you can also set up an automatic (permanent) storage increase in case it's needed.

Service scalability and cost flexibility

Since Cloud SQL uses the computing power of Google Cloud, the cost depends on the disk space used and the usage per second. If there are few queries to the database and the usage isn't high, the cost of the service will be lower. When the application is under load (e.g., it will be used by several times more users than usual), the service will scale up, and Cloud SQL will easily handle all queries. The use of computing power will be higher, and the cost of the service will be proportional to consumption.

Reduction of maintenance costs thanks to automation

As I mentioned, GCP services are fully managed - and so is Cloud SQL. The Google team takes care of the physical infrastructure, which allows the user to transfer the maintenance costs to the development zone (in the case of Arena.pl, the transition to Google Cloud Platform allowed to reduce the internal infrastructure maintenance costs by 20-30%). Service automation not only allows for a reduction of internal costs, but also prevents from making mistakes.

A lot of automation can be implemented into the Cloud SQL service, which takes the strain off the technical team. You can automate, for example:

1. database administration;

2. management of database capacity and optimization of the occupied disk space,

3. performing data backup and recovery.

Use Cases

Google Cloud SQL provides a cloud-based alternative to local MySQL, PostgreSQL, and SQL Server databases. Users should use Cloud SQL if they want to spend less time managing their database and more time using it.
Many applications running on Compute Engine, App Engine, and other services in Google Cloud use Cloud SQL for database storage.

1.) Build a containerized app with a scalable database

Google Kubernetes Engine enables rapid development by making it easy to deploy, update, and manage applications and services. Cloud SQL it easy to set up, manage, and administer Postgres databases on Google Cloud. This use case is a building block of a microservices architecture that is backed by an independent storage service, decentralizing data management and ensuring that each service is independently scalable.

1. MySQL: It is an open-source, fully-managed, relational database management system used for cloud application development and deployment. You can use Cloud SQL for MySQL with App Engine applications that are written in languages specifically Java, Python, PHP, Nodes.js, Go, and Ruby. Cloud SQL for MySQL can also be used with external applications using the standard MySQL protocol.

Features of Cloud SQL for MySQL

1. Fully managed MySQL Community Edition databases in the cloud.

2. Create and manage instances in the Google Cloud Console.

3. Instances are available in the US, EU, Asia, and Australia.

4. Customer data is encrypted on Google's internal networks and also in database tables, temporary files, and backups.

5. Supports Automated and on-demand backups, and point-in-time recovery.

6. Allows integration with Google Cloud's operations suite logging and monitoring.

PostgreSQL

PostgreSQL is a free, open-source, advanced RDBMS that can handle web services supporting many users at the same time. It focuses on extensibility and is referred to as enterprise-class RDBMS.

Cloud SQL for PostgreSQL can be used with App Engine applications running in a flexible environment written in Java, Python, PHP, Node.js, Go, and Ruby. It can also be used with external applications using the standard PostgreSQL client-sever protocol.

Features of Cloud SQL for PostgreSQL:

1. Fully managed PostgreSQL databases in the cloud.

2. Provides custom machine types with up to 624 GB of RAM and 96 CPUs.

3. Up to 30 TB of storage available, which can be expanded if needed.

4. Provides data replication between multiple zones with automatic failover.

5. Support for PostgreSQL client-server protocol and standard PostgreSQL connectors.

SQL Server

SQL Server is a relational database management software product that helps store and extract data when requested by the applications which can be running on the same system or a network of systems spread across a network.

Users can use Cloud SQL for SQL Server with App Engine applications running in the flexible environment written in Java, Python, PHP, Node.js, Go, and Ruby.

Features of Cloud SQL for SQL Server

1. Fully managed SQL Server databases in the cloud.

2. Up to 30 TB of storage available which also provides the ability to automatically increase the storage size if needed.

3. Support for secure external connections with the Cloud SQL Auth proxy or with the SSL/TLS protocol.

4. Allows integration with Stackdriver logging and monitoring.

5. Provides high availability through the regional persistent disk.