You’ll almost certainly require a relational database for transaction processing if you’re developing an application. Cloud SQL can help you with that. It’s a MySQL, PostgreSQL, and SQL Server relational database that’s completely managed. It automates database deployment, storage capacity management, backups, and out-of-the-box high availability and disaster recovery/failover while lowering maintenance costs.
It’s simple to set up Cloud SQL. You choose the area and zone where you want the instance to be built, and it is generated. Configure the machine type to have the correct number of CPUs and RAM for your application. Depending on latency, QPS, and cost needs, choose between solid state and hard disk devices for storage. Cloud SQL also has options for automatic backups and point-in-time recovery. Backups can be scheduled and stored in several places. It is suggested that production applications use the built-in high availability (HA) option, which provides a 99.95 percent SLA. Google Cloud uses a heartbeat signal to continually monitor the Cloud SQL instance, and when a master fails, an automated failover to another zone in your specified area is initiated in the event of an outage. To guard against regional failure, you may also construct copies across regions. You may also activate automatic storage increase to add extra storage when your current storage is reaching capacity. Cloud SQL Insights is a free application that helps Cloud SQL database users discover, diagnose, and identify issues in their queries. It offers self-service, simple monitoring, and diagnostic data that goes beyond detection to assist you in determining the source of performance issues.
If you’re migrating an existing application to the cloud, you’ll almost certainly need to migrate your SQL database to Cloud SQL. Database Migration Service (DMS) makes moving MySQL and PostgreSQL databases from on-premises, Google Compute Engine, and other clouds to Cloud SQL a breeze. It is serverless, easy to set up and available at no additional cost. It replicates data continuously for minimal downtime migrations. The following is how it works: Provide information about your data source, such as the database engine (MySQL, PostgreSQL, Amazon RDS, or others). For the least amount of downtime, choose between one-time or continuous replication. As your destination, create a Cloud SQL instance. DMS makes connecting to the source instance simple by giving several choices. You may allow-list an IP address, set up VPC peering, or establish a reverse SSH tunnel using a cloud-hosted Virtual Machine. Finally, test the migrated instance and promote it to the principal Cloud SQL instance. At rest and in transit, CloudSQL data is automatically secured. External connections can be made SSL-only if desired. You may also utilize Cloud SQL Proxy for secure connectivity, which is a program that allows you to connect to your Cloud SQL instance from your local workstation. Firewall protection allows you to manage network access. Cloud SQL is SSAE 16, ISO 27001, PCI DSS v3.0, and HIPAA compliant from a compliance standpoint.
Cloud SQL may be utilized in a variety of scenarios and with a variety of computing options. As a transactional database, long-term analytics backend with BigQuery, predictive analytics with Vertex AI, and event-driven communications with Pub/Sub, it can be used in any application. When coupled with Datasteam (Change Data Capture), Cloud SQL provides a powerful real-time analysis solution for any incoming data. Whatever your application’s use case, Cloud SQL is built to work with a variety of Google Cloud services as well as external services. Use this fully managed relational database to let Google handle the never-ending database maintenance, such as setting up servers, applying patches and updates, establishing replication, and maintaining backups. Instead, concentrate your efforts on higher-priority tasks where you can truly contribute. Check out the documentation for a more in-depth look at Cloud SQL.

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