During my discussions with customers I’ve sometimes heard some incorrect expectations and assumptions when people are defining their backup and recovery strategy. As a database and, in general, data centric person I think it is quite important to understand what the Point In Time Recovery (PITR) means and what Google Cloud SQL can do and what it cannot do. The information here is relevant for September 2022 when the post has been written.
Let’s start from the point of time recovery and how it works. From the high level of view the PITR should provide the ability to restore and recover your data up to the last seconds defining a desirable point of time in the past to represent the consistent dataset at that moment.
To achieve that goal the database recovery uses a combination of backup and stored transaction logs. The transaction logs contain sequential records with all the changes applied to the database dataset. The logs have different names, such as binary log, Write-Ahead Logging (WAL) or Redo logs, but conceptually they are designed to store and apply information for recovery purposes. To recover the database instance should be restored from the latest suitable backup which was completed before the PITR and apply all the changes from the transaction logs starting from time when the backup had started and until the PITR time.
In one of my previous posts I’ve noted that the GCP Cloud SQL for SQL Server doesn’t have point of time recovery as of March 2022. As result the default out of box backups can only provide RPO as 24 hours or more. The exact RPO might vary from day to day since you can only specify a window for backup but not exact time. So far it seems like the only reasonable approach to reduce the RPO is to schedule on-demand backups, and in this post I am going to show how you can do that using a couple of different approaches.
Before starting the post let me clarify that what I am going to describe as the state of readiness of the Google Cloud SQL Server is actual for early February 2022. It is quite possible that some things can be different when you read the post.
For the last several months I was helping some big enterprises to adopt Google Cloud Platform (GCP) and, as part of the implementation, a significant number of SQL Server databases were moving to the GCP Cloud SQL service. But when we started to build the environment in GCP it was clear that the SQL Server option for Cloud SQL is much inferior not only to some other cloud offerings and on-prem installations but also to other databases engines on the same Cloud SQL. In short the SQL Server on GCP Cloud SQL service lacked some essential features. Here I will try to explain why I think the SQL Server in GCP is not mature enough for enterprise.