By default, for each instance, Cloud SQL retains seven automated backups, in addition to on-demand backups. You can configure how many automated backups to retain (from 1 to 365). We charge a lower rate for backup storage than for other types of instances. https://cloud.google.com/sql/docs/mysql/backup-recovery/backups

This answer meets the RTO and RPO requirements by using synchronous replication within the same region, which ensures that all writes made to the primary instance are replicated to disks in both zones before a transaction is reported as committed 1 .  This minimizes data loss and downtime in case of a zonal or an instance failure, and allows for a quick failover to the standby instance 1 .

This answer also meets the high availability and disaster recovery requirements by using asynchronous replication across different regions, which ensures that the data changes made to the primary instance are replicated to the read replicas in other regions with minimal delay 2 .  This provides additional redundancy and backup in case of a regional failure, and allows for a manual failover to the read replica in another region 2 .

https://cloud.google.com/spanner/docs/iam#spanner.backupWriter

https://cloud.google.com/spanner/docs/schema-design D because high cardinality means you have more unique values in the collumn. That's a good thing for a hot-spotting issue. E because Spanner specifically has this feature to reduce hot spotting. Basically, it generates unique values https://cloud.google.com/spanner/docs/schema-design#bit_reverse_primary_key

D. Promote high-cardinality attributes in multi-attribute primary keys.

This is a correct answer because promoting high-cardinality attributes in multi-attribute primary keys can help avoid hotspots in Cloud Spanner.  High-cardinality attributes are those that have many distinct values, such as UUIDs, email addresses, or timestamps 1 .  By placing high-cardinality attributes first in the primary key, you can ensure that the rows are distributed more evenly across the key space, and avoid having too many requests sent to the same server 2 .

E. Use bit-reverse sequential value as the primary key.

This is a correct answer because using bit-reverse sequential value as the primary key can help avoid hotspots in Cloud Spanner.  Bit-reverse sequential value is a technique that reverses the bits of a monotonically increasing value, such as a timestamp or an auto-incrementing ID 1 .  By reversing the bits, you can create a pseudo-random value that spreads the writes across the key space, and avoid having all the inserts occurring at the end of the table 2 .

https://cloud.google.com/spanner/docs/autoscaling-overview

1. CloudSQL max out at 64TB, so unable to told 100TB of data. https://cloud.google.com/sql/docs/quotas#metrics_collection_limit 2. Scale is done manually on SQL Cloud

https://cloud.google.com/solutions/implementing-multi-tenancy-cloud-spanner#multi-tenancy-data-management-patterns

https://cloud.google.com/solutions/implementing-multi-tenancy-cloud-spanner

https://cloud.google.com/sql/docs/postgres/using-query-insights#filter_by_query_tags

To troubleshoot high read latency, you can use SQL statements to analyze the SPANNER_SYS.READ_STATS* tables. These tables contain statistics about read operations in Cloud Spanner, including the number of reads, read latency, and the number of read errors. By analyzing these tables, you can identify the cause of the high read latency and take appropriate action to resolve the issue. Other options, such as using query parameters to speed up frequently executed queries or changing the Cloud Spanner configuration from multi-region to single region, may not be directly related to the issue of high read latency. Similarly, analyzing the SPANNER_SYS.QUERY_STATS* tables, which contain statistics about query operations, may not be relevant to the issue of high read latency.