Deploy scalable and highly available databases in Google Cloud →mediumMultiple ChoiceObjective-mapped
PCDE Practice Question: Deploy scalable and highly available databases in Google Cloud
A company uses Cloud Bigtable for a real-time analytics pipeline. They have configured replication with a primary cluster in us-central1 and a secondary cluster in us-west1. They want to minimize data loss during a failover to the secondary cluster. What is the best approach to achieve the lowest possible RPO?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Use multi-cluster routing with read-failover enabled and direct all writes to the primary cluster.
Bigtable replication is asynchronous, so RPO is determined by replication lag. To minimize data loss, you should route writes to the primary cluster and use read-failover routing to consume from the secondary only when primary is unhealthy. During failover, switch writes to secondary manually.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Use single-cluster routing with failover priority set to the secondary cluster.
Why it's wrong here
Single-cluster routing with failover priority sends all traffic to the primary until it fails; this does not affect RPO.
- ✗
Use any-replica routing and let Cloud Bigtable automatically direct reads and writes to the healthiest cluster.
Why it's wrong here
any-replica routing allows writes to both clusters, which can cause conflicts and does not guarantee lowest RPO.
- ✗
Use single-cluster routing and regularly back up the Bigtable data.
Why it's wrong here
Backups would result in RPO equal to backup frequency, which is higher than replication lag.
- ✓
Use multi-cluster routing with read-failover enabled and direct all writes to the primary cluster.
Why this is correct
This configuration ensures writes go to primary (minimizing replication lag) and reads automatically fail over to secondary when primary is unhealthy, minimizing data loss.
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