PAS-C01 Design of SAP Workloads on AWS Practice Question
A company runs SAP S/4HANA on AWS in a multi-AZ deployment. The SAP HANA database is 2 TB and uses EBS gp3 volumes. During a monthly patching cycle, the primary database fails over to the secondary, but the secondary takes over 30 minutes to come online. Which TWO changes would most likely reduce the failover time? (Choose two.)
⚠ Common exam trap
The trap here is that candidates often focus on network latency or instance placement (Options D and B) as the primary cause of slow failover, when in reality the bottleneck is the I/O performance of the log volumes during log replay.
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
✓
Increase the provisioned IOPS and throughput on the EBS log volumes.
Increasing the provisioned IOPS and throughput on the EBS log volumes accelerates the replay of redo logs during the takeover process. SAP HANA relies on log replay to bring the secondary database to a consistent state; higher IOPS/throughput reduces the time required to apply pending log entries, directly shortening failover duration.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Increase the provisioned IOPS and throughput on the EBS log volumes.
Why this is correct
Higher log volume performance improves replication throughput.
- ✓
Place the primary and secondary HANA servers in a cluster placement group.
Why this is correct
Placement groups reduce network latency between nodes.
- ✗
Use different EC2 instance types for primary and secondary to balance cost.
Why it's wrong here
Asymmetric instances can cause performance mismatch.
- ✗
Deploy all HANA nodes in the same Availability Zone to reduce network latency.
Why it's wrong here
Same AZ removes HA benefit.
- ✗
Enable EBS optimization on the secondary instance's EBS volumes.
Why it's wrong here
EBS optimization is automatic on current gen instances.
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