Your company has HQ in Tokyo and branch offices all over the world and is using a logistics software with a
multi-regional deployment on AWS in Japan, Europe and USA. The logistic software has a 3-tier architecture
and currently uses MySQL 5.6 for data persistence. Each region has deployed its own database. In the HQ
region you run an hourly batch process reading data from every region to compute cross-regional reports that
are sent by email to all offices this batch process must be completed as fast as possible to quickly optimize
logistics how do you build the database architecture in order to meet the requirements?
A.
For each regional deployment, use RDS MySQL with a master in the region and a read replica in the HQ
region.
B.
For each regional deployment, use MySQL on EC2 with a master in the region and send hourly EBS
snapshots to the HQ region.
C.
For each regional deployment, use RDS MySQL with a master in the region and send hourly RDS
snapshots to the HQ region.
D.
For each regional deployment, use MySQL on EC2 with a master in the region and use S3 to copy data files
hourly to the HQ region.
E.
Use Direct Connect to connect all regional MySQL deployments to the HQ region and reduce network
latency for the batch process.
A
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A
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I would say C.
WIth a read replic, you do not control the lag, which you do if you send a snapshot in an hourly basis
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Exactly, I will choose C.
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but the most recent changes will occur quickly in the read replica before you get to see them in the next coming snapshot, so technically ‘A’ shall be correct.
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A, AWS replicate changes in the master to read replica automatically, no need to send data. Create the report from the read replica.
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