A company hosts a portfolio of e-commerce websites across the Oregon, N. Virginia, Ireland, and Sydney AWS regions. Each site keeps log files that capture user behavior. The company has built an application that generates batches of product recommendations with collaborative filtering in Oregon. Oregon was selected because the flagship site is hosted there and provides the largest collection of data to train machine learning models against. The other regions do NOT have enough historic data to train accurate machine learning models.
Which set of data processing steps improves recommendations for each region?

Question

A company hosts a portfolio of e-commerce websites across the Oregon, N. Virginia, Ireland, and Sydney AWS regions. Each site keeps log files that capture user behavior. The company has built an application that generates batches of product recommendations with collaborative filtering in Oregon. Oregon was selected because the flagship site is hosted there and provides the largest collection of data to train machine learning models against. The other regions do NOT have enough historic data to train accurate machine learning models.

Which set of data processing steps improves recommendations for each region?

Maksim Alpatov · Accepted Answer

Use the CloudWatch Logs agent to consolidate logs into a single CloudWatch Logs group.

Maksim Alpatov · Answer

Use the e-commerce application in Oregon to write replica log files in each other region.

Maksim Alpatov · Answer

Use Amazon S3 bucket replication to consolidate log entries and build a single model in Oregon.

Maksim Alpatov · Answer

Use Kinesis as a buffer for web logs and replicate logs to the Kinesis stream of a neighboring region.

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