Which solution meets these requirements and is MOST cost-effective?
Create an S3 Lifecycle policy that copies the objects from one of the application S3 buckets to the centralized S3 bucket.
Use S3 Same-Region Replication to replicate logs from the S3 buckets to another S3 bucket in us-west-2. Use this S3 bucket for log analysis.
Write a script that uses the PutObject API operation every day to copy the entire contents of the buckets to another S3 bucket in us-west-2. Use this S3 bucket for log analysis.
Write AWS Lambda functions in these accounts that are triggered every time logs are delivered to the S3 buckets (s3:ObjectCreated:* event). Copy the logs to another S3 bucket in us-west-2. Use this S3 bucket for log analysis.
Explanations:
An S3 Lifecycle policy only allows for automated transitions or deletions of objects after a certain period of time. It cannot copy objects to another S3 bucket. Thus, this option does not fulfill the requirement to copy logs to a centralized bucket.
S3 Same-Region Replication (SRR) allows automatic replication of objects between S3 buckets within the same AWS region (us-west-2 in this case). This meets the requirement for centralized log storage while ensuring logs do not leave the region. It is also cost-effective and requires minimal operational overhead.
Writing a custom script to use the PutObject API to copy data every day adds significant operational overhead. Additionally, this approach is prone to errors and would require manual management of logs, making it less efficient and more costly.
While using AWS Lambda to copy logs from S3 buckets is feasible, it introduces additional complexity. Lambda functions incur costs per invocation, and setting up triggers for every object creation in multiple accounts adds operational overhead. SRR is a simpler and more cost-effective solution.
I deduce that the answer is:
Use S3 Same-Region Replication to replicate logs from the S3 buckets to another S3 bucket in us-west-2. Use this S3 bucket for log analysis.