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Difficulty: MediumDatabase and Storage Strategy

A healthcare provider is designing a claims portal that will store digital claims documents and transaction metadata. The claims documents (average size 2 MB) are accessed by internal processes and must also be shared securely with a third-party auditor operating in a separate AWS account. The documents require immediate retrieval for the first 30 days. After 30 days, they must be archived to a cheaper storage tier, but must remain retrievable within 5 minutes. The transaction metadata workload is relational, requires high availability across multiple Availability Zones, and experiences frequent spikes in analytical reporting queries that must not impact active write transactions. Which two of the following database and storage configurations should the solutions architect select to satisfy these requirements? (Select TWO.)

  1. Store the claims documents in an Amazon S3 bucket. Encrypt the bucket using a customer managed KMS key, and configure the key policy to allow cross-account decrypt permissions for the third-party auditor's AWS account. Use an S3 Lifecycle policy to transition the documents to Amazon S3 Glacier Flexible Retrieval after 30 days.Answer
  2. Store the transaction metadata in an Amazon Aurora PostgreSQL database cluster. Deploy the cluster with one writer instance and at least one reader replica in a different Availability Zone. Configure Aurora Auto Scaling to dynamically add reader replicas based on average CPU utilization to handle reporting query spikes.Answer
  3. C
    Store the transaction metadata in an Amazon RDS for PostgreSQL Multi-AZ deployment. Configure the reporting applications to direct their read-only queries to the standby replica instance located in the secondary Availability Zone to prevent performance impacts on the primary database instance.
  4. D
    Store the claims documents in an Amazon S3 bucket. Encrypt the bucket using the default AWS-managed key (aws/s3). Configure the S3 bucket policy to grant read access to the third-party auditor's AWS account, and configure a cross-account IAM role to allow key access.
  5. E
    Store the claims documents in an Amazon S3 bucket. Use an S3 Lifecycle policy to transition the documents to Amazon S3 Glacier Deep Archive after 30 days to minimize storage costs, and use expedited retrievals to access the documents when requested by the auditor.

Answer

The system should store the claims documents in an Amazon S3 bucket, encrypted with a customer managed KMS key, and transitioned to Amazon S3 Glacier Flexible Retrieval after 30 days. The database tier should utilize Amazon Aurora PostgreSQL with reader replicas and Auto Scaling.
Storing the claims documents in Amazon S3 and transitioning them to Amazon S3 Glacier Flexible Retrieval after 30 days meets both the archive and the sub-5-minute retrieval requirements because Glacier Flexible Retrieval supports expedited retrievals (1-5 minutes). Additionally, cross-account access to encrypted S3 objects requires a customer managed KMS key because the default AWS-managed KMS key (aws/s3) cannot be shared across accounts. For the database tier, Amazon Aurora PostgreSQL with reader replicas and Auto Scaling allows the system to automatically handle spikes in analytical reporting queries without affecting the primary writer instance.

Step-by-Step Solution

1
Determine the S3 storage class and lifecycle policy requirements for archiving claims documents.
Select Amazon S3 with an S3 Lifecycle transition to S3 Glacier Flexible Retrieval after 30 days.
S3 Glacier Flexible Retrieval supports expedited retrievals (1-5 minutes), meeting the 5-minute RTO requirement, whereas S3 Glacier Deep Archive only supports standard/bulk retrievals (12-48 hours).
2
Evaluate the encryption and cross-account access requirements for S3 objects.
Use a customer managed KMS key (CMK) with cross-account access granted via the key policy.
AWS-managed KMS keys (like aws/s3) cannot be shared with external AWS accounts because their policies cannot be customized, so a customer managed KMS key is required.
3
Determine the database architecture to support scaling reads for analytical reporting without affecting writes.
Deploy Amazon Aurora PostgreSQL with reader replicas and configure Aurora Auto Scaling.
Aurora Replicas handle read scaling, and Auto Scaling automatically handles query spikes. Amazon RDS Multi-AZ standby instances are passive and cannot be queried.

Key Concept

Selecting optimal storage tiers and encryption methods for cross-account access, and choosing high-availability database architectures to scale read-heavy analytical workloads.
Estimated Time:2m 0s
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Topics

Database and Storage Strategy

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