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Difficulty: HardCost-Optimized Database Design and Capacity Planning

A company is designing a database architecture for a multi-tenant web application. The database tier has two distinct workloads:

First, a tenant metadata and configuration store which experiences predictable, steady read/write volume throughout the day, requiring high availability with a recovery point objective (RPO) of 00.

Second, an analytics database that ingests large batches of telemetry data from tenants during random, unpredictable 1515-minute windows, remaining completely idle for the rest of the day.

Which combination of database configurations will meet these requirements in the most cost-effective manner? (Select TWO.)

  1. Configure an Amazon RDS for PostgreSQL Multi-AZ DB instance deployment using gp3 storage volumes for the tenant metadata.Answer
  2. Configure an Amazon DynamoDB table in On-Demand capacity mode for the analytics telemetry store.Answer
  3. C
    Configure an Amazon RDS for PostgreSQL Single-AZ DB instance with an active Read Replica, relying on the replica as the automatic failover target to guarantee a recovery point objective (RPO) of zero.
  4. D
    Configure an Amazon DynamoDB table in Provisioned capacity mode with Auto Scaling enabled to automatically adjust capacity units from zero to peak during ingestion windows.
  5. E
    Configure Amazon RDS for PostgreSQL in a Multi-AZ DB instance deployment and purchase a Compute Savings Plan to discount the hourly database instance compute costs.

Answer

Configure an Amazon RDS for PostgreSQL Multi-AZ DB instance deployment using gp3 storage volumes for the tenant metadata, and configure an Amazon DynamoDB table in On-Demand capacity mode for the analytics telemetry store.
The correct architecture combines an Amazon RDS Multi-AZ DB instance deployment with gp3 storage for the tenant metadata, and an Amazon DynamoDB table in On-Demand capacity mode for the telemetry store. The RDS Multi-AZ deployment ensures high availability and zero recovery point objective (RPO) through synchronous replication. Utilizing gp3 volumes allows the company to optimize storage costs by configuring performance independent of storage size. DynamoDB On-Demand capacity mode is ideal for the telemetry store because it instantly handles unpredictable, short-duration spikes without throttling and incurs no charges when the database is idle.

Step-by-Step Solution

1
Analyze the tenant metadata store requirements.
The metadata store requires high availability, RPO of 00, and handles predictable, steady volume.
RDS Multi-AZ DB instance deployments utilize synchronous replication to a standby instance in another Availability Zone, ensuring an RPO of 00 and automatic failover. General Purpose gp3 storage is the most cost-effective storage option for predictable database workloads because it decoupling performance (IOPS and throughput) from capacity.
2
Analyze the analytics telemetry store requirements.
The analytics store requires handling sudden, unpredictable spikes during 1515-minute windows, remaining idle for most of the day.
Amazon DynamoDB in On-Demand capacity mode scales dynamically to meet write spikes instantly without throttling. Since charges are based strictly on actual read/write requests consumed, no costs are incurred during the long idle periods, making it highly cost-effective.
3
Evaluate the database replication and capacity planning distractors.
Identify incorrect configurations based on replication mechanics, capacity scaling speed, and savings plan applicability.
RDS Read Replicas are asynchronously replicated and cannot guarantee RPO of 00. DynamoDB Provisioned capacity mode cannot scale to 00 and Auto Scaling cannot scale up fast enough for a 1515-minute spike from a low baseline. Compute Savings Plans do not cover Amazon RDS instances.

Key Concept

Cost-Optimized Database Capacity Planning and Storage Selection
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Topics

Cost-Optimized Database Design and Capacity Planning