A logistics company is designing a new global supply chain tracking system that requires a… — AWS Certified Solutions Architect - Professional

A logistics company is designing a new global supply chain tracking system that requires a highly available relational database for an OLTP workload. The application handles write-heavy transactions for package tracking statuses and must support a read-heavy dashboard showing real-time delivery performance metrics. The architecture requires that database read operations scale dynamically during peak shipping seasons without impacting write performance. Additionally, the system must achieve a Recovery Time Objective ( $RTO$ ) of less than $5\text{ minutes}$ and a Recovery Point Objective ( $RPO$ ) of less than $1\text{ minute}$ in the event of an Availability Zone outage. Which database and storage strategy meets these requirements while minimizing management overhead?

A
Deploy an Amazon RDS for PostgreSQL DB instance with a Multi-AZ standby deployment. Route dashboard read queries directly to the Multi-AZ standby instance, and configure RDS Auto Scaling to scale the standby instance's compute resources during peak hours.
Deploy an Amazon Aurora PostgreSQL DB cluster across multiple Availability Zones. Configure Aurora Replicas to handle the read-heavy dashboard queries, and set up Aurora Auto Scaling to dynamically adjust the number of replicas based on CPU utilization.Cevap
C
Deploy an Amazon RDS for PostgreSQL DB instance with a Multi-AZ deployment. Create cross-region read replicas in a secondary AWS Region to handle read queries, and configure a Pilot Light disaster recovery strategy with daily snapshots to achieve the RTO and RPO requirements.
D
Deploy an Amazon Aurora PostgreSQL DB cluster. Configure a centralized Amazon S3 bucket in a separate management account to store database backups, and secure the bucket using the default AWS-managed KMS key (aws/s3) with cross-account access granted via bucket policies.

Cevap

Deploying an Amazon Aurora PostgreSQL DB cluster across multiple Availability Zones with Aurora Replicas and Aurora Auto Scaling.

Deploying an Amazon Aurora PostgreSQL DB cluster across multiple Availability Zones natively provides high availability with synchronous replication to a shared storage volume, easily meeting the strict

RTO < 5\text{ minutes}

and

RPO < 1\text{ minute}

requirements during an Availability Zone outage. Aurora Replicas share the same underlying storage volume, reducing replication lag to milliseconds. Setting up Aurora Auto Scaling allows the cluster to dynamically scale the number of read replicas in response to CPU utilization spikes on the read-heavy dashboard, minimizing administrative overhead.

Adım Adım Çözüm

Analyze database workload and Availability Zone high availability requirements.

The system requires an OLTP database that handles write-heavy transactions and scales reads. An Availability Zone outage must meet

RTO < 5\text{ minutes}

and

RPO < 1\text{ minute}

This establishes the baseline requirements, eliminating single-instance configurations and low-frequency replication options.

Evaluate read-scaling mechanisms and read capability of high availability replicas.

Amazon Aurora Replicas share the cluster's underlying storage volume and can serve read traffic. Standby instances in Amazon RDS Multi-AZ deployments are passive and cannot serve read traffic.

This eliminates options that propose routing queries to standard RDS Multi-AZ standby instances.

Validate scalability and security constraints for the final configuration.

Aurora Auto Scaling dynamically adjusts replica counts based on target metrics (such as CPU utilization) to handle read-heavy dashboard spikes, meeting all RTO/RPO metrics with minimum operational overhead.

This confirms Aurora PostgreSQL with replicas and Auto Scaling is the optimal, low-overhead design.

Anahtar Kavram

Relational database high availability and scale-out read architectures

Tahmini Süre:1m 30s

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