AWS Certified Solutions Architect Professional SAP-C02 Practice Question
A company operates a Kubernetes-based product-catalog microservice that runs in Amazon EKS clusters deployed in us-east-1, eu-west-1, and ap-southeast-2. The service performs read-only SQL queries against a single Amazon Aurora MySQL DB cluster located in us-east-1. During global marketing events, 90 % of traffic originates outside the primary Region and p99 end-to-end latency in Europe spikes above 400 ms. New performance objectives state:
End-user latency must remain below 100 ms at the 99th percentile worldwide.
Read traffic is expected to grow 5× within 12 months.
Catalog updates occur only in us-east-1 and may be eventually consistent everywhere else within 2 minutes.
The solution must keep code changes and ongoing cost to a minimum.
Which combination of actions best meets these objectives?
Put the API behind an Amazon CloudFront distribution and use Lambda@Edge to cache GET responses for 120 seconds at edge locations worldwide while leaving the Aurora database unchanged.
Implement Amazon Aurora Global Database by adding read-only secondary clusters in eu-west-1 and ap-southeast-2, and modify the service so that read queries are routed to the Region-local reader endpoint.
Migrate the catalog to Amazon DynamoDB and place a DynamoDB Accelerator (DAX) cluster in each Region, routing reads to the local DAX endpoint and writes to DynamoDB in us-east-1.
Create an Amazon ElastiCache for Redis Global Datastore: deploy a primary cluster in us-east-1 and read-only replica clusters in eu-west-1 and ap-southeast-2, and implement a write-through pattern so the service first reads from the Region-local Redis endpoint and updates the primary cluster after each catalog change.
ElastiCache Global Datastore replicates Redis data to up to two secondary Regions with typical cross-Region lag of less than 1 s, enabling sub-millisecond local reads while writes occur only in the primary Region. Using a write-through pattern keeps the cache hot and ensures replicas converge well inside the 2-minute consistency window. Because 90 % of requests are now served from in-memory caches close to users, p99 latency comfortably drops below 100 ms and Aurora writer CPU load is relieved without expensive multi-Region database clusters. Aurora Global Database would meet latency but requires full secondary clusters, dramatically increasing cost; migrating to DynamoDB with DAX demands a data-model change and additional engineering effort; edge caching with CloudFront cannot guarantee a warm cache globally, adds invalidation complexity, and leaves the database hot. Therefore, deploying an ElastiCache for Redis Global Datastore and adopting a write-through caching strategy is the most cost-effective way to satisfy all stated requirements.
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AWS Certified Solutions Architect Professional SAP-C02
Design for New Solutions
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