AWS Certified CloudOps Engineer Associate SOA-C03 Practice Question

A gaming company runs its leaderboard microservice on an ElastiCache for Redis cluster using the cache.r6g.large node type in cluster-mode disabled. During weekend tournaments, GET requests increase tenfold and CPU utilization on the primary exceeds 80 percent, resulting in time-outs. Operations wants the cache layer to scale out automatically during bursts and scale in afterward without code changes or manual intervention, while maintaining write availability and existing TTL behavior. Which approach meets these requirements?

Enable Multi-AZ with automatic failover on the existing cluster and configure a CloudWatch alarm to reboot the primary when CPU exceeds 80 percent.
Replace the Redis cluster with an ElastiCache for Memcached cluster and add nodes through an Auto Scaling group for horizontal scaling.
Create a new cluster-mode enabled Redis replication group and attach an Application Auto Scaling target-tracking policy that adds or removes shards based on EngineUtilization.
Modify the parameter group to increase maxclients and reserved-memory, then enable AOF persistence to improve performance under load.

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Answer Description

Only a cluster-mode enabled replication group can add or remove shards to change throughput and memory capacity with no code change, because Redis clients continue to use the same configuration endpoint. ElastiCache integrates with Application Auto Scaling, so a target-tracking policy based on a CloudWatch metric such as EngineUtilization can automatically increase or decrease shard count during load spikes.

Multi-AZ with automatic failover (incorrect) improves availability but does not add capacity. Changing parameters or enabling AOF (incorrect) does not provide elastic scaling. Switching to Memcached (incorrect) would require code changes and Application Auto Scaling cannot automatically remove nodes; write durability would also be lost.

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