A global multiplayer gaming platform uses Amazon API Gateway, AWS Lambda, and an Amazon DynamoDB table to store and serve live game leaderboards. During peak tournament events, users experience high latency when retrieving leaderboard standings, and the DynamoDB table experiences read throttling. The company needs a caching solution to reduce response latency to milliseconds and offload read queries from the database. Which two actions should the solutions architect take to meet these requirements? (Choose two.)
- Deploy an Amazon DynamoDB Accelerator (DAX) cluster to cache read queries to the leaderboard table.Cevap
- Deploy an Amazon CloudFront distribution in front of the API Gateway, and configure a cache behavior for the leaderboard API resource with a positive Default TTL.Cevap
- CDeploy an Amazon CloudFront distribution in front of API Gateway, and set the Minimum TTL, Maximum TTL, and Default TTL values to 0 for the leaderboard API cache behavior.
- DTransition the DynamoDB table from on-demand mode to provisioned capacity mode with high Read Capacity Units (RCUs) to handle the peak spikes, while disabling all caching layers.
- ERedesign the DynamoDB table to use a monotonically increasing tournament timestamp as the partition key to aggregate leaderboard reads, and query the table directly.
Cevap
Deploying an Amazon DynamoDB Accelerator (DAX) cluster to cache read queries to the leaderboard table, and deploying an Amazon CloudFront distribution in front of API Gateway with a cache behavior configured with positive TTLs.
Deploying Amazon DynamoDB Accelerator (DAX) directly in front of DynamoDB handles database query caching, returning cached results in microseconds and reducing database read load. Deploying Amazon CloudFront in front of Amazon API Gateway with positive TTL values caches API responses at the edge, reducing both Lambda executions and API Gateway hits for global clients.
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Anahtar Kavram
Multi-tier caching using Amazon CloudFront and Amazon DynamoDB Accelerator (DAX)