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Zorluk: OrtaOptimizing Performance with Caching and DAX

A corporate employee portal retrieves employee profile metadata and contact information from an Amazon DynamoDB table. During morning log-in hours, the portal experiences high read latency and ProvisionedThroughputExceededException errors when fetching the profiles of executive leadership, which are queried by many employees. The developer wants to reduce read latency to sub-millisecond levels for these read-heavy requests without modifying the existing query API calls. Which of the following actions should the developer take? (Select two.)

  1. Deploy an Amazon DynamoDB Accelerator (DAX) cluster to cache the read requests.Cevap
  2. Configure the application to use the DAX client SDK to direct read requests to the DAX cluster.Cevap
  3. C
    Increase the provisioned Read Capacity Units (RCUs) on the DynamoDB table to absorb the peak traffic.
  4. D
    Modify the application to perform Scan operations with Parallel Scan enabled to retrieve employee profiles.
  5. E
    Configure the DAX client by hardcoding the developer's AWS Access Key ID and Secret Access Key directly in the application code.

Cevap

To optimize read performance and achieve sub-millisecond latency for the hot partition requests without changing query logic, the developer should deploy an Amazon DynamoDB Accelerator (DAX) cluster and update the application to use the DAX client SDK.
The correct options recommend deploying a DynamoDB Accelerator (DAX) cluster and using the DAX client SDK. DAX acts as a managed write-through cache that provides sub-millisecond response times for read-intensive workloads. Because the DAX SDK is API-compatible with DynamoDB, it serves as a drop-in replacement that requires no changes to the existing query API calls.

Adım Adım Çözüm

1
Identify the performance requirement and constraint.
The application requires sub-millisecond latency for frequently accessed items (hot partitions) without changing the query API calls.
This points to a caching layer that is compatible with the DynamoDB API.
2
Select the appropriate caching solution.
Amazon DynamoDB Accelerator (DAX) is selected as it is a fully managed, highly available, in-memory cache specifically designed for DynamoDB that delivers sub-millisecond latency.
DAX API is compatible with DynamoDB, meaning the application query logic does not need to change.
3
Configure the application to communicate with the cache.
The application code is updated to use the DAX client SDK instead of the standard AWS SDK for DynamoDB.
The DAX SDK acts as a drop-in replacement, directing requests to the DAX cluster endpoint and falling back to DynamoDB if necessary.

Anahtar Kavram

Amazon DynamoDB Accelerator (DAX) is an in-memory write-through cache designed to reduce read response times to sub-milliseconds for DynamoDB tables, requiring minimal application modifications via the DAX client SDK.
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Optimizing Performance with Caching and DAX

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