An IoT application collects data from a large number of devices and uses DynamoDB to store the data.
Due to variable and unpredictable workloads, short bursts of traffic spikes occur resulting in throttling of requests on the DynamoDB table.
What is the optimal solution to this problem?
Click on the arrows to vote for the correct answer
A. B. C. D.Answer: D.
Option A is incorrect because this is not the most cost-effective solution.
It results in an over-provisioned and underutilized DynamoDB table.
Option B is incorrect because it is not the most optimal solution.
Auto-scaling is a delayed process and doesn't work well with short bursts of traffic spikes.
Option C is incorrect because it is not the most optimal solution.It requires additional development and operational overhead for the implementation and maintenance of the Lambda function.
Option D is CORRECT because Amazon's on-demand capacity mode is the best solution for applications whose database workload is complex to forecast, with large spikes of short duration or average table utilization well below the peak.
Reference:
https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/HowItWorks.ReadWriteCapacityMode.html#HowItWorks.OnDemand https://aws.amazon.com/blogs/aws/amazon-dynamodb-on-demand-no-capacity-planning-and-pay-per-request-pricing/The optimal solution to address the problem of throttling of requests on the DynamoDB table due to variable and unpredictable workloads is to configure DynamoDB Auto-Scaling. Option B is the correct answer.
DynamoDB Auto-Scaling allows for automatic adjustment of read and write capacity of DynamoDB tables in response to changes in application traffic. It enables DynamoDB to automatically increase or decrease capacity based on the configured thresholds, which can be based on CloudWatch metrics such as table utilization, throttled requests, or other custom metrics.
Option A, increasing the provisioned capacity, can help prevent throttling, but it is not an optimal solution because it requires manual adjustments and may result in overprovisioning and higher costs.
Option C, configuring a CloudWatch alarm on DynamoDB utilization and using the alarm to trigger a Lambda function to scale up the DynamoDB capacity is a viable solution, but it requires additional setup and maintenance of the Lambda function.
Option D, switching the DynamoDB table to on-demand capacity mode, may eliminate throttling, but it can result in higher costs due to the pay-per-request pricing model.
Therefore, the best option is to configure DynamoDB Auto-Scaling to automatically adjust the capacity of the DynamoDB table based on the workload. This ensures that the application can handle short bursts of traffic spikes without experiencing throttling, while also optimizing costs by scaling down capacity during periods of low traffic.