A company is running a Docker application on Amazon ECS. The application must scale based on user load in the last 15 seconds. How should a Developer instrument the code so that the requirement can be met?
A.
Create a high-resolution custom Amazon CloudWatch metric for user activity data, then publish data every 30 seconds
B.
Create a high-resolution custom Amazon CloudWatch metric for user activity data, then publish data every 5 seconds
C.
Create a standard-resolution custom Amazon CloudWatch metric for user activity data, then publish data every 30 seconds
D.
Create a standard-resolution custom Amazon CloudWatch metric for user activity data, then publish data every 5 seconds
B) Correct - Amazon CloudWatch high-resolution metrics support granularity down to 1 second (as opposed to standard-resolution metrics, which have a granularity of 1 minute).
To scale based on user activity from the last 15 seconds, high-resolution metrics are essential because standard-resolution metrics would not provide the necessary granularity.
It is B, we need an high resolution CloudWatch metric in order to generate data each second (instead of each minute with the standard resolution). We are able to publish data every 5 second and analyze the user load data for the last 15 seconds.
Standard-resolution of CloudWatch is 1 minute, you need high-resolution for timespan smaller than 1 minute so C, D are out
A only give you data after 30 sec while you need last 15 sec -> B is the answer.
Option D recommends publishing data every 5 seconds, but using a standard-resolution metric. While this may capture user activity data frequently enough, it may not provide the necessary level of detail for accurate scaling decisions.
Therefore, the best option is to create a high-resolution custom CloudWatch metric for user activity data and publish it every 5 seconds. This will provide accurate and frequent data points that can be used to make scaling decisions based on user load in the last 15 seconds.
Option A and C recommend creating a custom CloudWatch metric for user activity data and publishing it every 30 seconds, which may not be frequent enough to capture user activity data within the last 15 seconds accurately
To scale the Docker application on Amazon ECS based on user load in the last 15 seconds, a high-resolution custom Amazon CloudWatch metric for user activity data should be created, and data should be published every 5 seconds.
Option B is the correct answer because high-resolution custom metrics have a finer resolution than standard-resolution custom metrics, with data points that can be as frequent as 1 second. The user activity data needs to be measured in near-real-time to accurately reflect the current user load, and publishing the data every 5 seconds will provide the necessary frequency. This will allow Amazon ECS to scale the Docker application appropriately based on the user load.
Option A, C, and D do not provide the required frequency for the user activity data, and therefore may not be accurate enough to scale the Docker application in a timely manner.
"The application must scale based on user load in the last 15 seconds".
- The app needs to scale based on load in the last 15 secs
- If data was published every 30 seconds, this criteria wouldn't be fulfilled as it'd have to wait for the remaining 15 sec, whereas with 5 secs publishing, data can be received every 5 sec enabling the app to scale at the required time
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