You Have a Web Application That Is Currently Running on a Collection

question 273

Multiple Choice

You have a web application that is currently running on a collection of micro instance types in a single AZ behind a single load balancer. You have an Auto Scaling group configured to scale from 2 to 64 instances. When reviewing your CloudWatch metrics, you see that sometimes your Auto Scaling group is running 64 micro instances. The web application is reading and writing to a DynamoDB-configured backend and configured with 800 Write Capacity Units and 800 Read Capacity Units. Your customers are complaining that they are experiencing long load times when viewing your website. You have investigated the DynamoDB CloudWatch metrics; you are under the provisioned Read and write Capacity Units and there is no throttling. How do you scale your service to improve the load times and ensure the principles of high availability?

• A) Change your Auto Scaling group configuration to include multiple AZs.
• B) Change your Auto Scaling group configuration to include multiple AZs, and increase the number of Read Capacity Units in your DynamoDB table by a factor of three, because you will need to be calling DynarnoDB from three AZs.
• C) Add a second load balancer to your Auto Scaling group so that you can support more inbound connections per second.
• D) Change your Auto Scaling group configuration to use larger instances and include multiple AZ's instead of one.

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Definitions:

Binomial Distribution

A probability distribution that summarizes the likelihood that a value will take one of two independent states under a given number of trials.

Sampling Distribution

Sampling Distribution is the probability distribution of a given statistic based on a random sample, used to make inferences about a population.

Sample Proportion

The ratio of members in a sample exhibiting a certain trait to the total number of members in the sample.

Central Limit Theorem

A principle stating that the distribution of sample means approaches a normal distribution as the sample size becomes larger, regardless of the population's distribution.