HikeHills.com (HH) is an online specialty retailer that sells clothing and outdoor refreshment gear for trekking, go camping, boulevard biking, mountain biking, rock hiking, ice mountaineering, skiing, avalanche protection, snowboarding, fly fishing, kayaking, rafting, road and trace running, and many more. HHruns their entire online infrastructure on java based web applications running on AWS.
The HH is capturing click stream data and use custom-build recommendation engine to recommend products which eventually improve sales, understand customer preferences and already using AWS kinesis data streams (KDS) KPL to collect events and transaction logs and process the stream. Multiple departments from HH use different streams to address real-time integration and induce analytics into their applications.
HH is looking at generating costs and system usage by different departments.
How can this be achieved? select 1 option.
Click on the arrows to vote for the correct answer
A. B. C. D.Answer: A.
Use tags to categorize and track your AWS costs.
When you apply tags to your AWS resources, including streams, your AWS cost allocation report includes usage and costs aggregated by tags
https://docs.aws.amazon.com/streams/latest/dev/tagging.htmlThe correct answer is A. Use tags to categorize and track the AWS KDS costs generated by each department.
Explanation:
HikeHills.com (HH) is capturing click stream data and using custom-built recommendation engines to improve sales, understand customer preferences, and already using AWS Kinesis Data Streams (KDS) KPL to collect events and transaction logs and process the stream. Multiple departments from HH use different streams to address real-time integration and induce analytics into their applications. Therefore, HH needs to generate costs and system usage by different departments.
Option A: Use tags to categorize and track the AWS KDS costs generated by each department Tagging AWS resources is a best practice that enables cost allocation, categorization, and tracking usage by different departments or projects. With tagging, users can easily identify and allocate the costs generated by each department or project. Users can also use AWS Cost Explorer to visualize and analyze the cost and usage data of tagged resources, and generate reports based on specific tags. Therefore, this option is the best choice.
Option B: Use unique names for streams and track the AWS costs generated by each department This option does not provide an efficient solution for tracking costs generated by each department, as it does not provide any information about the department responsible for creating the stream. Using unique names for streams is a good practice, but it is not sufficient for cost allocation and tracking.
Option C: Define different subscriptions for each account and allocate the same administrator to manage all the subscriptions for each department This option does not provide a solution for cost allocation and tracking, as it only suggests creating different subscriptions for each account. Additionally, allocating the same administrator to manage all the subscriptions for each department does not ensure efficient cost management.
Option D: Define different User IDs to process the stream and calculate costs based on different users. This is easy to implement. This option is not a suitable solution for cost allocation and tracking, as it only suggests defining different User IDs to process the stream. Moreover, it does not provide a detailed method for tracking costs and usage data by different departments or users.
In conclusion, option A is the best solution for HH to generate costs and system usage by different departments. By using tags to categorize and track the AWS KDS costs generated by each department, HH can efficiently allocate costs and usage data to specific departments or projects.