Tick-Bank's Web Traffic Analytics Implementation Guidelines

Web Traffic Analytics Implementation Guidelines for Tick-Bank

Question

Tick-Bank is a privately held Internet retailer of both physical and digital products founded in 2008

The company has more than six-million clients worldwide.

Tick-Bank aims to serve as a connection between digital content makers and affiliate dealers, who then promote them to clients.

Tick-Bank's technology aids in payments, tax calculations and a variety of customer service tasks.

Tick-Bank assists in building perceptibility and revenue making opportunities for entrepreneurs. Tick-Bank runs multiple java based web applications running on windows based EC2 machines in AWS managed by internal IT Java team, to serve various business functions.

Tick-Bank is looking to enable web-site traffic analytics there by understanding user navigational behavior, preferences and other click related info.

The amount of data captured per click is in tens of bytes.

Tick-Bank has the following objectives in mind for the solution. Tick-Bank uses KPL to process the data and KCL library to consume the records.

Thousands of events are being generated every second and every event is sensitive and equally important and Gluebush.com wants to treat every record as a separate stream.

please detail the implementation guidelines.

select 2 options.

Answers

Explanations

Click on the arrows to vote for the correct answer

A. B. C. D.

Answer: A,D.

Option A is correct -When batching is not implemented, each record is treated as a separate data stream record.

In this context batching is not implemented.

https://docs.aws.amazon.com/streams/latest/dev/kinesis-kpl-concepts.html

Option B is incorrect - When batching is not implemented, each record is treated as a separate data stream record.

In this context batching is not implemented.

https://docs.aws.amazon.com/streams/latest/dev/kinesis-kpl-concepts.html

Option C is incorrect -Batching refers to performing a single action on multiple items instead of repeatedly performing the action on each individual item.

In this context, the "item" is a record, and the action is sending it to Kinesis Data Streams.

In a non-batchingsituation, you would place each record in a separate Kinesis Data Streams record and make one HTTP request to send it to Kinesis Data Streams.

With batching, each HTTP request can carry multiple records instead of just one.

https://docs.aws.amazon.com/streams/latest/dev/kinesis-kpl-concepts.html

Option D is correct -Batching refers to performing a single action on multiple items instead of repeatedly performing the action on each individual item.

In this context, the "item" is a record, and the action is sending it to Kinesis Data Streams.

In a non-batchingsituation, you would place each record in a separate Kinesis Data Streams record and make one HTTP request to send it to Kinesis Data Streams.

With batching, each HTTP request can carry multiple records instead of just one.

https://docs.aws.amazon.com/streams/latest/dev/kinesis-kpl-concepts.html

Tick-Bank is looking to enable web-site traffic analytics by understanding user navigational behavior, preferences, and other click-related information. The amount of data captured per click is in tens of bytes. Tick-Bank uses KPL to process the data and KCL library to consume the records. Thousands of events are being generated every second, and every event is sensitive and equally important, and Tick-Bank wants to treat every record as a separate stream. Based on these requirements, the following implementation guidelines should be considered:

Option A: each record in a separate Kinesis Data Streams record and make one HTTP request to send it to Kinesis Data Streams.

This option involves creating a Kinesis Data Stream that will receive the clickstream data generated by Tick-Bank's web applications. Since every event is sensitive and equally important, Tick-Bank can consider each record as a separate stream, and each record can be sent as a separate HTTP request to the Kinesis Data Stream. This approach provides low latency, as each record is sent to the stream immediately after it is generated, but it can result in a high number of HTTP requests to the Kinesis Data Stream, which may increase the overall cost of the solution.

Option B: each HTTP request carries multiple Kinesis Stream records, which are sent to Kinesis Data Streams.

This option involves batching multiple records into a single HTTP request and sending them to the Kinesis Data Stream. This approach can reduce the number of HTTP requests sent to the Kinesis Data Stream and therefore reduce the overall cost of the solution. However, since Tick-Bank wants to treat every record as a separate stream, this option may not be the best fit for Tick-Bank's use case.

Option C: Batching is implemented as the target implementation.

Batching involves collecting multiple records and sending them together in a single request to the Kinesis Data Stream. This option can reduce the number of requests sent to the Kinesis Data Stream and improve the overall cost efficiency. However, since Tick-Bank wants to treat every record as a separate stream, batching may not be the optimal solution.

Option D: Batching is not implemented as the target implementation.

This option involves sending each record as a separate stream to the Kinesis Data Stream. Since every event is sensitive and equally important, treating each record as a separate stream can help ensure that no data is lost. While this approach may result in a high number of HTTP requests and increased costs, it provides the necessary level of data integrity for Tick-Bank's use case.

In summary, based on the requirements provided by Tick-Bank, the optimal solution is Option A: each record in a separate Kinesis Data Streams record and make one HTTP request to send it to Kinesis Data Streams, as it ensures that every record is treated as a separate stream and provides low latency. However, this option may result in a higher number of HTTP requests and increased costs. Option D is also a viable solution, as it provides the necessary level of data integrity for Tick-Bank's use case, but may result in increased costs. Options B and C may not be the best fit for Tick-Bank's use case, given its requirements.