Your current log analysis application takes more than four hours to generate a report of the top 10 users of your web application. You have been asked to implement a system that can report this information in real-time, ensure that the report is always up to date, and handle increases in the number of requests to your web application. Choose the option that is cost-effective and can fulfill the requirements.

Answer options:

A.Publish your data to CloudWatch Logs, and configure your application to autoscale to handle the load on demand.
B.Publish your log data to an Amazon S3 bucket.Use AWS CloudFormation to create an Auto Scaling group to scale your post-processing application configured to pull down your log files stored in an Amazon S3.
C.Post your log data to an Amazon Kinesis data stream, and subscribe to your log-processing application so that it is configured to process your logging data. Configure your application to autoscale to handle the load on demand.
D.Create a multi-AZ Amazon RDS MySQL cluster, post the logging data to MySQL, and run a map reduce job to retrieve the required information on user counts.

Answer – C
When you see Amazon Kinesis as an option, this becomes the ideal option to process data in real-time.
 Amazon Kinesis makes it easy to collect, process, and analyze real-time, streaming data so you can get timely insights and react quickly to new information. Amazon Kinesis offers key capabilities to cost-effectively process streaming data at any scale, along with the flexibility to choose the tools that best suit the requirements of your application. With Amazon Kinesis, you can ingest real-time data such as application logs, website clickstreams, IoT telemetry data, and more into your databases, data lakes and data warehouses, or build your own real-time applications using this data. 
For more information on Amazon Kinesis, please visit the below URL:
https://aws.amazon.com/kinesis