A hospital uses an electronic health records (EHR) system to collect two types of data
• Patient information, which includes a patient's name and address
• Diagnostic tests conducted and the results of these tests
Patient information is expected to change periodically Existing diagnostic test data never changes and only new records are added
The hospital runs an Amazon Redshift cluster with four dc2.large nodes and wants to automate the ingestion of the patient information and diagnostic test data into respective Amazon Redshift tables for analysis The EHR system exports data as CSV files to an Amazon S3 bucket on a daily basis Two sets of CSV files are generated One set of files is for patient information with updates, deletes, and inserts The other set of files is for new diagnostic test data only
What is the MOST cost-effective solution to meet these requirements?
An IOT company is collecting data from multiple sensors and is streaming the data to Amazon Managed Streaming for Apache Kafka (Amazon MSK). Each sensor type has
its own topic, and each topic has the same number of partitions.
The company is planning to turn on more sensors. However, the company wants to evaluate which sensor types are producing the most data sothat the company can scale
accordingly. The company needs to know which sensor types have the largest values for the following metrics: ByteslnPerSec and MessageslnPerSec.
Which level of monitoring for Amazon MSK will meet these requirements?