Understanding the Purpose of AWS Kinesis Firehose
Question
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. HH runs 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 KPL to collect events and transaction logs and process the stream.
The event/log size is around 12 bytes. The log stream generated into the stream is used for multiple purposes.HH proposes Kinesis Firehose to process the stream and capture information.
What purposes can be fulfilled OOTB without writing applications or consumer code? Select 4 options.
Answers
Explanations
Click on the arrows to vote for the correct answer
A. B. C. D. E. F.Answer: A, C, D, E.
Amazon Kinesis Data Firehose is a fully managed service for delivering real-time streaming data to destinations such as Amazon Simple Storage Service (Amazon S3), Amazon Redshift, Amazon Elasticsearch Service (Amazon ES), and Splunk.
With Kinesis Data Firehose, you don't need to write applications or manage resources.
Configure data producers to send data to Kinesis Data Firehose, and it automatically delivers the data to the destination that you specified.
You can also configure Kinesis Data Firehose to transform your data before delivering it.
https://docs.aws.amazon.com/firehose/latest/dev/what-is-this-service.htmlHikeHills.com (HH) is an online retailer that sells outdoor gear for various activities, and they use AWS to run their web applications. They capture clickstream data and use a custom-built recommendation engine to improve sales and understand customer preferences. They currently use AWS Kinesis KPL to collect events and transaction logs and process the stream.
HH proposes using Kinesis Firehose to process the stream and capture information. Kinesis Firehose is a fully managed service that delivers real-time streaming data to destinations such as Amazon S3, DynamoDB, Redshift, Elasticsearch, and Splunk.
The event/log size is around 12 bytes, and the log stream generated into the stream is used for multiple purposes. The following are the purposes that can be fulfilled OOTB without writing applications or consumer code:
A. Deliver real-time streaming data to Amazon S3: With Kinesis Firehose, HH can deliver real-time streaming data to an Amazon S3 bucket. This is useful for long-term storage, backup, and analysis. HH can use Amazon S3 for data warehousing, big data analytics, and business intelligence.
B. Deliver real-time streaming data to DynamoDB to support processing of digital documents: HH can use Kinesis Firehose to deliver real-time streaming data to DynamoDB. This is useful for processing digital documents such as invoices, contracts, and receipts. HH can use DynamoDB to store and retrieve data, and perform queries and scans.
C. Deliver real-time streaming data to Redshift to support data warehousing and real-time analytics: HH can use Kinesis Firehose to deliver real-time streaming data to Redshift. This is useful for data warehousing and real-time analytics. HH can use Redshift to store and analyze large amounts of data, and perform queries and reports.
D. Ingest data into ES domains to support Enterprise search built on Elasticsearch: HH can use Kinesis Firehose to ingest data into Elasticsearch domains. This is useful for enterprise search, where HH can search and analyze large amounts of data across multiple sources. HH can use Elasticsearch to index, search, and visualize data.
E. Allow Splunk to read and process data stream directly from Kinesis Firehose: HH can use Kinesis Firehose to allow Splunk to read and process data streams directly. This is useful for real-time analysis and monitoring of data streams. HH can use Splunk to monitor and troubleshoot their infrastructure, applications, and services.
F. Ingest data into Amazon EMR to support big data analytics: HH can use Kinesis Firehose to ingest data into Amazon EMR. This is useful for big data analytics, where HH can analyze large amounts of data using tools such as Apache Hadoop, Spark, and Hive. HH can use Amazon EMR to run big data workloads, process and analyze data, and generate insights and reports.
In conclusion, Kinesis Firehose can deliver real-time streaming data to various destinations, such as Amazon S3, DynamoDB, Redshift, Elasticsearch, and Splunk. HH can use these destinations for long-term storage, processing, analysis, and visualization of data. HH can fulfill multiple purposes OOTB without writing applications or consumer code, such as data warehousing, real-time analytics, enterprise search, and big data analytics.
