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Exam AWS Certified Solutions Architect - Associate SAA-C03 All Questions

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Exam AWS Certified Solutions Architect - Associate SAA-C03 topic 1 question 77 discussion

A company needs to configure a real-time data ingestion architecture for its application. The company needs an API, a process that transforms data as the data is streamed, and a storage solution for the data.
Which solution will meet these requirements with the LEAST operational overhead?

  • A. Deploy an Amazon EC2 instance to host an API that sends data to an Amazon Kinesis data stream. Create an Amazon Kinesis Data Firehose delivery stream that uses the Kinesis data stream as a data source. Use AWS Lambda functions to transform the data. Use the Kinesis Data Firehose delivery stream to send the data to Amazon S3.
  • B. Deploy an Amazon EC2 instance to host an API that sends data to AWS Glue. Stop source/destination checking on the EC2 instance. Use AWS Glue to transform the data and to send the data to Amazon S3.
  • C. Configure an Amazon API Gateway API to send data to an Amazon Kinesis data stream. Create an Amazon Kinesis Data Firehose delivery stream that uses the Kinesis data stream as a data source. Use AWS Lambda functions to transform the data. Use the Kinesis Data Firehose delivery stream to send the data to Amazon S3.
  • D. Configure an Amazon API Gateway API to send data to AWS Glue. Use AWS Lambda functions to transform the data. Use AWS Glue to send the data to Amazon S3.
Show Suggested Answer Hide Answer
Suggested Answer: C 🗳️

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123jhl0
Highly Voted 2 years, 2 months ago
Selected Answer: C
(A) - You don't need to deploy an EC2 instance to host an API - Operational overhead (B) - Same as A (**C**) - Is the answer (D) - AWS Glue gets data from S3, not from API GW. AWS Glue could do ETL by itself, so don't need lambda. Non sense. https://aws.amazon.com/glue/
upvoted 44 times
Futurebones
1 year, 7 months ago
I don''t understand is why we should use Lambda in between to transform data. To me, Kinesis data firehose is enough as it is an extract, transform, and load (ETL) service.
upvoted 5 times
Remy_d
1 year, 2 months ago
It is because they assume that Kinesis Data Firehose built-in transformations are not enough. So you have to use specific lambda transformation. Please refer to this link : https://aws.amazon.com/kinesis/data-firehose/#:~:text=Amazon%20Kinesis%20Data%20Firehose%20is,data%20stores%2C%20and%20analytics%20services.
upvoted 6 times
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TariqKipkemei
Highly Voted 1 year, 4 months ago
Selected Answer: C
The company needs an API = Amazon API Gateway API A real-time data ingestion = Amazon Kinesis data stream A process that transforms data = AWS Lambda functions Kinesis Data Firehose delivery stream to send the data to Amazon S3 A storage solution for the data = Amazon S3
upvoted 27 times
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PaulGa
Most Recent 3 months, 1 week ago
Selected Answer: C
Ans C - the API is given so just configure Kinesis stream/Firehouse to use it
upvoted 1 times
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awsgeek75
11 months, 2 weeks ago
Selected Answer: C
C is least operational overhead A: EC2 is overhead in this scenario B: Same as A D: Glue is not real time data streaming
upvoted 3 times
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Mikado211
1 year ago
Selected Answer: C
It looks overengineered, but as it works, let's go for the C
upvoted 5 times
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Ruffyit
1 year, 1 month ago
The company needs an API = Amazon API Gateway API A real-time data ingestion = Amazon Kinesis data stream A process that transforms data = AWS Lambda functions Kinesis Data Firehose delivery stream to send the data to Amazon S3 A storage solution for the data = Amazon S3
upvoted 4 times
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peekingpicker
1 year, 2 months ago
Selected Answer: D
"a real-time data ingestion" isn't firehose not realtime ? Kinesis FireHose is "Near" Real-time . It has 60 seconds gap. I think it should be D
upvoted 1 times
rlamberti
1 year, 2 months ago
The real-time part (data ingestion) will be performed by Kinesis Data Stream and API Gateway. After this, the transformation and storage of the data don't need to be in real-time, since it was already ingested, so Kinesis Firehose + Lambda is perfect. C makes sense to me.
upvoted 5 times
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Guru4Cloud
1 year, 4 months ago
Selected Answer: C
Option C provides the least operational overhead to meet the requirements: API Gateway provides the API Kinesis Data Streams ingests the real-time data Lambda functions transform the data Firehose delivers the data to S3 storage The key advantages are: Serverless architecture requires minimal operational overhead Fully managed ingestion, processing and storage services No need to manage EC2 instances
upvoted 2 times
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diabloexodia
1 year, 5 months ago
Requirements: API- API gateway Real time data ingestion - AWS Kinesis data stream ETL(Extract Transform Load) - Kinesis Firehose Storage- S3
upvoted 3 times
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tamefi5512
1 year, 5 months ago
Selected Answer: C
C - is the answer
upvoted 1 times
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cookieMr
1 year, 6 months ago
Selected Answer: C
C. By leveraging these services together, you can achieve a real-time data ingestion architecture with minimal operational overhead. The data flows from the API Gateway to the Kinesis data stream, undergoes transformations with Lambda, and is then sent to S3 via the Kinesis Data Firehose delivery stream for storage. A. This adds operational overhead as you need to handle EC2 management, scaling, and maintenance. It is less efficient compared to using a serverless solution like API Gateway. B. It requires deploying and managing an EC2 to host the API and configuring Glue. This adds operational overhead, including EC2 management and potential scalability limitations. D. It still requires managing and configuring Glue, which adds operational overhead. Additionally, it may not be the most efficient solution as Glue is primarily used for ETL scenarios, and in this case, real-time data transformation is required.
upvoted 2 times
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winzzhhzzhh
1 year, 7 months ago
Selected Answer: D
I am gonna choose D for this. Kinesis Data Stream + Data Firehose will adds up to the operational overhead, plus it is "Near real-time", not a real time solution. Lambda functions scale automatically, so no management of scaling/compute resources is needed. AWS Glue handles the data storage in S3, so no management of that is needed.
upvoted 2 times
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UnluckyDucky
1 year, 9 months ago
Gotta love all those chatgpt answers y'all are throwing at us. Kinesis Firehose is NEAR real-time, not real-time like your bots tell you.
upvoted 2 times
pentium75
12 months ago
Stem is about "real-time data INGESTION", not real-time processing.
upvoted 2 times
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bullrem
1 year, 11 months ago
Selected Answer: C
option C is the best solution. It uses Amazon Kinesis Data Firehose which is a fully managed service for delivering real-time streaming data to destinations such as Amazon S3. This service requires less operational overhead as compared to option A, B, and D. Additionally, it also uses Amazon API Gateway which is a fully managed service for creating, deploying, and managing APIs. These services help in reducing the operational overhead and automating the data ingestion process.
upvoted 1 times
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Selected Answer: C
Option C is the solution that meets the requirements with the least operational overhead. In Option C, you can use Amazon API Gateway as a fully managed service to create, publish, maintain, monitor, and secure APIs. This means that you don't have to worry about the operational overhead of deploying and maintaining an EC2 instance to host the API. Option C also uses Amazon Kinesis Data Firehose, which is a fully managed service for delivering real-time streaming data to destinations such as Amazon S3. With Kinesis Data Firehose, you don't have to worry about the operational overhead of setting up and maintaining a data ingestion infrastructure.
upvoted 1 times
Finally, Option C uses AWS Lambda, which is a fully managed service for running code in response to events. With AWS Lambda, you don't have to worry about the operational overhead of setting up and maintaining a server to run the data transformation code. Overall, Option C provides a fully managed solution for real-time data ingestion with minimal operational overhead.
upvoted 2 times
Option A is incorrect because it involves deploying an EC2 instance to host an API, which adds operational overhead in the form of maintaining and securing the instance. Option B is incorrect because it involves deploying an EC2 instance to host an API and disabling source/destination checking on the instance. Disabling source/destination checking can make the instance vulnerable to attacks, which adds operational overhead in the form of securing the instance.
upvoted 2 times
Option D is incorrect because it involves using AWS Glue to send the data to Amazon S3, which adds operational overhead in the form of maintaining and securing the AWS Glue infrastructure. Overall, Option C is the best choice because it uses fully managed services for the API, data transformation, and data delivery, which minimizes operational overhead.
upvoted 2 times
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career360guru
2 years ago
Selected Answer: C
Option C
upvoted 1 times
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career360guru
2 years ago
Selected Answer: C
Option C
upvoted 1 times
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