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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 107 discussion

A bicycle sharing company is developing a multi-tier architecture to track the location of its bicycles during peak operating hours. The company wants to use these data points in its existing analytics platform. A solutions architect must determine the most viable multi-tier option to support this architecture. The data points must be accessible from the REST API.
Which action meets these requirements for storing and retrieving location data?

  • A. Use Amazon Athena with Amazon S3.
  • B. Use Amazon API Gateway with AWS Lambda.
  • C. Use Amazon QuickSight with Amazon Redshift.
  • D. Use Amazon API Gateway with Amazon Kinesis Data Analytics.
Show Suggested Answer Hide Answer
Suggested Answer: D 🗳️

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ArielSchivo
Highly Voted 2 years, 1 month ago
Selected Answer: B
API Gateway is needed to get the data so option A and C are out. “The company wants to use these data points in its existing analytics platform” so there is no need to add Kynesis. Option D is also out. This leaves us with option B as the correct one.
upvoted 97 times
MutiverseAgent
1 year, 4 months ago
B might work but D works better. B requieres API gateway + lambda for data input & output, whereas D is a broader solution, as Kinesis Data Analytics APIs can be used to extract and process data better that API Gateway + Lambdas. Also, Kinesis is highly recommended for telemetry data which is the question scenario. @See Kinesys flexible API (https://aws.amazon.com/documentation-overview/kinesis-data-analytics/)
upvoted 7 times
MutiverseAgent
1 year, 4 months ago
Also by using kinesis the analytics platform will have a storing buffer to take & process data through the kinesys API. The lambda aproach in the B scenario is to wide and leaves many loose ends.
upvoted 3 times
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Tsige
1 month ago
While API Gateway and Lambda can work together for processing requests, this setup doesn't efficiently handle continuous real-time data streaming and analysis, which is required for tracking the bicycle locations. Lambda is stateless and is better suited for on-demand execution, not for real-time analytics of streaming data. So, the correct option is D
upvoted 4 times
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bullrem
1 year, 10 months ago
AWS Lambda is a serverless compute service that can be used to run code in response to specific events, such as changes to data in an Amazon S3 bucket or updates to a DynamoDB table. It could be used to process the location data, but it doesn't provide storage solution. Therefore, it would not be the best option for storing and retrieving location data in this scenario.
upvoted 12 times
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alfonso_ciampa
1 year, 4 months ago
You are right, but it clearly say "store data". AWS Lambda don't store data, Kinesis could.
upvoted 7 times
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Six_Fingered_Jose
Highly Voted 2 years ago
Selected Answer: D
I dont understand why you will vote B? how are you going to store data with just lambda? > Which action meets these requirements for storing and retrieving location data In this use case there will obviously be a ton of data and you want to get real-time location data of the bicycles, and to analyze all these info kinesis is the one that makes most sense here.
upvoted 71 times
a070112
1 year, 11 months ago
Lambda isn't storing the data themselves. It's triggering the data store to the company's "existing data analytics platform"
upvoted 9 times
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kmliuy73
1 year, 11 months ago
Real-time analytics on Kinesis Data Streams & Firehose using SQL, not store db ...
upvoted 4 times
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Six_Fingered_Jose
2 years ago
https://aws.amazon.com/blogs/aws/real-time-hotspot-detection-in-amazon-kinesis-analytics/
upvoted 5 times
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UWSFish
2 years ago
I don't think you need to worry about storing data. The question states their is an existing platform.
upvoted 4 times
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jayessh
Most Recent 1 week, 2 days ago
Selected Answer: B
According to copilot: Initial setup & scaling ability of lambda is way better than kinesis. Also for storing data points we need DB or any other solution in both cases, which should not be point for considering answer here
upvoted 1 times
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Sergantus
3 weeks, 1 day ago
Selected Answer: D
API Gateway is definitely needed, so A and C are out, I would agree with B is there was SQS in the picture, as Lambda may not be able to work with a large volume of continuous location data.
upvoted 3 times
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Mish
4 weeks, 1 day ago
D. Use Amazon API Gateway with Amazon Kinesis Data Analytics.
upvoted 1 times
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Omariox
1 month, 3 weeks ago
Selected Answer: D
it should be D because ChatGPT said that :D
upvoted 2 times
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PaPi_z
1 month, 3 weeks ago
Selected Answer: D
The most viable option for storing and retrieving location data in a multi-tier architecture with the requirements mentioned is D. Use Amazon API Gateway with Amazon Kinesis Data Analytics. Here's why: Amazon API Gateway: It provides a managed solution for exposing a REST API, which is needed for making the location data accessible to external clients and applications. Amazon Kinesis Data Analytics: This service is designed to handle real-time data streams and analytics, which is ideal for tracking the location of bicycles during peak operating hours when real-time data processing is essential. Kinesis Data Analytics can efficiently process, analyze, and store the location data from bicycles, making it a good fit for real-time tracking scenarios. This solution supports the real-time ingestion of location data and enables integration with the company's existing analytics platform for further processing, while also providing access to the data via REST APIs.
upvoted 3 times
PaPi_z
1 month, 3 weeks ago
continues here... Why the other options are less viable: A. Use Amazon Athena with Amazon S3: While Athena is great for querying large datasets stored in S3, it is not suitable for real-time data processing and tracking since it is more focused on batch querying rather than continuously ingesting and processing live data streams. B. Use Amazon API Gateway with AWS Lambda: While this combination is useful for building scalable APIs, AWS Lambda is not designed for high-throughput real-time data processing or storage of continuous data streams. It would be complex and inefficient for storing and analyzing real-time location data from the bikes. C. Use Amazon QuickSight with Amazon Redshift: QuickSight is primarily a data visualization tool, and Redshift is used for data warehousing and batch processing. This combination is not suitable for handling real-time streaming data and making it accessible via a REST API.
upvoted 2 times
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PaulGa
2 months ago
Selected Answer: D
Ans D - hint: "The data points must be accessible from the REST API" so we need an API interface - that's leaves only B or D, of which B uses a Lambda function (undefined) and D provides Kinesis data analytics
upvoted 3 times
tomasiraz
1 month, 3 weeks ago
Kinesis data analytics cant consume from API Gateway, only from Kinesis Data Stream or Amazon Data Firehose https://docs.aws.amazon.com/es_es/kinesisanalytics/latest/dev/what-is.html
upvoted 3 times
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SaurabhTiwari1
2 months, 3 weeks ago
Selected Answer: B
B seems right, because it has already existing analytics plateform so don't need D.
upvoted 1 times
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rpmaws
2 months, 3 weeks ago
Selected Answer: D
In option B who will ingest realtime data in S3 ? so Answer is D.
upvoted 1 times
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bignatov
2 months, 4 weeks ago
Selected Answer: D
RDS Event Notification: Amazon RDS supports event notifications, which can trigger actions when specific events occur, such as a record update or delete operation. In this case, an event would be triggered when a listing is removed. Amazon SNS: SNS allows the event to be published to a topic that can then be fanned out to multiple SQS queues. This is useful when you have multiple target systems that need to receive the data. SNS can push the message to all subscribed SQS queues simultaneously. Amazon SQS: SQS provides reliable message queuing. Each target system can consume messages from its respective SQS queue at its own pace, ensuring that no messages are lost. AWS Lambda: Lambda functions can be triggered by the SQS queues to process the messages and update the target systems accordingly. This approach allows for asynchronous processing and decouples the RDS update from the target system updates, improving scalability and reliability.
upvoted 3 times
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knben
3 months, 2 weeks ago
Selected Answer: D
D is the correct answer!
upvoted 2 times
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KTEgghead
3 months, 3 weeks ago
Selected Answer: B
To meet the requirements for storing and retrieving location data in a multi-tier architecture with accessibility from a REST API, the most viable option would be to use Amazon API Gateway with AWS Lambda. This combination allows for the creation of a serverless architecture that can handle the data points effectively: Amazon API Gateway: Acts as the front door for the REST API, managing and securing the traffic to the back-end services. AWS Lambda: Processes the incoming requests from the API Gateway, performs operations such as storing and retrieving location data, and integrates with other AWS services as needed. This setup enables the bicycle sharing company to have a scalable, cost-effective, and efficient system for tracking the location of its bicycles and integrating the data with its existing analytics platform.
upvoted 1 times
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jaradat02
4 months ago
Selected Answer: B
All of these options are a little bit vague, we can rule out A and C because they don't provide a solution for the API requirement, since the company has it's own analytics platform, we can rule out D, although option B doesn't provide a storage solution, it's the one that makes the most sense.
upvoted 1 times
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jatric
4 months, 2 weeks ago
Selected Answer: A
Option A makes more sense as this provide both storing option as S3 and rest endpoint in Athena to retrieve data points integrating with S3
upvoted 1 times
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ChymKuBoy
5 months ago
Selected Answer: B
B for sure
upvoted 1 times
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JunsK1e
5 months ago
Selected Answer: D
you can't store data in lambda
upvoted 2 times
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Community vote distribution
A (35%)
C (25%)
B (20%)
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