Exam AWS Certified Solutions Architect - Associate SAA-C03 topic 1 question 107 discussion

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.

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.

A common use is the real-time aggregation of data followed by loading the aggregate data into a data warehouse or map-reduce cluster. https://docs.aws.amazon.com/streams/latest/dev/introduction.html#using-the-service

D is the most viable multi-tier option, as it supports real-time data ingestion, analytics, and accessibility through a REST API.

kinesis more complex than lambda

The company needs to track bicycle locations during peak operating hours and make this data accessible via a REST API. The data will be part of an analytics platform, so the solution should support real-time data processing, storage, and easy retrieval. Amazon API Gateway: This can be used to create a REST API to receive and expose the location data of the bicycles. Amazon Kinesis Data Analytics: This service is specifically designed to process real-time streaming data, such as location data points sent from the bicycles. It enables real-time analytics and can seamlessly integrate with other services like Amazon S3, DynamoDB, or Amazon Redshift, which may be used for further storage or analysis.

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

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.

D. Use Amazon API Gateway with Amazon Kinesis Data Analytics.

it should be D because ChatGPT said that :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.

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

B seems right, because it has already existing analytics plateform so don't need D.

In option B who will ingest realtime data in S3 ? so Answer is 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.

D is the correct answer!

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.