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.

lambda can store data in db which is not mentioned but can be implemented, wherein kinesis data analytics would be more complex to implement just for simple location tracking. Also, a data analytics tool is already there. Hence, B is more suitable.

Amazon Kinesis Data Analytics allows you to build more complex analytics applications that support flexible processing choices and robust fault-tolerance with exactly-once processing without duplicates, and analytics that can be performed over an entire data stream across multiple logical partitions. With KDA, you can analyze data over multiple types of aggregation windows (tumbling window, stagger window, sliding window, session window) using either the event time or the processing tim

Lambda is not most viable, or real time

Given that the company already has an existing analytics platform and needs a solution for storing and retrieving location data that can be accessed through a REST API, the best choice is: B. Use Amazon API Gateway with AWS Lambda

Kinesis is specifically designed for telemetry data, making it a better fit for tracking bicycle locations.

B. Amazon API Gateway com AWS Lambda: Essa combinação é útil para fornecer APIs REST, mas o Lambda não é otimizado para ingestão contínua de dados de localização em tempo real. Ele seria mais adequado para processos eventuais ou tarefas específicas.

the best answer is B: Use Amazon API Gateway with AWS Lambda Reasoning: API Gateway provides the required REST API endpoint Lambda can handle real-time processing of location data This combination is cost-effective and scalable Can easily integrate with other AWS services for analytics Provides the necessary multi-tier architecture (API Layer, Processing Layer, Storage Layer)

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