AWS Certified Solutions Architect Associate SAA-C03 Practice Question
A company is building a centralized logging solution that will aggregate logs from various microservices. Each microservice will publish log messages to a central system, which will then store the logs for analysis and monitoring purposes. Given the need for high throughput and the ability to handle spikes in log data volume without losing messages, which service should the Architect recommend for collecting log data?
Amazon Glacier
Amazon Simple Queue Service (SQS)
Amazon Kinesis Data Firehose
Amazon Relational Database Service (RDS) Read Replicas
The correct answer is Amazon Kinesis Data Firehose because it is designed for reliably loading streaming data into data lakes, data stores, and analytics tools. It can handle high-volume and high-throughput data with ease, making it ideal for aggregating logs from multiple sources without data loss during volume spikes. Amazon Kinesis Data Firehose can scale automatically to accommodate the data throughput and volume, ensuring that log data is captured and stored reliably. The incorrect options are either not primarily designed for handling streaming data (RDS), lack the same scalability and automatic throughput handling (SQS), or are not services (Amazon Glacier is a storage solution and does not support data streaming).
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What is Amazon Kinesis Data Firehose?
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Why shouldn't I use Amazon SQS for this logging solution?