Examkin

Question

Difficulty: MediumServerless and Automated Scaling Architectures for Cost Efficiency

A smart agriculture company collects telemetry data from thousands of soil sensors. The sensors upload data hourly, but during storm events, they transmit readings every minute, causing sudden traffic spikes. To prevent old sensor readings from overwriting newer updates, the telemetry data must be processed in the exact order it was captured. Additionally, a complex analytics job needs to process historical data once a day, taking approximately 30 minutes to complete. The company wants a serverless, cost-effective solution with no idle resource costs.

Which combination of services should a solutions architect recommend to meet these requirements? (Select TWO.)

  1. Configure an Amazon SQS FIFO queue to buffer the telemetry data and trigger an AWS Lambda function for processing.Answer
  2. Use Amazon EventBridge to schedule an AWS Fargate task to run the daily analytics job.Answer
  3. C
    Configure an Amazon SQS standard queue to buffer the telemetry data and trigger an AWS Lambda function for processing.
  4. D
    Configure an AWS Lambda function to run the daily analytics job once per day.
  5. E
    Provision an Amazon DynamoDB table in provisioned capacity mode sized for peak storm traffic to store the telemetry data.

Answer

The correct combination of services is configuring an Amazon SQS FIFO queue to buffer telemetry data and triggering an AWS Lambda function for processing, along with using Amazon EventBridge to schedule an AWS Fargate task to run the daily analytics job.
The correct solution uses an Amazon SQS FIFO queue to ensure telemetry data is processed in the exact chronological order it was received, coupled with AWS Lambda to handle unpredictable incoming spikes serverlessly. For the daily analytics job, AWS Fargate is scheduled using Amazon EventBridge. Because the job runs for 30 minutes, it exceeds AWS Lambda's 15-minute timeout constraint. AWS Fargate is serverless, charges only for the duration of the execution, and avoids any idle server costs.

Step-by-Step Solution

1
Evaluate the telemetry ingestion requirements.
Identify that the system needs to handle highly variable traffic spikes cost-effectively while preserving strict message ordering.
Amazon SQS FIFO queues guarantee first-in, first-out delivery, and AWS Lambda provides automatic scaling with a pay-per-use model that scales down to zero when idle.
2
Evaluate the daily analytics job requirements.
Identify that the analytics job takes 30 minutes, which exceeds AWS Lambda's 15-minute execution limit.
AWS Fargate runs containerized workloads serverlessly without execution timeout limits, billing only for the resources consumed during the 30-minute run.

Key Concept

Selecting serverless services based on execution limits (AWS Fargate for >15 minute jobs) and ordering requirements (Amazon SQS FIFO queues) to design cost-efficient architectures that scale to zero.
Rate this question

Topics

Serverless and Automated Scaling Architectures for Cost Efficiency