Domain 2.4: Reliability Requirements

A company is designing an event-driven architecture. An Amazon API Gateway receives orders and triggers an AWS Lambda function. The Lambda function processes the order and sends a message to an Amazon SQS queue. A backend fleet of EC2 instances polls the queue. During peak times, the API receives thousands of requests per second, causing the Lambda function to hit concurrency limits and drop orders. How can the architect redesign the system to ensure NO orders are lost during traffic spikes?

A retail company is designing a serverless order processing system. Orders are received via API Gateway and placed into an SQS queue. A Lambda function processes the orders and updates a DynamoDB table. During flash sales, the SQS queue receives millions of messages, causing the Lambda function to scale rapidly and exhaust the DynamoDB write capacity, leading to throttled requests and failed orders. Which combination of actions should the architect take to improve reliability? (Select TWO)

A company is building a serverless application using AWS Step Functions to orchestrate a complex workflow. One of the steps involves calling an external third-party API that is known to be unreliable and frequently times out. The workflow must not fail immediately; it should retry the API call up to 5 times, waiting longer between each attempt. How should the architect implement this?

A popular news website experiences massive, unpredictable spikes in traffic during breaking news events. The site is hosted on EC2 instances behind an ALB, with an Amazon RDS database. During spikes, the database is overwhelmed by read requests for the same articles, causing the site to crash. What is the MOST effective architectural change to improve reliability?

A data engineering team is building a data pipeline. Data is uploaded to Amazon S3, which triggers an AWS Lambda function. The Lambda function transforms the data and loads it into Amazon Redshift. The team notices that during large data uploads, the Lambda function times out, and data is lost. Which combination of architectural changes will make the pipeline more resilient and scalable? (Select TWO)