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Platforms in AWS Elastic Beanstalk determine an application's underlying infrastructure, including operating system, webserver, and runtime. Furthermore, developers can choose from a wide range of platforms, such as Go, PHP, Python, Ruby, Node.js, Java, and .NET. Users can also create customized pl…

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AWS Certified Solutions Architect - Platform Example Questions

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Question 1

A company runs a web application on a single Amazon EC2 instance that reads from an Amazon DynamoDB table. During peak hours, users report high latency. CloudWatch shows low EC2 CPU utilization, but DynamoDB ReadLatency and ReadThrottleEvents increase significantly. The workload is read-heavy with repeated reads of hot items, and the application can tolerate eventually consistent reads. Which action will most effectively reduce end-to-end request latency with minimal operational overhead?

Correct Answer: Enable DynamoDB Accelerator (DAX)

DynamoDB Accelerator (DAX) is a fully managed, in-memory cache that sits in front of DynamoDB and can reduce read latencies from milliseconds to microseconds for read-heavy, eventually consistent workloads. By caching hot items, DAX lowers DynamoDB read pressure, reduces throttling, and improves end-to-end response times during peak periods. Increasing the EC2 instance size does not address a database-side latency bottleneck, and adding a load balancer to a single instance does not reduce DynamoDB latency and can add overhead. S3 Transfer Acceleration is unrelated to DynamoDB or EC2 application latency.

Question 2

Your company is deploying a multi-tier web application that requires a managed relational database. The database layer must be highly available and fault-tolerant within a single AWS Region, with automatic failover across Availability Zones and no application changes during failover. Which AWS service configuration best meets these requirements?

Correct Answer: Amazon RDS with Multi-AZ Deployment

Amazon RDS with Multi-AZ Deployment provides high availability and fault tolerance for relational databases by synchronously replicating data to a standby instance in a different Availability Zone and performing automatic failover if the primary instance becomes unavailable. The database endpoint remains the same, minimizing application impact during failover. In contrast, RDS Read Replicas use asynchronous replication intended for read scaling and require manual promotion with potential data loss; DynamoDB is a NoSQL service and not a relational database; and RDS in a single Availability Zone lacks multi-AZ redundancy and automatic failover.

Question 3

You need to analyze log data and generate reports in near real-time based on specific keywords for a web-based application. Which combination of AWS services can be used to fulfill these requirements?

Correct Answer: AWS Kinesis Data Firehose and Amazon Elasticsearch

Using AWS Kinesis Data Firehose can help stream log data, and Amazon Elasticsearch will enable near real-time data analysis with specific keywords. EMR and S3 are not built for near real-time analysis. Elastic Beanstalk and RDS are for deploying applications and relational databases. SQS and Redshift do not help with near real-time analysis. AWS Batch and EFS handle batch processing and shared storage. Glue and DynamoDB are not suitable for real-time log data analysis.

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