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Transactions

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Amazon DynamoDB supports transactions, which enable you to perform multiple create, update, or delete operations in a single request. DynamoDB transactions provide the following guarantees: all-or-nothing (all operations within a transaction succeed or fail as a group), isolation (no other requests…

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AWS Certified Solutions Architect - Transactions Example Questions

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Question 1

A company needs automatic failover for a managed relational database engine such as MySQL or SQL Server using a Multi-AZ deployment (non-Aurora). Which AWS service should they choose?

Correct Answer: Amazon RDS

Amazon RDS provides Multi-AZ deployments for non-Aurora engines (such as MySQL, PostgreSQL, MariaDB, Oracle, and SQL Server) with synchronous replication to a standby in a different Availability Zone and automatic failover if the primary instance becomes unavailable. Amazon Aurora is a separate service with its own high-availability model, while Amazon ElastiCache is for in-memory caching and Amazon Redshift is a data warehouse, neither of which is used for a transactional SQL database with RDS-style Multi-AZ failover.

Question 2

An online shopping platform requires transaction support for multiple items being purchased at once. Which AWS service should be used to ensure transactional support for multi-item orders?

Correct Answer: Amazon DynamoDB with AWS Lambda

Amazon DynamoDB with AWS Lambda allows for multiple-item transactions to be processed and ensures transactional support. The other options do not provide the transactional support required for multi-item purchases.

Question 3

A company runs a financial application that processes transactions. During peak hours, the application's capacity to handle transactions is exceeded, causing some transactions to fail. What is the appropriate solution?

Correct Answer: Use Amazon SQS to decouple the application and store transactions temporarily.

By using Amazon SQS, the application can store transactions temporarily, which can then be processed by the application during non-peak hours, avoiding failure due to capacity constraints. The other options do not address the capacity limitation during peak hours.

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