Amazon DynamoDB Interview Questions and Answers for 5 years experience

1. What is Amazon DynamoDB and what are its core features?

   • Answer: Amazon DynamoDB is a fully managed, serverless NoSQL database service offered by Amazon Web Services (AWS). Its core features include: key-value and document data models, flexible schema, automatic scaling, high availability, low latency, and built-in security.

2. Explain the difference between key-value and document data models in DynamoDB.

   • Answer: The key-value model uses a simple primary key to access individual items. The document model uses a primary key but allows for more complex, JSON-like structures within each item. Key-value is ideal for simple data, while the document model is better for more structured data.

3. What are the different types of DynamoDB primary keys? Explain their use cases.

   • Answer: DynamoDB supports two types of primary keys: A simple primary key (partition key only) and a composite primary key (partition key and sort key). A simple primary key is suitable for scenarios where you don't need to sort items within a partition. A composite key is used when you need to efficiently query and retrieve items based on both the partition key and sort key.

4. Describe the concept of read and write capacity units (RCUs and WCUs) in DynamoDB.

   • Answer: RCUs and WCUs are units of measure for the throughput of your DynamoDB tables. RCUs represent the number of read operations you can perform per second, while WCUs represent the number of write operations. They are used to provision capacity and manage costs. You pay based on provisioned capacity.

5. Explain DynamoDB's auto-scaling capabilities. How do you configure them?

   • Answer: DynamoDB allows you to automatically scale your read and write capacity to handle fluctuating workloads. You can configure auto-scaling using the AWS Management Console, AWS CLI, or AWS SDKs. You specify target utilization metrics and DynamoDB will automatically adjust capacity based on these metrics.

6. How do you handle data consistency in DynamoDB?

   • Answer: DynamoDB offers different consistency models: strong consistency and eventual consistency. Strong consistency ensures that the data you read is the most recent write. Eventual consistency means there might be a slight delay before the data you read reflects the latest write. The choice depends on the application's requirements.

7. What are Global Secondary Indexes (GSIs) and Local Secondary Indexes (LSIs)? When would you use each?

   • Answer: GSIs provide a way to query data based on attributes other than the primary key. They can be defined on any attributes and have their own partition key and sort key. LSIs can only have the same partition key as the table but allow you to query based on a different sort key. GSIs are useful for complex queries on different attributes, while LSIs are optimized for filtering within a partition.

8. Explain the concept of DynamoDB streams. How are they used?

   • Answer: DynamoDB Streams capture a continuous stream of changes to your DynamoDB tables. You can use DynamoDB Streams to build applications that react to data changes in real-time, such as building audit trails or triggering Lambda functions.

9. How do you optimize DynamoDB queries for performance?

   • Answer: Optimization involves using appropriate primary keys, GSIs, and LSIs to efficiently target specific data. Filtering data at the query level, using projection expressions to fetch only necessary attributes, and ensuring efficient read and write capacity provisioning are also key strategies.

10. How do you handle data backups and recovery in DynamoDB?

    • Answer: DynamoDB automatically handles backups through point-in-time recovery (PITR). You can restore your table to a previous point in time using the AWS Management Console or AWS CLI. For more granular control, consider using DynamoDB Streams to replicate data to another region or service.

11. Describe your experience with DynamoDB transactions.

    • Answer: [Describe specific experiences using DynamoDB transactions, including details about using `TransactWriteItems` or `TransactGetItems` and addressing potential challenges like transaction limits and retry strategies. Be specific about the use case and success/challenges faced.]

12. Explain DynamoDB's security features.

    • Answer: DynamoDB integrates with IAM for access control, allowing granular permissions to be set. Encryption at rest and in transit is supported using various methods (like AWS KMS). VPC endpoints can be used to limit access to DynamoDB from within your VPC.

13. How do you monitor DynamoDB performance and identify bottlenecks?

    • Answer: DynamoDB provides CloudWatch metrics to monitor various aspects such as consumed capacity, throttled requests, and latency. These metrics can be used to identify bottlenecks and adjust capacity accordingly. AWS X-Ray can help trace requests through DynamoDB to pinpoint performance issues.

14. What are some common DynamoDB anti-patterns to avoid?

    • Answer: Some common anti-patterns include: using DynamoDB as a relational database, neglecting to use indexes effectively, over-provisioning or under-provisioning capacity, not utilizing DynamoDB Streams for auditing or event processing, and ignoring error handling and retry mechanisms.

15. How do you handle data modeling challenges in DynamoDB?

    • Answer: [Describe your approach to data modeling in DynamoDB. Discuss experiences with denormalization, designing for efficient queries, handling relationships between data items, and resolving schema evolution issues. Provide specific examples from past projects.]

16. Explain your experience with DynamoDB's capacity modes (on-demand vs. provisioned).

    • Answer: [Discuss your experience with both on-demand and provisioned capacity modes, highlighting the trade-offs between cost and performance. Mention specific use cases where each mode was preferred and why.]

17. Describe your experience using DynamoDB with other AWS services.

    • Answer: [Detail specific examples of integrating DynamoDB with services like Lambda, SQS, SNS, Kinesis, etc. Explain how the integration worked, the benefits achieved, and any challenges overcome.]

18. How would you design a DynamoDB schema for a specific application (e.g., e-commerce)?

    • Answer: [Provide a detailed schema design for a given application, explaining the choice of primary keys, GSIs/LSIs, data modeling strategies, and considerations for scalability and performance. Show understanding of tradeoffs.]

19. What are your preferred tools and techniques for troubleshooting DynamoDB issues?

    • Answer: [List your go-to tools like CloudWatch, AWS X-Ray, DynamoDB console logs, and any other relevant tools. Detail your typical troubleshooting process, from identifying symptoms to finding root causes and implementing solutions.]

20. How do you ensure data integrity in DynamoDB?

    • Answer: [Discuss strategies for data validation during both write and read operations. Describe how you implement data consistency checks, error handling, and potentially data versioning to ensure data accuracy and reliability.]

21. Describe a complex problem you solved using DynamoDB.

    • Answer: [Describe a specific challenging problem, the solution you implemented using DynamoDB, and the results achieved. Highlight your problem-solving skills and technical expertise.]

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