DynamoDB Streams Interview Questions and Answers for internship

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DynamoDB Streams Interview Questions

  1. What are DynamoDB Streams?

    • Answer: DynamoDB Streams are a feature that captures a continuous, immutable stream of changes in your DynamoDB tables. These changes include CREATE, UPDATE, and DELETE operations. This allows you to build applications that react to changes in your data in real-time or near real-time.

  2. What are the different stream view types in DynamoDB Streams?

    • Answer: DynamoDB Streams offer two view types: `NEW_IMAGE` and `OLD_IMAGE`. `NEW_IMAGE` contains the new item after a modification or the item itself after a creation. `OLD_IMAGE` contains the item before it was modified or deleted. `NEW_AND_OLD_IMAGES` provides both.

  3. What is the purpose of `NEW_IMAGE` and `OLD_IMAGE` in DynamoDB Streams?

    • Answer: `NEW_IMAGE` shows the state of the item *after* the operation (creation, update, or even after a successful delete if configured). `OLD_IMAGE` shows the state of the item *before* the operation. This allows applications to track changes and perform actions based on the previous and current states.

  4. How do DynamoDB Streams handle deletes?

    • Answer: When an item is deleted, DynamoDB Streams capture this event. The `OLD_IMAGE` will contain the item's data before deletion. The `NEW_IMAGE` might be empty or contain minimal data depending on the stream configuration.

  5. What are the limitations of DynamoDB Streams?

    • Answer: DynamoDB Streams have limitations on retention period (up to 24 hours or 7 days depending on configuration), throughput limitations (related to the write capacity of the table), and the size of individual records (limited to 4 MB).

  6. Explain the concept of shards in DynamoDB Streams.

    • Answer: DynamoDB Streams are partitioned into shards. Each shard represents a segment of the stream's data. Shards are automatically managed by DynamoDB to handle the throughput of the stream. Consumers read data from specific shards.

  7. How do you consume data from DynamoDB Streams?

    • Answer: You can consume data from DynamoDB Streams using AWS Lambda, Kinesis Data Analytics, or other services that can integrate with Kinesis Data Streams (as DynamoDB Streams are essentially Kinesis Data Streams).

  8. What is the role of AWS Lambda in processing DynamoDB Streams?

    • Answer: AWS Lambda can be configured as a consumer of DynamoDB Streams. Each stream record triggers an invocation of your Lambda function, allowing you to process each change event individually and in real-time.

  9. How do you handle errors when consuming DynamoDB Streams?

    • Answer: Implement robust error handling in your Lambda function or other consumer. Use retry mechanisms to process failed records. Implement dead-letter queues to store records that consistently fail to process. Proper logging is crucial for debugging.

  10. Explain the concept of stream archival.

    • Answer: Stream archival allows you to retain stream data beyond the default retention period. This is useful for auditing or long-term analysis of data changes. The archived data is stored in S3.

  11. How can you optimize the performance of DynamoDB Streams?

    • Answer: Optimize by using appropriate stream view types (`NEW_IMAGE` if you only need the new data), efficient consumer processing (avoid long-running tasks within your Lambda), and proper shard management (ensure sufficient capacity to handle throughput).

  12. Describe the cost associated with DynamoDB Streams.

    • Answer: Costs are associated with the consumed read capacity units (RCUs) of the stream and any storage used for archival in S3. There are no charges for the stream itself, only for accessing and storing the data.

  13. How does DynamoDB Streams relate to DynamoDB Global Tables?

    • Answer: DynamoDB Streams can be used with Global Tables, but you need to configure streams on each regional table separately. Changes in one region will be captured by that region's stream, and you can use a consumer to replicate the changes to other regions if needed.

  14. Can you use DynamoDB Streams with DynamoDB Accelerator (DAX)?

    • Answer: No, DAX does not directly integrate with DynamoDB Streams. Changes made via DAX are still reflected in the underlying DynamoDB table, and those changes will trigger events in the DynamoDB Streams.

  15. What are some use cases for DynamoDB Streams?

    • Answer: Use cases include audit logging, change data capture (CDC), real-time data synchronization, building reactive applications (e.g., updating a dashboard based on data changes), and powering event-driven architectures.

  16. How do you manage the throughput of DynamoDB Streams?

    • Answer: Throughput is managed implicitly by DynamoDB based on the write capacity of the underlying table. Ensure sufficient write capacity to accommodate the rate of changes in your table. Monitor the stream's metrics to identify potential throughput bottlenecks.

  17. What security considerations should be addressed when using DynamoDB Streams?

    • Answer: Secure your Lambda function or other consumer with appropriate IAM roles, limiting permissions to only access the necessary resources. Consider encryption of data at rest (in S3 if archival is used) and in transit.

  18. How do you handle large records in DynamoDB Streams?

    • Answer: DynamoDB limits record size. For large records, consider breaking them down into smaller, manageable units before inserting into DynamoDB. This also improves performance and simplifies processing.

  19. Explain the concept of sequence numbers in DynamoDB Streams.

    • Answer: Each record in a DynamoDB stream has a sequence number. This number is unique within a shard and provides a way to order events and ensure that records are processed in the correct order. It's crucial for maintaining data consistency.

  20. How can you monitor the health and performance of your DynamoDB Streams?

    • Answer: Use CloudWatch metrics to monitor key performance indicators such as record processing time, throughput, and errors. Set up alarms to notify you of potential issues.

  21. What are the best practices for designing DynamoDB tables for use with Streams?

    • Answer: Design tables with efficient data models to minimize write operations and therefore reduce stream load. Use appropriate data types to minimize storage costs. Plan for sufficient write capacity.

  22. How does DynamoDB Streams handle concurrent writes to the same item?

    • Answer: DynamoDB Streams records each write separately, regardless of concurrency. Each write will generate a distinct stream record.

  23. What is the difference between a DynamoDB Stream and a Kinesis Data Stream?

    • Answer: DynamoDB Streams are a specific type of Kinesis Data Stream tightly integrated with DynamoDB. Kinesis Data Streams are a more general-purpose service for processing streaming data from various sources.

  24. Can you use DynamoDB Streams with serverless technologies?

    • Answer: Yes, DynamoDB Streams are ideally suited for serverless architectures. They integrate seamlessly with AWS Lambda and other serverless components.

  25. How do you handle schema changes in DynamoDB when using Streams?

    • Answer: Your consumer application needs to be resilient to schema changes. Implement logic to handle missing attributes or changes in data types gracefully. Versioning your schema can help.

  26. Explain the concept of iterator types in DynamoDB Streams.

    • Answer: Iterators allow you to control how you read from the stream: `TRIM_HORIZON` starts from the beginning of the stream, `LATEST` starts from the most recent record, and `AT_SEQUENCE_NUMBER` starts at a specific sequence number.

  27. How can you test your DynamoDB Streams application?

    • Answer: Use local testing tools or set up a separate test environment. Use mocked data to simulate stream events. Monitor CloudWatch logs and metrics to verify functionality.

  28. What are some common pitfalls to avoid when working with DynamoDB Streams?

    • Answer: Ignoring error handling, insufficient throughput planning, not using appropriate iterator types, not considering schema changes, and neglecting security best practices.

  29. How does DynamoDB Streams handle the consistency of data?

    • Answer: DynamoDB Streams offers eventual consistency. There might be a slight delay between a change in the table and the appearance of the corresponding record in the stream.

  30. Explain the role of IAM permissions when using DynamoDB Streams.

    • Answer: Appropriate IAM roles need to be assigned to your Lambda function or consumer to allow it to read from the stream. Principle of least privilege should be applied.

  31. How can you improve the scalability of your DynamoDB Streams application?

    • Answer: Use parallel processing with multiple Lambda functions or consumers, each handling a subset of the stream shards. Implement auto-scaling for your consumers to handle fluctuations in throughput.

  32. What are some tools or services you can use to monitor DynamoDB Streams?

    • Answer: CloudWatch, X-Ray, and various third-party monitoring tools.

  33. How do you handle idempotency when processing DynamoDB Stream records?

    • Answer: Implement idempotency in your consumer to handle duplicate processing of the same record. Use sequence numbers or other unique identifiers to track processed records.

  34. What is the impact of increasing the write capacity of the DynamoDB table on the Streams?

    • Answer: Increasing write capacity allows for a higher rate of data changes, which directly impacts the stream's throughput. More changes mean a higher volume of records in the stream.

  35. How can you optimize the Lambda function for processing DynamoDB Stream records?

    • Answer: Optimize Lambda function code for efficiency, handle errors gracefully, use batch processing (when appropriate), and consider using provisioned concurrency to reduce cold starts.

  36. Describe the process of setting up DynamoDB Streams for a new table.

    • Answer: Enable streams on the table during creation or modification. Choose the desired stream view type (e.g., `NEW_IMAGE`, `OLD_IMAGE`, or `NEW_AND_OLD_IMAGES`). Specify a retention period.

  37. How can you troubleshoot issues with DynamoDB Stream consumption?

    • Answer: Check CloudWatch logs for errors, review IAM permissions, monitor stream throughput and latency, investigate consumer code for bugs, and check for any configuration errors.

  38. What are some alternative approaches to using DynamoDB Streams for real-time data processing?

    • Answer: Kinesis Data Streams (more general purpose), AWS AppSync with real-time subscriptions, and other message queues like SQS.

  39. How do you determine the appropriate shard count for a DynamoDB Stream?

    • Answer: DynamoDB automatically manages shards based on write capacity. Monitor metrics to see if you need to adjust the write capacity. Excessive shards can lead to unnecessary overhead.

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