DynamoDB Streams Interview Questions and Answers for 5 years experience

1. What are DynamoDB Streams?

   • Answer: DynamoDB Streams are a feature that captures a stream of changes to your DynamoDB tables. These changes include additions, modifications, and deletions of items. They provide a near real-time feed of data modifications, allowing you to build applications that react to these changes immediately or asynchronously.

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

   • Answer: DynamoDB offers two stream types: NEW_IMAGE and OLD_IMAGE. NEW_IMAGE contains only the new item after a modification or the entire item for inserts. OLD_IMAGE contains the item before a modification or deletion. You can also enable both NEW_and OLD_IMAGE or just one depending on your application needs. There is also a third option, KEYS_ONLY, which only includes the primary key of the modified item.

3. Explain the concept of shards in DynamoDB Streams.

   • Answer: DynamoDB Streams are partitioned into shards. Each shard represents a segment of the stream, and data is distributed across these shards. The number of shards is determined during stream creation and is based on the write throughput capacity of the DynamoDB table. Sharding ensures scalability and parallel processing of stream events.

4. How do you choose the appropriate shard count for your DynamoDB Stream?

   • Answer: The optimal shard count depends on your write throughput. AWS recommends starting with a shard count that matches your table's write capacity units (WCUs). If you anticipate high write throughput, it's better to start with more shards to avoid throttling and ensure even distribution of events. Too few shards can lead to bottlenecks, while too many can be inefficient. You can adjust the shard count when needed, but it's a costly operation.

5. What are the limitations of DynamoDB Streams?

   • Answer: DynamoDB Streams have several limitations, including a 24-hour retention period for stream data (unless you use Kinesis Data Firehose or another mechanism for long-term storage), a maximum of 1000 shards per table, and the fact that they are append-only – you cannot modify or delete individual events. There's also a limit on the size of individual items in the stream.

6. How can you consume DynamoDB Streams using Lambda?

   • Answer: AWS Lambda can be configured as a trigger for DynamoDB Streams. When a new event occurs in the stream, Lambda automatically invokes a corresponding function to process the data. This allows you to handle stream events in a serverless, scalable manner.

7. Describe how to use DynamoDB Streams with Kinesis Data Firehose.

   • Answer: Kinesis Data Firehose can be used to ingest data from DynamoDB Streams into various destinations like S3, Redshift, or Elasticsearch. This provides a mechanism for long-term storage, analysis, and further processing of your DynamoDB stream data beyond the 24-hour retention limit.

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

   • Answer: Each record in a DynamoDB Stream has a unique sequence number. This number provides an ordering within the stream and helps in ensuring that events are processed in the correct order, even if they are consumed from multiple shards concurrently.

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

   • Answer: Error handling is crucial when consuming DynamoDB Streams. Implement retry mechanisms in your Lambda functions or other consumers to handle transient failures. Use dead-letter queues (DLQs) to capture messages that consistently fail to be processed, allowing for later investigation and remediation. Consider idempotency in your processing logic to handle duplicate events.

10. What are the best practices for designing DynamoDB Streams applications?

    • Answer: Best practices include: choosing the appropriate stream type based on your needs, selecting an appropriate shard count, utilizing efficient data processing mechanisms (Lambda, Kinesis Firehose), implementing robust error handling, designing for idempotency, and considering the eventual consistency of DynamoDB.

11. How does DynamoDB Streams handle eventual consistency?

    • Answer: DynamoDB is eventually consistent. This means that data written to a DynamoDB table may not be immediately visible in the stream. There's a short delay between a write operation and the corresponding event appearing in the stream. Your applications must be designed to handle this eventual consistency.

12. Explain the differences between DynamoDB Streams and DynamoDB Global Tables.

    • Answer: DynamoDB Streams capture changes within a single table, providing a history of modifications. DynamoDB Global Tables provide low-latency read and write access to multiple tables across different AWS regions. They are distinct features serving different purposes. Streams are for change data capture and real-time processing, while Global Tables focus on data replication and global availability.

13. How can you optimize the performance of DynamoDB Stream consumption?

    • Answer: Optimizations include using parallel processing (multiple Lambda functions consuming different shards), efficiently handling large items (avoiding unnecessary data transfer), optimizing your consumer function's code for speed and efficiency, and using appropriate buffering strategies.

14. Describe a scenario where you would use DynamoDB Streams.

    • Answer: Scenarios include building audit trails, implementing real-time data synchronization between systems, creating reactive applications that respond to data changes in DynamoDB (e.g., updating a search index, triggering notifications), and building data pipelines for analytics and reporting.

15. How do you monitor DynamoDB Streams?

    • Answer: You can monitor DynamoDB Streams using CloudWatch metrics. These metrics track shard consumption, error rates, and throughput. You can set up alarms to notify you of potential issues, ensuring your applications are running smoothly.

16. What are the pricing considerations for DynamoDB Streams?

    • Answer: You are charged for the consumed read capacity units when you read from the stream. There are no charges for writing to the stream. The pricing is based on the amount of data read and the number of requests made. The retention period also indirectly influences cost (longer retention means more storage costs).

17. How do you handle idempotency when processing DynamoDB stream events?

    • Answer: Idempotency ensures that processing the same event multiple times has the same effect as processing it only once. Techniques include using a unique identifier for each event (like the sequence number), storing a record of processed events, and designing your downstream systems to be idempotent.

18. Explain the concept of DynamoDB Streams and its relation to eventual consistency.

    • Answer: DynamoDB Streams provide a feed of changes to a DynamoDB table. However, because DynamoDB is eventually consistent, there's a delay between a write operation and its appearance in the stream. Applications consuming the stream must account for this eventual consistency and handle potential delays or out-of-order events.

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