DynamoDB Streams enable __________ processing of data changes in DynamoDB tables.
- Batch
- Delayed
- Periodic
- Real-time
DynamoDB Streams enable real-time processing of data changes in DynamoDB tables, allowing immediate and continuous data handling.
To consume DynamoDB Streams in real-time, you can use services like __________ or AWS Lambda.
- AWS EC2
- AWS S3
- Amazon Kinesis
- Amazon Redshift
Amazon Kinesis can consume DynamoDB Streams in real-time, providing a way to process and analyze streaming data.
__________ is a mechanism provided by DynamoDB Streams to ensure that each shards data is processed in the correct order.
- Partition keys
- Sequence numbers
- Shard iterators
- Stream records
Sequence numbers in DynamoDB Streams ensure that records within a shard are processed in the correct order, maintaining data consistency.
DynamoDB Streams provide an at-least-once __________ of stream records, ensuring durability and data consistency.
- Delivery
- Execution
- Processing
- Retransmission
DynamoDB Streams ensure at-least-once delivery of stream records, meaning each record is delivered to the consumer at least once, ensuring durability and data consistency.
Scenario: You are designing an application where you need to perform real-time analytics on data changes in a DynamoDB table. How would you implement this using DynamoDB Streams and AWS Lambda?
- Create a Lambda function triggered by DynamoDB Streams
- Directly query the DynamoDB table for changes
- Schedule periodic batch jobs with Lambda
- Use AWS Glue for ETL jobs
Creating a Lambda function triggered by DynamoDB Streams allows you to process changes in real time, enabling real-time analytics.
Scenario: Your team is building a system where data integrity is crucial, and you're considering using DynamoDB Streams for change tracking. What are some considerations you need to keep in mind regarding data consistency and reliability?
- Ensure idempotency in Lambda functions
- Ignore duplicate records
- Rely on DynamoDB's default retry behavior
- Use eventual consistency for all operations
Ensuring idempotency in Lambda functions is crucial to maintain data integrity and reliability when using DynamoDB Streams for change tracking.
How do custom event sources differ from standard event sources in AWS Lambda?
- Customizability
- Built-in compatibility
- Scalability
- Performance
Custom event sources offer more flexibility and customization options compared to standard event sources, allowing developers to define their own event formats and sources.
What is the significance of integrating custom event sources with AWS Lambda?
- Cost reduction
- Extensibility
- Latency reduction
- Security enhancement
Integrating custom event sources with AWS Lambda extends the capabilities of Lambda functions, allowing them to respond to a wider range of events from external sources.
What are some examples of custom event sources that can trigger AWS Lambda functions?
- AWS Step Functions, AWS Glue, AWS CodePipeline
- Amazon API Gateway, Amazon CloudFront, Amazon S3
- Amazon EC2, Amazon RDS, Amazon DynamoDB
- Amazon SQS, Amazon SNS, Amazon Kinesis
Custom event sources for AWS Lambda include services like Amazon SQS, Amazon SNS, and Amazon Kinesis, allowing you to trigger functions in response to messages, notifications, and streaming data.
What are the advantages of using custom event sources for AWS Lambda over traditional event sources?
- Built-in integration
- Flexibility and extensibility
- Higher reliability
- Lower latency
The advantages of using custom event sources for AWS Lambda over traditional event sources include flexibility and extensibility, allowing you to integrate with a wide range of services and systems beyond those natively supported by AWS Lambda.