How long does DynamoDB Streams retain records by default?
- 24 hours
- 30 days
- 48 hours
- 7 days
DynamoDB Streams retains records for 24 hours by default.
SNS triggers can be used to invoke AWS Lambda functions based on incoming __________ messages.
- HTTP
- SMS
- SNS
- SQS
SNS messages are designed for notifications and can directly trigger AWS Lambda functions based on incoming messages.
AWS Lambda functions triggered by SNS messages can process the message payload and perform various __________ tasks.
- Data processing
- Hardware management
- Networking
- UI/UX design
AWS Lambda functions can process incoming SNS message payloads and perform various data processing tasks, such as parsing and transforming data.
SNS triggers enable __________ integration with AWS Lambda, allowing for real-time event-driven architectures.
- Direct linking
- Loose coupling
- Synchronous processing
- Tight coupling
Loose coupling refers to a design principle that enables components to interact with minimal dependencies, which is facilitated by SNS triggers with AWS Lambda.
Scenario: You are building a real-time notification system for a mobile app. Which AWS service would you use to send push notifications and trigger AWS Lambda functions to process them?
- AWS IoT
- Amazon SES
- Amazon SNS
- Amazon SQS
Amazon SNS can send push notifications to mobile devices and trigger AWS Lambda functions for processing them.
What is the purpose of a DynamoDB stream ARN (Amazon Resource Name)?
- Creating backup snapshots
- Granting IAM permissions
- Identifying a specific stream
- Monitoring stream activity
A DynamoDB stream ARN uniquely identifies a specific stream.
How can you ensure ordered processing of records in DynamoDB Streams?
- Enable cross-region replication
- Implement conditional writes
- Increase read capacity units
- Use partition keys
Using partition keys ensures that records with the same partition key are processed in order.
What are some use cases for integrating DynamoDB Streams with AWS Lambda?
- Load balancing
- Long-term data storage
- Real-time analytics
- Static website hosting
Real-time analytics, such as processing and analyzing data changes in real-time, is a key use case for integrating DynamoDB Streams with AWS Lambda.
How does DynamoDB Streams handle data consistency across multiple shards?
- Batch processing
- Parallel processing
- Sequence numbers
- Timestamps
DynamoDB Streams uses sequence numbers to maintain the correct order of records, ensuring data consistency across multiple shards.
What are the limitations of DynamoDB Streams regarding scalability and performance?
- High latency
- Lack of data encryption
- Limited read throughput
- Limited write capacity
The limited read throughput of DynamoDB Streams can impact scalability and performance, particularly when processing high volumes of data.