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.

Scenario: Your application receives a sudden surge of incoming messages through SNS. How can you ensure that the AWS Lambda functions triggered by these messages can handle the increased load efficiently?

  • Enable concurrency limits
  • Increase Lambda memory allocation
  • Use AWS Batch
  • Use Step Functions
Setting concurrency limits helps manage the number of concurrent executions, preventing Lambda functions from being overwhelmed.

Scenario: You need to implement a serverless architecture where incoming data from IoT devices triggers AWS Lambda functions for processing. How would you design the integration between SNS and AWS Lambda in this scenario?

  • Deploy EC2 instances
  • Publish data to SNS topic
  • Use S3 for data storage
  • Utilize Kinesis Data Streams
Publishing data to an SNS topic allows SNS to trigger AWS Lambda functions for processing the incoming data from IoT devices.

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.

DynamoDB Streams are triggered by changes to __________ tables.

  • DynamoDB
  • RDS
  • Redshift
  • S3
DynamoDB Streams are triggered by changes to DynamoDB tables, capturing data modifications and enabling subsequent processing.

__________ is the process of capturing a time-ordered sequence of item-level modifications in a DynamoDB table.

  • Change data capture
  • Data replication
  • Data warehousing
  • ETL
Change data capture is the process of capturing a time-ordered sequence of item-level modifications in a DynamoDB table.