How does AWS Lambda integrate with other AWS services?
- Direct API calls
- Manual configuration
- Only through SDKs
- Through event sources
AWS Lambda integrates with other AWS services through event sources, allowing functions to be triggered by events such as file uploads to Amazon S3 or database updates in Amazon DynamoDB.
What are some benefits of using AWS Lambda for serverless computing?
- High upfront costs
- Limited language support
- Reduced operational overhead
- Requires manual scaling
AWS Lambda reduces operational overhead by automatically managing server provisioning, maintenance, and scaling, allowing developers to focus on code development.
How does AWS Lambda handle scaling automatically?
- Automatically adjusts based on incoming traffic
- Relies on third-party tools for scaling
- Requires manual intervention for scaling
- Uses static scaling configurations
AWS Lambda automatically adjusts its capacity to handle incoming traffic, scaling up or down as needed to accommodate changes in demand.
How does AWS Lambda pricing typically work?
- Fixed monthly subscription
- Pay-per-invocation
- Pay-per-storage
- Pay-per-use
AWS Lambda pricing typically works on a pay-per-use model, where you are charged for the compute time consumed by your function.
What are the key components of an AWS Lambda function?
- API Gateway, CloudWatch, S3 bucket
- EC2 instances, Load balancer, Auto Scaling group
- Function code, Runtime, Handler
- Function name, IAM role, Event source
The key components of an AWS Lambda function include the function code, runtime, and handler.
Scenario: You're tasked with building a scalable and fault-tolerant system using DynamoDB Streams for a high-traffic application. How would you design the system to handle potential spikes in workload and ensure reliable processing of stream records?
- Depend on DynamoDB auto-scaling only
- Implement a dead-letter queue for failed records
- Limit the number of stream records processed
- Use a single large Lambda function
Implementing a dead-letter queue for failed records ensures that any unprocessed records are not lost, allowing for reliable and fault-tolerant processing.
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.
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.
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.
__________ 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.
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.
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.