Streams and Triggers

5 minutes 5 Questions

Streams and triggers are essential features in Amazon DynamoDB for capturing and reacting to changes in the data. DynamoDB Streams is a time-ordered and durable event stream of all changes (creation, update, or deletion) made to the items in a table. You can process the stream records using AWS Lambda or other applications. Triggers are a form of serverless computing that respond to specific events, such as updates to the data in a DynamoDB table. AWS Lambda can be utilized as a trigger to automatically process these events and execute custom logic, for example, synchronizing data between tables or sending notifications through Amazon SNS. In summary, streams and triggers enable real-time data processing and event-driven applications in DynamoDB.

Guide to Amazon DynamoDB Streams and Triggers

Amazon DynamoDB Streams and Triggers form a key component of the AWS Solution Architect toolkit. They are a concept within the larger context of Amazon DynamoDB, which is a fully managed NoSQL database service.

What are DynamoDB Streams and Triggers?
DynamoDB Streams is essentially a time-ordered sequence of database modifications, while Triggers instigate specific functions whenever modifications to the table data occur.

Why are they important?
These tools allow for continuous, automated reactions to data modifications, enabling real-time data analysis, efficient data replication, and robust recovery options. This makes them crucial for managing large-scale, high-traffic applications, such as those commonly handled with AWS.

How do they work?
DynamoDB Streams capture a time-ordered sequence of item-level modifications in your DynamoDB tables and store this data for 24 hours. The changes are then available in near real-time for other services to consume and act upon.
Triggers, meanwhile, are linked to specific DynamoDB tables and then invoke a Lambda function when the table is modified. This could be a simple notification of the change or a complex response, such as instigating other AWS services.

Exam Tips: Answering Questions on Streams and Triggers:
- Remember, DynamoDB Streams are time-ordered and data is stored for 24 hours.
- Triggers are used to automate responses to these changes, and they invoke AWS Lambda functions.
- Understanding these functions and when they would be utilized is key to answering many AWS Solution Architect exam questions on this subject.
- Real-world application questions can often be solved by considering how these tools can provide automated, real-time reactions to specific changes in table data.

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Question 1

A retail company wants to use AWS Lambda to process customer orders from their Amazon RDS database. However, they need near real-time processing of INSERT and UPDATE statements. How can this be achieved?

Use Amazon CloudWatch metrics to monitor RDS database changes and trigger Lambda functions. Configure AWS DMS to directly invoke Lambda functions for real-time processing. Enable RDS triggers and use an Amazon Kinesis Data Stream to process the data with Lambda. Configure Amazon RDS to save change events as S3 objects and process with Lambda.

Correct Answer: Enable RDS triggers and use an Amazon Kinesis Data Stream to process the data with Lambda.

Enable RDS triggers that send events to Kinesis Data Streams to process them with Lambda, allowing near real-time processing at scale. Other options either do not provide direct integration with RDS or do not enable near-real-time processing.

Question 2

A company is using AWS Kinesis Data Streams to process stock market data. They require that no stock market event is processed more than once. How can they ensure this requirement is met?

Enable 'exactly-once' processing on the Kinesis Data Stream. Use AWS Outposts to ensure data processing only occurs once. Use record sequence numbers to identify and discard duplicates. Enable 'at-least-once' processing on the Kinesis Data Stream.

Correct Answer: Use record sequence numbers to identify and discard duplicates.

Kinesis Data Streams provides record sequence numbers for each record, which can be used to identify and discard duplicates. Other options do not offer built-in de-duplication or do not apply to Kinesis Data Streams.

Question 3

An IoT system sends events to an Amazon Kinesis Data Stream for further processing. To save costs, the company wants to process events immediately only during working hours and in batches outside working hours. How should they implement this?

Attach AWS Lambda triggers to the Kinesis Data Stream, and use CloudWatch Events to enable or disable the triggers during specific hours. Set up an Amazon S3 bucket policy that triggers AWS Lambda functions depending on the hour. Use Amazon Kinesis Data Firehose to process events in real-time during working hours and batch outside of working hours. Configure Amazon EC2 Scheduler to modify the trigger availability.

Correct Answer: Attach AWS Lambda triggers to the Kinesis Data Stream, and use CloudWatch Events to enable or disable the triggers during specific hours.

Attaching Lambda triggers to the Kinesis Data Stream and using CloudWatch Events to enable or disable them allows you to control event processing based on specific hours. Other options don't provide this level of control or focus on different use cases.

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