Learn how to use AWS Lambda to insert records into DynamoDB when a new file is added to an S3 bucket. Find out the best solution and the steps to implement it.
Table of Contents
Question
A developer wants to insert a record into an Amazon DynamoDB table as soon as a new file is added to an Amazon S3 bucket.
Which set of steps would be necessary to achieve this?
A. Create an event with Amazon EventBridge that will monitor the S3 bucket and then insert the records into DynamoDB.
B. Configure an S3 event to invoke an AWS Lambda function that inserts records into DynamoDB.
C. Create an AWS Lambda function that will poll the S3 bucket and then insert the records into DynamoDB.
D. Create a cron job that will run at a scheduled time and insert the records into DynamoDB.
Answer
B. Configure an S3 event to invoke an AWS Lambda function that inserts records into DynamoDB.
Explanation
The correct answer to the question is B. Configure an S3 event to invoke an AWS Lambda function that inserts records into DynamoDB.
The reason for this answer is that:
- Option B: Configuring an S3 event to invoke an AWS Lambda function that inserts records into DynamoDB is a simple and efficient way to achieve the desired functionality. S3 events can trigger Lambda functions whenever a new object is created, modified, or deleted in an S3 bucket. Lambda functions can then perform any custom logic, such as inserting records into DynamoDB, using the event data and the AWS SDKs. This way, the developer can ensure that the DynamoDB table is updated in near real-time as soon as a new file is added to the S3 bucket.
- Option A: Creating an event with Amazon EventBridge that will monitor the S3 bucket and then insert the records into DynamoDB is not a necessary step to achieve this functionality. EventBridge is a serverless event bus service that allows you to connect your applications with data from a variety of sources, such as AWS services, SaaS applications, or custom applications. However, EventBridge does not directly support S3 as a source of events. To use EventBridge with S3, you would need to configure an S3 event to send notifications to an Amazon Simple Notification Service (SNS) topic, and then create a rule in EventBridge to match those notifications and invoke a target, such as a Lambda function, that inserts records into DynamoDB. This would add an extra layer of complexity and latency compared to option B.
- Option C: Creating an AWS Lambda function that will poll the S3 bucket and then insert the records into DynamoDB is not a recommended way to achieve this functionality. Polling is a technique where an application repeatedly checks for new data or changes in a data source at regular intervals. Polling can be inefficient and costly, as it consumes resources even when there is no new data available. Polling can also introduce delays and inconsistencies, as the polling frequency may not match the rate of data arrival or change. Instead of polling, it is better to use event-driven architectures, where data sources notify applications of new data or changes as they occur. This way, the applications can respond immediately and only consume resources when needed.
- Option D: Creating a cron job that will run at a scheduled time and insert the records into DynamoDB is not a suitable way to achieve this functionality. A cron job is a task that runs at a specified time or interval on a server or system. Cron jobs can be useful for performing periodic or recurring tasks, such as backups, maintenance, or reporting. However, cron jobs are not designed for handling real-time or near real-time data processing scenarios, such as inserting records into DynamoDB as soon as a new file is added to an S3 bucket. Cron jobs can introduce delays and inconsistencies, as the scheduled time or interval may not match the rate of data arrival or change. Cron jobs can also be unreliable and difficult to manage, as they depend on the availability and performance of the server or system where they run. Instead of cron jobs, it is better to use serverless services, such as Lambda and S3 events, that can scale automatically and handle data processing scenarios efficiently and reliably.
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