A developer is building a microservice that uses AWS Lambda to process messages from an Amazon Simple Queue Service (Amazon SQS) standard queue. The Lambda function calls external APIs to enrich the SOS message data before loading the data into an Amazon Redshift data warehouse. The SOS queue must handle a maximum of 1.000 messages per second.
During initial testing, the Lambda function repeatedly inserted duplicate data into the Amazon Redshift table. The duplicate data led to a problem with data analysis. All duplicate messages were submitted to the queue within 1 minute of each other.
How should the developer resolve this issue?
A developer is building a serverless application that is based on AWS Lambd
a. The developer initializes the AWS software development kit (SDK) outside of the Lambda handcar function.
What is the PRIMARY benefit of this action?
This benefit occurs when initializing the AWS SDK outside of the Lambda handler function because it allows the SDK instance to be reused across multiple invocations of the same function. This can improve performance and reduce latency by avoiding unnecessary initialization overhead. If the SDK is initialized inside the handler function, it will create a new SDK instance for each invocation, which can increase memory usage and execution time.
A company is using the AWS Serverless Application Model (AWS SAM) to develop a social media application. A developer needs a quick way to test AWS Lambda functions locally by using test event payloads. The developer needs the structure of these test event payloads to match the actual events that AWS services create.
Comprehensive Detailed Step by Step Explanation with All AWS Developer Reference:
The AWS Serverless Application Model (SAM) includes features for local testing and debugging of AWS Lambda functions. One of the most efficient ways to generate test payloads that match actual AWS event structures is by using the sam local generate-event command.
sam local generate-event: This command allows developers to create pre-configured test event payloads for various AWS services (e.g., S3, API Gateway, SNS). These generated events accurately reflect the format that the service would use in a live environment, reducing the manual work required to create these events from scratch.
Operational Overhead: This approach reduces overhead since the developer does not need to manually create or maintain test events. It ensures that the structure is correct and up-to-date with the latest AWS standards.
Alternatives:
Option A suggests using shareable test events, but manually creating or sharing these events introduces more overhead.
Option B and C both involve manually storing and maintaining test events, which adds unnecessary complexity compared to using sam local generate-event.
A developer must analyze performance issues with production-distributed applications written as AWS Lambda functions. These distributed Lambda applications invoke other components that make up me applications. How should the developer identify and troubleshoot the root cause of the performance issues in production?
This solution will meet the requirements by using AWS X-Ray to analyze and debug the performance issues with the distributed Lambda applications. AWS X-Ray is a service that collects data about requests that the applications serve, and provides tools to view, filter, and gain insights into that data. The developer can use AWS X-Ray to identify the root cause of the performance issues by examining the segments and errors that show the details of each request and the components that make up the applications. Option A is not optimal because it will use logging statements and Amazon CloudWatch, which may not provide enough information or visibility into the distributed applications. Option B is not optimal because it will use AWS CloudTrail, which is a service that records API calls and events for AWS services, not application performance data. Option D is not optimal because it will use Amazon Inspector, which is a service that helps improve the security and compliance of applications on Amazon EC2 instances, not Lambda functions.
A developer is building an ecommerce application that uses multiple AWS Lambda functions. Each function performs a specific step in a customer order workflow, such as order processing and inventory management.
The developer must ensure that the Lambda functions run in a specific order.
Which solution will meet this requirement with the LEAST operational overhead?
The requirement here is to ensure that Lambda functions are executed in a specific order. AWS Step Functions is a low-code workflow orchestration service that enables you to sequence AWS services, such as AWS Lambda, into workflows. It is purpose-built for situations like this, where different steps need to be executed in a strict sequence.
AWS Step Functions: Step Functions allows developers to design workflows as state machines, where each state corresponds to a particular function. In this case, the developer can create a Step Functions state machine where each step (order processing, inventory management, etc.) is represented by a Lambda function.
Operational Overhead: Step Functions have very low operational overhead because it natively handles retries, error handling, and function sequencing.
Alternatives:
Amazon SQS (Option A): While SQS can manage message ordering, it requires more manual handling of each step and the logic to sequentially invoke the Lambda functions.
Amazon SNS (Option B): SNS is a pub/sub service and is not designed to handle sequences of Lambda executions.
EventBridge (Option D): EventBridge Scheduler allows you to invoke Lambda functions based on scheduled times, but it doesn't directly support sequencing based on workflow logic. Therefore, AWS Step Functions is the most appropriate solution due to its native orchestration capabilities and minimal operational complexity.
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