Questions and Answers
Which AWS solution ensures that orders are processed in the sequence they are received?
What is a benefit of using Amazon SQS FIFO queues over standard queues for order processing?
Which AWS service is best suited for processing messages in an order-dependent manner from an API Gateway?
What is the primary function of the AWS Lambda function in the described order processing setup?
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Which option is the least effective for ensuring reliable order processing via an API Gateway?
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When configuring an API Gateway to handle orders, which setup minimizes operational overhead?
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Which option provides the least assurance of processing orders in sequence when using API Gateway?
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What is a potential downside of using API Gateway with an SQS standard queue for order processing?
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Which service allows for direct querying of log files stored in JSON format in S3 without data loading?
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What is a significant benefit of using Amazon Athena for analyzing log files?
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When working with Athena, what can users avoid by directly querying JSON logs in S3?
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How does Amazon Athena minimize operational overhead for users?
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Which of the following best describes the SQL querying capability of Amazon Athena?
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Why is Amazon Athena considered a low-overhead solution for analyzing logs?
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What type of storage does Amazon Athena utilize for querying data?
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Which process is not required when using Athena to analyze logs in JSON format?
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Which option best maximizes resiliency and scalability for a migrating distributed application to AWS?
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What is the primary benefit of using Amazon Simple Queue Service (SQS) in the given architecture?
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How should the compute nodes be configured to adapt to changing workloads effectively?
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What role does the Auto Scaling group play in the architecture proposed for the distributed application?
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What is a key factor to consider when deciding between scheduled scaling and dynamic scaling using SQS metrics?
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Which of the following best describes a suitable destination for job processing in the cloud environment?
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When transitioning to a cloud-based architecture, what is the benefit of using Amazon EC2 instances within an Auto Scaling group?
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What is a significant drawback of using a primary server in the proposed distributed application architecture?
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Study Notes
Amazon Kinesis and Message Processing
- Amazon Kinesis Data Analytics can enhance message processing capabilities in consumer applications.
- Implementing Kinesis may necessitate architectural changes to the application.
- FIFO queues are ideal for ordered message processing, while standard queues allow virtually limitless message volume.
Migrating Distributed Applications to AWS
- A company aims to modernize a distributed application by migrating it to AWS.
- The legacy architecture involved a primary server coordinating multiple compute nodes.
- For resilient and scalable design:
- Option A: Use Amazon SQS with EC2 instances in an Auto Scaling group, leveraging scheduled scaling.
- Option B: Implement SQS with EC2 instances in Auto Scaling, triggered by queue size.
- Option C: Maintain the primary server and nodes with EC2 in Auto Scaling, reliant on server load.
- Option D: Use EC2 instances with EventBridge for job destination handling.
E-commerce Application Order Processing
- An e-commerce application sends new order information to an Amazon API Gateway for processing.
- Ensuring that order processing follows the exact order of receipt is essential.
- Suggested solutions:
- Option A: Utilize API Gateway to publish messages to an SNS topic and subscribe a Lambda function for processing.
- Option B: Implement API Gateway to send messages to an SQS FIFO queue, invoking a Lambda function for order processing.
- Option C: Apply an API Gateway authorizer to manage request blocking during order processing.
- Option D: Send messages to an SQS standard queue via API Gateway, triggering a Lambda function for processing.
Data Analysis with Amazon Athena
- Amazon Athena enables querying JSON logs stored in S3 without the need for transformation or additional infrastructure.
- This serverless interactive query service uses standard SQL queries directly against S3 data.
- Athena provides a low-overhead solution, supporting efficient and uncomplicated data analysis from existing log files.
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Description
This quiz covers the fundamentals of Amazon Kinesis Data Analytics and its architecture. It discusses the configurations needed for processing messages through consumer applications and the differences between FIFO and standard queues. Test your knowledge on Kinesis Data Analytics and its application in data streaming.