AWS Certified Solutions Architect - Associate
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A company has a data ingestion workflow that consists of the following:
- An Amazon Simple Notification Service (Amazon SNS) topic for notifications about new data deliveries
- An AWS Lambda function to process the data and record metadata
The company observes that the ingestion workflow fails occasionally because of network connectivity issues. When such a failure occurs, the Lambda function does not ingest the corresponding data unless the company manually reruns the job.
Which combination of actions should a solutions architect take to ensure that the Lambda function ingests all data in the future? (Choose two.)
Other
Community
UAnonymous
A
Deploy the Lambda function in multiple Availability Zones.
B
Create an Amazon Simple Queue Service (Amazon SQS) queue, and subscribe it to the SNS topic.
C
Increase the CPU and memory that are allocated to the Lambda function.
D
Increase provisioned throughput for the Lambda function.
E
Modify the Lambda function to read from an Amazon Simple Queue Service (Amazon SQS) queue.
Explanation:
Explanation
This question addresses resiliency in a data ingestion workflow that's experiencing failures due to network connectivity issues. The current architecture uses SNS → Lambda directly, which has a limitation: if the Lambda function fails to process a message (due to network issues), the message is lost unless manually retried.
Why Options B and E are Correct:
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Option B: Create an Amazon SQS queue and subscribe it to the SNS topic
- This creates a durable message buffer between SNS and Lambda
- Messages are stored in SQS even if Lambda is unavailable
- SQS provides message retention (up to 14 days) and automatic retries
- This decouples the producer (SNS) from the consumer (Lambda)
-
Option E: Modify the Lambda function to read from an Amazon SQS queue
- This completes the architectural pattern: SNS → SQS → Lambda
- Lambda can be configured as an SQS event source with built-in retry logic
- Failed messages remain in the queue for reprocessing
- Lambda can process messages with configurable batch sizes and retry attempts
Why Other Options are Incorrect:
-
Option A: Deploy the Lambda function in multiple Availability Zones
- Lambda functions are already highly available across multiple AZs by AWS's design
- This doesn't address the message loss issue when Lambda fails to process
-
Option C: Increase the CPU and memory that are allocated to the Lambda function
- This addresses performance issues, not resiliency to network failures
- More resources won't prevent message loss when Lambda invocation fails
-
Option D: Increase provisioned throughput for the Lambda function
- This refers to provisioned concurrency, which helps with cold starts
- Doesn't solve the problem of message durability during failures
Key Architecture Pattern:
The solution implements the SNS fanout pattern with SQS queue for reliable message delivery:
- SNS publishes messages to multiple subscribers (including SQS)
- SQS acts as a durable buffer
- Lambda processes messages from SQS with built-in retry capabilities
- Failed messages remain in the queue's dead-letter queue (DLQ) for investigation
This pattern ensures at-least-once delivery and fault tolerance for the data ingestion workflow.
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