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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Troubleshooting and Optimization | 18% | - Optimize application performance
|
| Topic 2: Deployment | 24% | - Deploy applications on AWS
|
| Topic 3: Security | 26% | - Secure application data
|
| Topic 4: Development with AWS Services | 32% | - Integrate AWS services into applications
|
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NEW QUESTION # 594
Users of a web-based music application are experiencing latency issues on one of the application's most popular pages. A developer identifies that the issue is caused by the slow load time of specific widgets that are used to rank and sort various songs and albums.
The developer need to ensure that the widgets load more quickly by using built-in in-memory ranking and sorting techniques. The developer must ensure that the data remains up to date.
Which solution will meet these requirements with the LEAST latency?
Answer: B
Explanation:
ElastiCache for Redis OSS is the best fit because Redis supports sorted sets, which are built specifically for real-time ranking and sorting use cases such as leaderboards. AWS documentation highlights Redis sorted sets for moving ranking complexity into the in-memory cache itself, which gives the lowest latency for these widgets. A write-through strategy keeps the cache updated as the application writes data, so the ranked and sorted results stay current instead of waiting for a cache miss to refresh them.
NEW QUESTION # 595
A company migrates some of its Amazon EC2 workloads to Spot Instances. An infrastructure team wants to determine how often the deployed Spot Instances are interrupted and replaced.
The infrastructure team must publish a custom metric to Amazon CloudWatch for Spot Instance interruptions and replacements.
Which solution will meet this requirement with LEAST development effort?
Answer: C
Explanation:
Amazon EventBridge emits specific events for Spot Instance interruptions. Creating a Lambda function triggered by these Spot interruption events allows direct detection without extra filtering or lifecycle hook configuration, minimizing development effort. The function can then publish a custom CloudWatch metric for each interruption.
NEW QUESTION # 596
A developer is building an application to process a stream of customer orders. The application sends processed orders to an Amazon Aurora MySQL database. The application needs to process the orders in batches.
The developer needs to configure a workflow that ensures each record is processed before the application sends each order to the database.
Options:
Answer: D
Explanation:
Step 1: Understanding the Problem
Processing in Batches: The application must process records in groups.
Sequential Processing: Each record in the batch must be processed before writing to Aurora.
Solution Goals: Use services that support ordered, batched processing and integrate with Aurora.
Step 2: Solution Analysis
Option A:
Amazon Kinesis Data Streams supports ordered data processing.
AWS Lambda can process batches of records via event source mapping with MaximumBatchingWindowInSeconds for timing control.
Configuring the batching window ensures efficient processing and compliance with the workflow.
Correct Option.
Option B:
Amazon SQS is not designed for streaming; it provides reliable, unordered message delivery.
Setting MaximumBatchingWindowInSeconds to 0 disables batching, which is contrary to the requirement.
Not suitable.
Option C:
Amazon MSK provides Kafka-based streaming but requires custom EC2-based processing.
This increases system complexity and operational overhead.
Not ideal for serverless requirements.
Option D:
DynamoDB Streams is event-driven but lacks strong native integration for batch ordering.
Using ECS adds unnecessary complexity.
Not suitable.
Step 3: Implementation Steps for Option A
Set up Kinesis Data Stream:
Configure shards based on the expected throughput.
Configure Lambda with Event Source Mapping:
Enable Kinesis as the event source for Lambda.
Set MaximumBatchingWindowInSeconds to 300 to accumulate data for processing.
Example:
{
"EventSourceArn": "arn:aws:kinesis:region:account-id:stream/stream-name",
"BatchSize": 100,
"MaximumBatchingWindowInSeconds": 300
}
Write Processed Data to Aurora:
Use AWS RDS Data API for efficient database operations from Lambda.
AWS Developer Reference:
Amazon Kinesis Data Streams Developer Guide
AWS Lambda Event Source Mapping
Batch Processing with Lambda
NEW QUESTION # 597
A company is building an application on AWS. The application's backend includes an Amazon API Gateway REST API. The company's frontend application developers cannot continue work until the backend API is ready for integration. The company needs a solution that will allow the frontend application developers to continue their work.
Which solution will meet these requirements in the MOST operationally efficient way?
Answer: D
NEW QUESTION # 598
A developer is migrating an application to Amazon Elastic Kubernetes Service (Amazon EKS). The developer migrates the application to Amazon Elastic Container Registry (Amazon ECR) with an EKS cluster.
As part of the application migration to a new backend, the developer creates a new AWS account. The developer makes configuration changes to the application to point the application to the new AWS account and to use new backend resources. The developer successfully tests the changes within the application by deploying the pipeline.
The Docker image build and the pipeline deployment are successful, but the application is still connecting to the old backend. The developer finds that the application's configuration is still referencing the original EKS cluster and not referencing the new backend resources.
Which reason can explain why the application is not connecting to the new resources?
Answer: C
Explanation:
The correct answer is C. The developer did not update the Docker image tag to a new version.
C). The developer did not update the Docker image tag to a new version. This is correct. When deploying an application to Amazon EKS, the developer needs to specify the Docker image tag that contains the application code and configuration. If the developer does not update the Docker image tag to a new version after making changes to the application, the EKS cluster will continue to use the old Docker image tag that references the original backend resources. To fix this issue, the developer should update the Docker image tag to a new version and redeploy the application to the EKS cluster.
A). The developer did not successfully create the new AWS account. This is incorrect. The creation of a new AWS account is not related to the application's connection to the backend resources. The developer can use any AWS account to host the EKS cluster and the backend resources, as long as they have the proper permissions and configurations.
B). The developer added a new tag to the Docker image. This is incorrect. Adding a new tag to the Docker image is not enough to deploy the changes to the application. The developer also needs to update the Docker image tag in the EKS cluster configuration, so that the EKS cluster can pull and run the new Docker image.
D). The developer pushed the changes to a new Docker image tag. This is incorrect. Pushing the changes to a new Docker image tag is not enough to deploy the changes to the application. The developer also needs to update the Docker image tag in the EKS cluster configuration, so that the EKS cluster can pull and run the new Docker image.
References:
1: Amazon EKS User Guide, "Deploying applications to your Amazon EKS cluster", https://docs.aws.amazon.
com/eks/latest/userguide/deploying-applications.html
2: Amazon ECR User Guide, "Pushing an image", https://docs.aws.amazon.com/AmazonECR/latest/userguide
/docker-push-ecr-image.html
3: Amazon EKS User Guide, "Updating an Amazon EKS cluster", https://docs.aws.amazon.com/eks/latest
/userguide/update-cluster.html
NEW QUESTION # 599
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