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| Section | Weight | Objectives |
|---|---|---|
| Development with AWS Services | 32% | - Write code for applications hosted on AWS
|
| Troubleshooting and Optimization | 18% | - Troubleshoot application issues
|
| Deployment | 24% | - Prepare application artifacts for deployment
|
| Security | 26% | - Implement authentication and authorization
|
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NEW QUESTION # 143
A company is using Amazon RDS as the Backend database for its application. After a recent marketing campaign, a surge of read requests to the database increased the latency of data retrieval from the database.
The company has decided to implement a caching layer in front of the database. The cached content must be encrypted and must be highly available.
Which solution will meet these requirements?
Answer: D
Explanation:
Explanation
This solution meets the requirements because it provides a caching layer that can store and retrieve encrypted data from multiple nodes. Amazon ElastiCache for Redis supports encryption at rest and in transit, and can scale horizontally to increase the cache capacity and availability. Amazon ElastiCache for Memcached does not support encryption, Amazon CloudFront is a content delivery network that is not suitable for caching database queries, and Amazon DynamoDB Accelerator (DAX) is a caching service that only works with DynamoDB tables.
NEW QUESTION # 144
A company needs a new REST API that can return information about the contents of an Amazon S3 bucket, such as a count of the objects stored in it. The company has decided that the new API should be written as a microservice using AWS Lambda and Amazon API Gateway. How should the developer ensure that the microservice has the necessary access to the Amazon S3 bucket, while adhering to security best practices?
Answer: D
Explanation:
A Lambda function should access AWS services through an IAM execution role with only the permissions required for the task. Granting the role access to the specific S3 bucket allows the microservice to read bucket contents securely without hardcoded credentials or overly broad permissions.
NEW QUESTION # 145
A company has multiple Amazon VPC endpoints in the same VPC. A developer needs configure an Amazon S3 bucket policy so users can access an S3 bucket only by using these VPC endpoints.
Which solution will meet these requirements?
Answer: D
Explanation:
This solution will meet the requirements by creating a single S3 bucket policy that denies access to the S3 bucket unless the request comes from one of the specified VPC endpoints. The aws:SourceVpce condition key is used to match the ID of the VPC endpoint that is used to access the S3 bucket. The StringNotEquals condition operator is used to negate the condition, so that only requests from the listed VPC endpoints are allowed. Option A is not optimal because it will create multiple S3 bucket policies, which is not possible as only one bucket policy can be attached to an S3 bucket. Option B is not optimal because it will use the aws:SourceVpc condition key, which matches the ID of the VPC that is used to access the S3 bucket, not the VPC endpoint. Option C is not optimal because it will use the StringNotEquals condition operator with a single value, which will deny access to the S3 bucket from all VPC endpoints except one.
NEW QUESTION # 146
An ecommerce company is developing a serverless application to track user activities. The company needs to track each type of activity with a timestamp and a unique product ID. The company also must track actions that are associated with each activity, such as product views, shopping cart actions, purchases, and checkout processes.
The company is planning a marketing campaign based on each user's activity. A developer needs to implement a partitioning strategy for an Amazon DynamoDB table to meet the data storage and access requirements for the application. The strategy must maximize provisioned throughput efficiency while minimizing the risk of throttling.
Which solution will meet these requirements?
Answer: C
Explanation:
For this workload, the access pattern is centered on each user's activity history over time (the company is planning a marketing campaign based on each user's activity). In DynamoDB, the most effective way to store and query time-ordered events per entity is to use a composite primary key where the entity identifier is the partition key and a time attribute is the sort key. Therefore, using user ID as the partition key groups all events for a given user together, and using timestamp as the sort key allows efficient retrieval in chronological order and supports range queries (for example, "activities in the last 7 days" or "between two dates").
This design also helps maximize provisioned throughput efficiency and reduce throttling risk because it distributes data across partitions based on the partition key values (user IDs). With many users, writes and reads naturally spread across multiple partition key values rather than concentrating on a small set. The sort key further enables multiple activity records per user without overwriting items and supports precise queries without scanning.
Option B (product ID as partition key) does not align with the stated marketing need (per-user activity). It would cluster all users' actions for a popular product into the same partition key, increasing the chance of hot partitions and throttling. Option C also risks hot partitions for popular product IDs; auto scaling helps capacity management but does not fix poor key distribution or hot-key access patterns. Option D (monotonic counter as partition key) is particularly problematic: sequential keys can create uneven distribution and a throughput bottleneck pattern, and it does not support user-centric queries efficiently.
Thus, A best matches the data model (user events over time), supports efficient queries, and reduces throttling risk by distributing workload across user IDs.
NEW QUESTION # 147
A development team is responsible for an application that uses a microservices architecture. The microservices are deployed to AWS Elastic Beanstalk. One of the services calls Amazon DynamoDB, Amazon S3, and a third-party service. The team notices that every morning around 7 AM, the production service performs poorly for a few minutes. Which action can the developer take to understand what is happening?
Answer: B
Explanation:
Enabling the AWS X-Ray daemon configuration and using the X-Ray SDK allows the developer to trace and collect detailed performance data about calls to AWS services and external APIs.
This provides insights into latency and errors, helping to diagnose why the service is performing poorly at a specific time.
NEW QUESTION # 148
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