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| Section | Weight | Objectives |
|---|
| Troubleshooting and Optimization | 18% | - Optimize application performance
- 1. Optimize resource usage and costs
- 2. Improve latency and throughput
- Debug and resolve errors
- 1. Identify and fix code defects
- 2. Resolve integration and configuration problems
- Troubleshoot application issues
- 1. Use Amazon CloudWatch, AWS X-Ray for monitoring
- 2. Analyze logs, metrics, and traces
|
| Deployment | 24% | - Deploy applications on AWS
- 1. Perform safe updates and rollbacks
- 2. Deploy to AWS Lambda, Amazon EC2, Elastic Beanstalk
- Implement CI/CD pipelines
- 1. Use AWS CodePipeline, CodeBuild, CodeDeploy
- 2. Automate deployment and testing workflows
- Prepare application artifacts for deployment
- 1. Package code and dependencies
- 2. Use infrastructure as code (AWS CloudFormation, AWS SAM)
|
| Development with AWS Services | 32% | - Write code for applications hosted on AWS
- 1. Implement architectural patterns
- 2. Use AWS SDKs and APIs
- 3. Develop serverless applications
- Integrate AWS services into applications
- 1. Implement messaging and event-driven workflows
- 2. Use AWS Lambda, API Gateway, Amazon EventBridge
- Interact with AWS data services
- 1. Work with Amazon DynamoDB, Amazon S3
- 2. Implement caching and data storage strategies
|
| Security | 26% | - Secure application data
- 1. Implement encryption at rest and in transit
- 2. Manage secrets and credentials securely
- Apply security best practices
- 1. Validate application security configurations
- 2. Follow AWS Well-Architected Framework security principles
- Implement authentication and authorization
- 1. Use Amazon Cognito for identity management
- 2. Manage IAM roles, policies, and permissions
|
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Amazon AWS Certified Developer - Associate Sample Questions (Q111-Q116):
NEW QUESTION # 111
A developer is deploying an application on Amazon EC2 instances that run in Account A.
The application needs to read data from an existing Amazon Kinesis data stream in Account B.
Which actions should the developer take to provide the application with access to the stream?
(Choose two.)
- A. Add a trust policy to the instance profile role and IAM role in Account B to allow the instance profile role to assume the IAM role.
- B. Add a trust policy to the instance profile role and IAM role in Account B to allow reads from the stream.
- C. Update the instance profile role in Account A with stream read permissions.
- D. Add a resource-based policy in Account B to allow read access from the instance profile role.
- E. Create an IAM role with stream read permissions in Account B.
Answer: A,E
Explanation:
https://aws.amazon.com/blogs/security/how-to-use-trust-policies-with-iam-roles
NEW QUESTION # 112
A company has an application that runs as a series of AWS Lambda functions. Each Lambda function receives data from an Amazon Simple Notification Service (Amazon SNS) topic and writes the data to an Amazon Aurora DB instance.
To comply with an information security policy, the company must ensure that the Lambda functions all use a single securely encrypted database connection string to access Aurora.
Which solution will meet these requirements?
- A. Store the credentials and read the credentials from an encrypted Amazon RDS DB instance.
- B. Store the credentials in AWS Systems Manager Parameter Store as a secure string parameter.
- C. Use Lambda environment variables with a shared AWS Key Management Service (AWS KMS) key for encryption.
- D. Use IAM database authentication for Aurora to enable secure database connections for all the Lambda functions.
Answer: B
Explanation:
AWS Systems Manager Parameter Store offers a more centralized way to manage encrypted secrets across multiple services than Lambda environment variables, making it a better fit for this scenario.
NEW QUESTION # 113
An application adds a processing date to each transaction that it receives. The application writes each transaction to an Amazon DynamoDB table by using the PutItem operation. Each transaction has a unique ID (transactionID). Sometimes the application receives transactions more than once.
A developer notices that duplicate transactions in DynamoDB have the latest processing date instead of the date when the transaction was first received. Duplicate records happen infrequently, and most of the transactions are unique.
What is the MOST cost-effective solution that the developer can implement to ensure that PutItem does not update an existing record?
- A. Call the GetItem operation first to confirm that the record does not exist. Then call PutItem.
- B. Enable the TTL attribute on the DynamoDB table.
- C. Implement a conditional put by using the attribute_not_exists(transactionID) condition expression.
- D. Implement a conditional put by using the attribute_exists(transactionID) condition expression.
Answer: C
Explanation:
Using a conditional PutItem with the condition expression attribute_not_exists(transactionID) ensures that the item is only inserted if it does not already exist, preventing overwrites of existing records. This approach avoids the extra read cost of a GetItem call and is more cost-effective.
NEW QUESTION # 114
A developer is building a three-tier web application that should be able to handle a minimum of 5000 requests per minute. Requirements state that the web tier should be completely stateless while the application maintains session state for the users.
How can session data be externalized, keeping latency at the LOWEST possible value?
- A. Create an Amazon DynamoDB table, then implement session handling at the application level to leverage the table for session data storage.
- B. Create an Amazon ElastiCache (Memcached) cluster, then implement session handling at the application level to leverage the cluster for session data storage.
- C. Create an Amazon RDS instance, then implement session handling at the application level to leverage a database inside the RDS database instance for session data storage.
- D. Implement a shared file system solution across the underlying Amazon EC2 instances, then implement session handling at the application level to leverage the shared file system for session data storage.
Answer: B
Explanation:
Comprehensive Detailed Explanation with all AWS Reference
Why Option C is Correct:
Amazon ElastiCache (Memcached) provides low-latency, in-memory caching suitable for session storage. It ensures stateless web tier operations and supports the high throughput of 5000 requests per minute.
Why Other Options are Incorrect:
Option A: RDS has higher latency compared to in-memory caching solutions like ElastiCache.
Option B: Shared file systems introduce additional complexity and are not ideal for low-latency session data storage.
Option D: DynamoDB has low latency but is less performant than ElastiCache for in-memory session management.
AWS Documentation Reference:
Amazon ElastiCache for Session State Management
NEW QUESTION # 115
A developer maintains an AWS Lambda function that is invoked synchronously through an API Gateway API. The Lambda function processes payments by calling a third-party platform. The Lambda function includes retry logic that will make five attempts for each invocation.
The third-party platform occasionally experiences outages that last 10-20 minutes. During outages, the Lambda function makes five retry attempts for each incoming request before failing. The request retry process generates thousands of wasted API calls and increases Lambda compute costs.
The developer needs a solution to detect third-party platform outages and to ensure that invocations of the Lambda function stop when a platform outage is detected. The developer must also ensure that the invocations resume when the platform is operational and accessible.
Which solution will meet these requirements?
- A. Add exponential backoff to the Lambda function ' s retry logic to space out retry attempts during failures.
- B. Increase the Lambda function ' s timeout allocation and memory allocation so that retry attempts run longer.
- C. Configure a dead-letter queue to capture events after the Lambda function ' s five retry attempts are exhausted.
- D. Implement a circuit breaker that stops invocations after failures exceed a threshold.
Answer: D
Explanation:
Option D is correct because this is exactly the problem the circuit breaker pattern solves. When a downstream service repeatedly fails or times out, a circuit breaker stops further calls after a failure threshold is reached. This prevents the Lambda function from repeatedly calling an unavailable third-party payment platform, reducing wasted API calls and Lambda compute cost. AWS Prescriptive Guidance states that the circuit breaker pattern can prevent a caller service from retrying calls to another service after repeated failures and can also detect when the downstream service becomes functional again. A DLQ does not help because the API Gateway invocation is synchronous and the waste happens before failure. Increasing timeout or memory makes the issue worse. Exponential backoff helps reduce retry pressure but does not stop invocations during an outage.
NEW QUESTION # 116
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