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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Security | 26% | - Apply security best practices
|
| Topic 2: Troubleshooting and Optimization | 18% | - Debug and resolve errors
|
| Topic 3: Deployment | 24% | - Implement CI/CD pipelines
|
| Topic 4: Development with AWS Services | 32% | - Integrate AWS services into applications
|
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NEW QUESTION # 21
A developer needs to build an AWS CloudFormation template that self-populates the AWS Region variable that deploys the CloudFormation template.
What is the MOST operationally efficient way to determine the Region in which the template is being deployed?
Answer: D
NEW QUESTION # 22
A Developer has been asked to make changes to the source code of an AWS Lambda function.
The function is managed using an AWS CloudFormation template. The template is configured to load the source code from an Amazon S3 bucket. The Developer manually created a .ZIP file deployment package containing the changes and put the file into the correct location on Amazon S3. When the function is invoked, the code changes have not been applied.
What step is required to update the function with the changes?
Answer: D
Explanation:
Changes to a deployment package in Amazon S3 are not detected automatically during stack updates. To update the function code, change the object key or version in the template.
https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-lambda- function-code.html
NEW QUESTION # 23
A team has an Amazon API Gateway REST API that consists of a single resource and a GET method that is backed by an AWS Lambda integration.
A developer makes a change to the Lambda function and deploys the function as a new version. The developer needs to set up a process to test the new version of the function before using the new version in production. The tests must not affect the production REST API.
Which solution will meet these requirements with the LEAST operational overhead?
Answer: D
Explanation:
The requirement is to test a new Lambda version without impacting the production API, and to do so with the least operational overhead. In API Gateway (REST API), the simplest pattern is to create a separate stage (for example, test) and use a stage variable to control which Lambda function version (or alias) the integration invokes.
With option B, the developer creates a new stage and defines a stage variable (commonly something like lambdaAlias or lambdaVersion). The API method integration URI can reference this stage variable so that each stage points to a different Lambda alias/version. The production stage (for example, prod) continues to call the stable version, while the test stage calls the new version. This cleanly isolates testing traffic and prevents any effect on the production REST API because stages have distinct invoke URLs and deployments.
This approach is operationally efficient because it avoids duplicating the API definition (new REST API) and avoids creating extra resources/methods that must be maintained. It also provides a repeatable process: future versions can be tested by updating only stage variables or alias routing rather than restructuring the API.
Why not the others:
* A adds additional resources/methods and increases API surface area and maintenance.
* C duplicates the entire API, increasing overhead and configuration drift risk.
* D would impact production because it changes the integration used by the existing method.
Therefore, using a new stage + stage variables to route to the updated Lambda version meets the requirements with minimal overhead.
NEW QUESTION # 24
A developer is building an application that stores objects in an Amazon S3 bucket. The bucket does not have versioning enabled. The objects are accessed rarely after 1 week. However, the objects must be immediately available at all times. The developer wants to optimize storage costs for the S3 bucket.
Which solution will meet this requirement?
Answer: B
Explanation:
Comprehensive Detailed and Lengthy Step-by-Step Explanation with All AWS Developer References:
1. Understanding the Use Case:
The goal is to store objects in an S3 bucket while optimizing storage costs. The key conditions are:
* Objects are accessed infrequently after 1 week.
* Objects must remainimmediately accessibleat all times.
2. AWS S3 Storage Classes Overview:
Amazon S3 offers various storage classes, each optimized for specific use cases:
* S3 Standard:Best for frequently accessed data with low latency and high throughput needs.
* S3 Standard-Infrequent Access (S3 Standard-IA):Optimized for infrequently accessed data but requires the same availability and immediate access as Standard storage. It provides lower storage costs but incurs retrieval charges.
* S3 Glacier Flexible Retrieval (formerly S3 Glacier):Designed for archival data with retrieval latency ranging from minutes to hours. This does not meet the requirement for "immediate access."
* S3 Glacier Deep Archive:Lowest-cost storage, suitable for rarely accessed data with retrieval times of hours.
3. Explanation of the Options:
* Option A:"Create an S3 Lifecycle rule to expire objects after 7 days."Expiring objects after 7 days deletes them permanently, which does not fulfill the requirement of retaining the objects for later infrequent access.
* Option B:"Create an S3 Lifecycle rule to transition objects to S3 Standard-Infrequent Access (S3 Standard-IA) after 7 days."This is the correct solution. S3 Standard-IA is ideal for objects accessed infrequently but still need to be available immediately. Transitioning objects to this storage class reduces storage costs while maintaining availability and low latency.
* Option C:"Create an S3 Lifecycle rule to transition objects to S3 Glacier Flexible Retrieval after 7 days."S3 Glacier Flexible Retrieval is a low-cost archival solution. However, it does not provide immediate accessas retrieval requires minutes to hours. This option does not meet the requirement.
* Option D:"Create an S3 Lifecycle rule to delete objects that have delete markers."This option is irrelevant to the given use case, as it addresses versioning cleanup, which is not enabled in the described S3 bucket.
4. Implementation Steps for Option B:
To transition objects to S3 Standard-IA after 7 days:
* Navigate to the S3 Console:
* Sign in to theAWS Management Consoleand open the S3 service.
* Select the Target Bucket:
* Choose the bucket where the objects are stored.
* Set Up a Lifecycle Rule:
* Go to theManagementtab.
* UnderLifecycle Rules, clickCreate lifecycle rule.
* Define the Rule Name and Scope:
* Provide a descriptive name for the rule.
* Specify whether the rule applies to the entire bucket or a subset of objects (using a prefix or tag filter).
* Configure Transitions:
* ChooseAdd transition.
* Specify that objects should transition toS3 Standard-IAafter7 days.
* Review and Save the Rule:
* Review the rule configuration and clickSave.
5. Cost Optimization Benefits:
Transitioning to S3 Standard-IA results in cost savings as it offers:
* Lower storage costs compared to S3 Standard.
* Immediate access to objects when required.However, remember that there is a retrieval cost associated with S3 Standard-IA, so it is best suited for data with low retrieval frequency.
NEW QUESTION # 25
A company has an application that stores data in Amazon RDS instances. The application periodically experiences surges of high traffic that cause performance problems.
During periods of peak traffic, a developer notices a reduction in query speed in all database queries.
The team's technical lead determines that a multi-threaded and scalable caching solution should be used to offload the heavy read traffic. The solution needs to improve performance.
Which solution will meet these requirements with the LEAST complexity?
Answer: B
Explanation:
* Amazon ElastiCache for Memcached is a fully managed, multithreaded, and scalable in-memory key- value store that can be used to cache frequently accessed data and improve application performance1.
By using Amazon ElastiCache for Memcached, the developer can reduce the load on the main database and handle high traffic surges more efficiently.
* To use Amazon ElastiCache for Memcached, the developer needs to create a cache cluster with one or more nodes, and configure the application to store and retrieve data from the cache cluster2. The developer can use any of the supported Memcached clients to interact with the cache cluster3. The developer can also use Auto Discovery to dynamically discover and connect to all cache nodes in a cluster4.
* Amazon ElastiCache for Memcached is compatible with the Memcached protocol, which means that the developer can use existing tools and libraries that work with Memcached1. Amazon ElastiCache for Memcached also supports data partitioning, which allows the developer to distribute data among multiple nodes and scale out the cache cluster as needed.
* Using Amazon ElastiCache for Memcached is a simple and effective solution that meets the requirements with the least complexity. The developer does not need to change the database schema, migrate data to a different service, or use a different caching model. The developer can leverage the existing Memcached ecosystem and easily integrate it with the application.
NEW QUESTION # 26
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