AWS Certified Developer Associate Practice Test (DVA-C02)

The correct answer is 'Canary deployments,' because this strategy allows for slowly rolling out the change to a subset of users before making it available to everybody. This approach is particularly useful for minimizing the impact on the production environment if a rollback is necessary due to unforeseen issues with the new version. A 'Blue/green deployment' is incorrect because it involves two separate but identical environments where traffic is switched all at once, not gradually. 'Rolling deployments' is also incorrect as it gradually replaces instances of the old version with the new one on a rolling basis without specifically targeting a population percentage. Lastly, 'All-at-once deployments' is incorrect since it deploys the new version to all instances simultaneously, which would not allow for the controlled exposure or easy rollback that the scenario requires.

Amazon ElastiCache is the appropriate service to be used for adding a caching layer because it supports caching strategies like write-through, read-through, and lazy loading which can handle high traffic and prevent throttling issues with DynamoDB. It supports both Memcached and Redis in-memory data stores which are suitable for various caching use cases.

The correct service for the described needs is AWS X-Ray. This service is specifically designed to help developers analyze and debug both production and distributed applications, such as those built with a microservices architecture. It provides an end-to-end view of requests as they journey through your application, and it constructs a detailed service map that visualizes the application’s architecture. While services like CloudTrail and VPC Flow Logs are useful for their own specific use cases (API activity monitoring and network traffic logging, respectively), they do not offer the dedicated tracing or application topology visualization capabilities that AWS X-Ray provides. Similarly, Amazon CloudWatch focuses primarily on monitoring operational metrics and logs, and it doesn't offer the same comprehensive tracing or service mapping that is native to AWS X-Ray.

The correct answer is 'Canary deployment'. Canary deployments are used to test the performance and stability of a new software version with a subset of users before rolling it out to all users. The term is derived from the 'canary in a coal mine' concept, where small, safe exposure to potential risk is monitored before proceeding further. Blue/green and rolling deployments, while viable strategies, do not use partial traffic routing for testing purposes. Instead, they provide full version replacement either instantly or incrementally across infrastructure. A/B testing, while involving traffic splitting, refers to a method primarily used to compare variations in user experience rather than software version stability.

Feature branching strategy allows for the development of new features to be done in isolation from the main branch (often called master or main). This means that different feature branches can be used for developing new features without affecting the stability of the main branch, which is often used for production or release purposes. When a feature is complete, it can then be merged back into the main branch. The hotfix branch is created specifically to address critical issues in the production environment and can be merged back into the main and development branches with pinpoint precision. This separation of concerns helps ensure that neither new development nor emergency fixes interrupt the flow of the other.

To ensure the most up-to-date data is retrieved, a strongly consistent read should be used. Strongly consistent reads return a response with the most recent data, reflecting all writes that received a successful response before the read. Eventual consistency might return stale data since it allows for the possibility of reads occurring before all of the recent write operations have fully propagated to all copies of the data. Write-through and read-through are caching strategies, not consistency models and thus do not directly pertain to the consistency of database read operations.

The correct approach is to create an alarm that monitors the service's 'ConcurrentExecutions' metric, signaling an impending breach of the allowable parallel execution threshold. The creation of such an alarm can be configured to send a notification to a designated topic within a notification service, which dispatches the alert to the developer. This is a proactive and automated way to monitor for critical thresholds and ensure the developer is promptly notified. The other approaches either do not provide real-time alerts, are not designed for this specific monitoring purpose, or involve manual processes that would not be immediate.

The correct answer automates the release process, handling the workflow from source code to deployment. It enables you to model complex workflows and integrates with other services for building and deployment. In contrast, the service focused on compilation and testing does not provide a full pipeline model. Another option allows you to execute code without managing servers, falling short as a full CI/CD solution. The last choice primarily offers scalable compute capacity and is not tailored for CI/CD.

The Parameter Store, part of Systems Manager, is the appropriate service for managing configuration data and secrets. It allows storing of parameters as plain text or encrypted data, making it suitable for handling sensitive information. It supports version tracking and notifications on parameter changes, and can be accessed dynamically at runtime. This service also provides granular permissions via IAM for controlling access, and integrates with KMS for encryption, ensuring a high security standard without the need to redeploy applications when configurations change.

Bearer tokens, such as JSON Web Tokens (JWT), are a means to ensure that the party making a request to a server is the one it claims to be. When a user authenticates, they receive a token that they include in the header of their HTTP requests. The server validates this token before proceeding with the request, thus securing the application by authenticating the client. Other options listed do not perform the role of bearer tokens because SSL/TLS is used for secure transmission, one-time passwords are typically used for multi-factor authentication, and Amazon Resource Names (ARNs) are used to identify AWS resources, not for securing application transactions between clients and servers.

The statement is false. While exponential backoff is a strategy that progressively increases the wait time between consecutive retry attempts, thus reducing the load on the server and giving it time to recover, it might still lead to the so-called 'retry-storm' if many clients are trying to reconnect at the same intervals. By adding jitter, or randomization to the wait times, the retries are more evenly spread out, which further decreases the likelihood of overwhelming the system. This combined approach reduces the chance of synchronized retries across multiple instances and is generally acknowledged as a best practice for fault-tolerant design within distributed systems.

To trigger an AWS Lambda function on S3 object creation, an event notification should be configured on the specific S3 bucket. Each event notification can specify an event type (such as 's3:ObjectCreated:*') and the destination for the event, which would be the Lambda function's ARN (Amazon Resource Name). Thus, the correct answer is 'Configure an event notification on the S3 bucket to invoke the Lambda function when an object is created'. Bucket policies and CORS configurations on the S3 bucket do not relate to the invocation of Lambda functions based on object creation events. An S3 lifecycle policy is used for object management (such as expiration or transition) and not for event invocation of Lambda functions

A mock integration directly on the gateway allows you to simulate the business logic response by returning preconfigured static data for a given endpoint. This bypasses the need for any actual backend service to be operational or implemented, enabling front-end teams to work against a predictable interface. On the other hand, deploying premature service logic just to produce static data introduces unnecessary overhead and complexity. CORS is related to cross-origin resource sharing, which isn't relevant to simulating service logic. Request validation is concerned with the structure of incoming requests, not the service responses.

Based on the principle of least privilege, the correct approach is to create a custom security profile (also known as an IAM role when implemented in AWS) for the application with the minimal set of permissions needed, which are those that allow reading from and writing to the specified storage buckets and database tables only. Granting full management capabilities across all services, as well as using the root user's credentials, would violate this principle by providing unnecessarily broad permissions and introduce significant security risks. Relying solely on network-based access controls is also incorrect as these are different types of security measures that do not manage the permissions for accessing cloud resources the way IAM roles or policies do.

The developer should leverage Amazon Cognito Identity Pools to meet the requirements. Identity Pools provide federated authentication, enabling users to authenticate with social identity providers, and then obtain temporary permissions to access cloud services directly. This is different from User Pools, which offer user directory functionality and authentication without direct federation into service-level access.