AWS Certified Developer Associate Practice Test (DVA-C02)

The correct approach is to integrate the cloud application with the on-premises directory service using a federation protocol such as SAML 2.0. IAM supports federation with SAML, which allows users to authenticate using their existing corporate credentials without storing those credentials in the cloud. While Cognito is also a service that supports federation, IAM with SAML is specifically designed to work seamlessly with corporate directories like Active Directory and is hence the better-suited choice for this particular use case. The other options mentioned do not directly address the requirement of federating with an existing on-premises directory service.

Branches are used to create separate lines of development in a project, enabling multiple developers to work on different features or components simultaneously without interfering with each other's work. The use of branches allows for a controlled way to integrate changes from different sources into the main codebase, typically through mechanisms such as pull requests or merge requests that facilitate code reviews and automated testing before the changes are incorporated into the main branch (often called 'master' or 'main').

The correct answer is git push. This command is used to upload local repository content to a remote repository. It's the standard way to share changes with other team members and keep repositories in sync. git commit only commits changes to the local repository and does not interact with remote repositories. git update is not a standard Git command. git clone is used to copy a repository from a remote source, not to push changes to it.

Cross-account access can be achieved by assuming an IAM role. The IAM role should be created in the target AWS account with the necessary permissions and a trust policy that allows the Lambda function's account to assume the role. Using a user's credentials directly is discouraged and goes against the principle of least privilege, as it can provide unnecessary and broad access. Inline policies are not the correct approach for cross-account access and Lambda environment variables are used for configuration and not for setting up cross-account permissions.

Amazon CloudWatch Logs provides real-time monitoring and logging capabilities. By utilizing CloudWatch Logs agents, you can efficiently transmit logs to CloudWatch without significant performance impacts on the application due to optimized batching and transmission of logs. Moreover, CloudWatch allows querying of log data within minutes of ingestion using features such as CloudWatch Logs Insights. This is essential for troubleshooting issues that require a quick response. On the other hand, manually pushing logs to Amazon S3 would not provide real-time analysis and would require custom solutions for efficient log ingestion, which could also impact application performance. Amazon DynamoDB is not designed as a logging service, and using Amazon Kinesis Data Firehose for direct push of logs would be less efficient due to higher costs and complexity compared to CloudWatch. Streaming logs into the database could result in high write-throughput costs and may not be optimized for log data.

AWS CodeCommit supports branch policies that allow repository administrators to set rules to enforce code quality. This includes the ability to restrict who can commit directly to specific branches, like the master branch. By setting up branch policies, organizations can enforce code reviews and other compliance measures, ensuring that no direct commits can occur without the required level of scrutiny. Limiting direct commits to certain branches is a common practice to ensure the stability of production code and enforce a workflow that includes pull requests and code reviews.

Creating and emitting a custom metric when the serverless function encounters client-related errors allows the team to track the exact number of such incidents. This is because custom metrics can be tailored to the application's unique operational requirements, thus offering the most insightful data for this particular situation. Options like enabling detailed monitoring or reviewing logs would provide broader information that might not be directly related to the client-related errors. Similarly, while distributed tracing systems could give further insights into the execution path, they are generally not as suitable for aggregating and analyzing event counts over time specifically for optimization purposes.

Amazon Simple Queue Service (Amazon SQS) is a managed message queue service that enables you to decouple and scale microservices, distributed systems, and serverless applications. By providing a messaging queue, it allows components in a system to communicate without being directly connected, thereby enhancing the fault tolerance and scalability of the application. Amazon SNS, on the other hand, is a publish/subscribe service, not a queue service. Amazon Kinesis is used primarily for real-time data streaming, not message queuing. Amazon MQ is a managed message broker service but not a native AWS messaging queue service.

For an AWS Lambda function to retrieve parameters from AWS Systems Manager Parameter Store, it requires the ssm:GetParameters IAM policy action. This action grants the function the necessary permissions to read the parameters at runtime. Other actions, such as ssm:PutParameter or ssm:DescribeParameters, are not required for retrieval and are used for different operations. ec2:DescribeInstances is unrelated to accessing parameters and would not grant access to AWS Systems Manager Parameter Store.

The question aims to validate the candidate's knowledge of setting up notifications for manual approval processes. The correct configuration would be to utilize an approval action that leverages Amazon SNS for email notifications. The senior developer would receive these notifications as they would be subscribed to the designated SNS topic. The incorrect answers involve using unrelated AWS services, like CloudWatch, which is primarily for monitoring and alarms, and AWS Lambda, which does serve for custom automation tasks but is not directly related to notification setup for pipeline approvals. The mention of webhooks also does not directly pertain to this scenario, as they are generally used for external event triggering rather than user notifications for approvals.

The development team should use a service designed to model, visualise, and automate the release process of their applications. This specific service should support defining various stages within a pipeline, such as building, validating, and positioning of code into different environments. Selecting a tool that integrates with other services for building and deployment tasks is also crucial. While there are multiple services related to version control and build processes, the one required here must have the capability to coherently orchestrate the flow between environments, ensuring a seamless transition of application code from commits to production readiness.

AWS Lambda Aliases enable you to route traffic to different versions of a Lambda function. Aliases are like pointers and can be changed to point to different function versions as needed. This is useful for integration testing as you can maintain separate testing environments without changing the function's ARN, thus ensuring the stability and consistency of your application during the testing phase. Using different function versions or Stage variables are incorrect choices because while they can point to different configuration settings or Lambda versions, they do not offer the same aliasing capability for routing across different environments without altering the ARN.

To emit a custom metric to Amazon CloudWatch from an AWS Lambda function, developers must use the PutMetricData API action provided by the Amazon CloudWatch service. When using AWS SDK for this action, they should create a metric data query structure that includes the namespace, metric name, value, and a timestamp. The putMetricData operation will then publish the custom metric to CloudWatch. Note that other answers involve incorrect methods that do not align with how CloudWatch custom metrics should be emitted from a Lambda function.

The team should update their production alias to point to both the old and new versions of the Lambda function and then use version weights within the alias configuration to specify the percentage of traffic that each version receives. This setup allows them to control the traffic flow and incrementally increase the weight towards the new version as confidence in stability increases. Assigning 100% to one version, updating the function code directly, or deploying without aliases, does not provide the gradual traffic shifting capability required for a canary release strategy. Therefore, careful allocation of weights to the alias is the correct approach.

The correct service is designed to automate code reviews and provide recommendations for enhancing code quality, including identifying security vulnerabilities. The other options listed are services that serve different purposes: orchestration of resource creation, tracking resource configurations and changes, and logging API activity across an account respectively.