Free AWS Certified Developer Associate DVA-C02 Practice Test

The correct answer is the one that adheres to the standard event structure that an AWS Lambda function expects from an API Gateway with proxy integration. This includes the correct use of 'httpMethod', 'body' with properly escaped JSON string, 'path', and 'requestContext'. The body must also be a string that is a serialized JSON object since the Lambda function will parse it as JSON. The correct option presents a nested JSON in a string format, properly serialized and escaped. Other options either present the body as an object instead of a string, improperly escape double quotes, or miss important property fields.

Observability extends beyond basic logging and monitoring by offering insights into the system's internal state, derived from the output data. This helps in proactive and efficient problem-solving. Logging refers to the recording of events and data, while monitoring is the process of tracking metrics and logs to oversee the performance and health of the system. Observability uses this data to provide a deeper understanding of the system, allowing for proactive issue identification and resolution.

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.

Attaching an instance profile that contains an IAM role with the necessary S3 permissions to your EC2 instances is the recommended solution for this scenario. This allows the application to assume the IAM role and obtain temporary credentials, which can be used to access the S3 bucket. The use of an instance profile ensures that the EC2 instance can securely make API calls to AWS services on behalf of the user that assumed the role. Unlike static credentials, these permissions are automatically rotated and managed by AWS. Creating individual IAM users is not scalable for multiple instances, and hard-coding credentials is a security risk and violates the AWS recommended practice of not embedding secrets in code. Using a resource-based policy on the S3 bucket is not possible, as it cannot grant the necessary EC2 instance permissions to assume a role.

The framework for building serverless applications provides a local environment that mimics the cloud execution environment. This feature allows developers to iterate quickly by executing and debugging their code on local machines, saving time and resources by not requiring code to be deployed to the cloud service for initial testing phases. This is particularly useful for developing, testing, and debugging Lambda functions.

The correct answer is the Serverless Application Model, which provides a streamlined way for defining functions, APIs, and the event source mappings that trigger them. It also supports configuration variants for different stages of deployment, such as development and production. This simplifies the process and makes it efficient for developers to manage serverless applications in a multi-environment setup.

The other options, like the service for deploying web applications or the deployment automation service, do not offer the same level of simplicity and direct support for serverless architecture templating. The infrastructure as code service is also capable of defining resources but does not offer the simplified syntax and tools that are tailored for serverless applications like the Serverless Application Model does. The Cloud Infrastructure Development Kit is a more generic tool for defining cloud resources using familiar programming languages and could be used for these purposes, but it doesn't offer the same level of convenience for serverless deployments specifically.

By storing the state externally in a database or caching system, the Lambda functions do not need to retain state between invocations. This approach aligns with the stateless nature of AWS Lambda, where each invocation should handle requests independently without relying on any prior state information. Using environment variables for configuration does not address state management between function invocations. Similarly, enabling automatic scaling or using asynchronous invocation does not inherently make an application stateless, although these configurations contribute to scalability and performance.

The best practice for deploying updates without impacting the live user environment is to deploy the changes to a separate staging environment. This approach provides a testing ground that simulates the live environment but prevents any disruptions or unintended consequences from reaching actual users. Directly updating the live environment can lead to untested or faulty code impacting users, while choosing a completely unrelated environment may not provide accurate testing feedback. Testing IAM role permissions is part of securing the deployments, but it does not replace the need for environment-specific deployment for testing changes.

Amazon CloudWatch Logs is the suitable service for analyzing log data in real time and setting up mechanisms to act upon particular log patterns, such as setting up metric filters and alarms. It facilitates the continuous monitoring, storing, and accessing log files. Additionally, application issues can be addressed rapidly by using its features to trigger automated responses. Options involving other services are incorrect as they are not primarily used for log data analysis or don't support triggering actions based on log events.

The service designed for providing insights into the performance and operation of distributed applications is X-Ray. It allows the collection, analysis, and visualization of tracing data, which is crucial for developers to understand and optimize their applications. CloudTrail, on the other hand, focuses on logging and auditing AWS account activity. Inspector assesses applications for vulnerabilities and deviations from best practices. CloudFormation automates infrastructure provisioning, which is unrelated to application performance tracing.

The developer should implement a Lambda authorizer, which is a way to handle custom authorization logic before granting access to the serverless function endpoint. The Lambda authorizer can verify the validity of the token and determine if the request should be allowed or denied. This approach is particularly useful in serverless architectures where application components are loosely coupled, and an external identity provider manages user authentication. This verification is performed within the AWS environment without making a round trip to the external identity provider. On the contrary, IAM roles are for access management within AWS services and resources, not for validating tokens directly. Resource-based policies define permissions for AWS resources, but they do not provide a method for validating bearer tokens. Client-side certificates are used for mutual TLS (mTLS) authentication but do not apply to the scenario involving verification of tokens provided by an external identity provider.

The service that fits the requirements described is designed to enable developers to manage and safely deploy application configurations separate from the application code. It has features for validating the changes against a schema, supporting scheduled updates, and allowing a controlled rollout, which includes the functionality to limit the percentage of an environment targeted by a new configuration. This advanced configuration deployment is not offered by the services primarily focused on secure storage of secrets or on providing basic configuration storage. Moreover, the described service aligns more closely with configuration and feature management rather than with the continuous integration and delivery process, which another service targets.

The correct service is designed to facilitate the separation of code from environment-specific configurations, allowing for settings to be deployed independently of the application code. This is a best practice, as it promotes consistent configuration across environments and makes management tasks simpler. The incorrect services, while they can store parameters or secrets, are not primarily focused on comprehensive configuration management at scale or safe deployment practices as their core functionalities. The last option is not a real service, and is listed to ensure that the test taker is not just recognizing AWS product names but actually understands their purposes.

The appropriate service for the creation and administration of encryption keys in the cloud is Key Management Service (KMS), which provides options to both create your own encryption keys and configure them for automatic rotation. Utilizing KMS keys offers the capability to fulfill the need for encryption at rest within S3 while also adhering to the company's guidelines for regular key rotation. The reliance on the platform's own managed keys would preclude direct control and rotation management. Certificate Manager's primary use case involves issuing certificates for TLS, not storage encryption, while CloudHSM is tailored for specific compliance requirements and does not innately manage automatic key rotation.

The developer should employ a composite primary key with two elements: a partition element that represents the individual customer, and a sort element that aligns with the chronological aspect of the interactions. This approach enables the table to isolate data per customer while allowing sorted and range-based retrieval within the confines of each customer's data set. A design with a singular identifier disregards the query needs by customer and date. A primary key based solely on the customer element would fail to account for multiple interactions and lead to poor distribution of data, whereas focusing on chronological elements alone could lead to similarly skewed data distribution due to concurrent interactions across customers.