View Full Amazon AWS Certified DevOps Engineer – Professional DOP-C02 Exam Dumps and Practice Test Dumps

 

Question 201. Which feature helps protect CodePipeline artifacts from unauthorized changes?

1. CloudWatch dashboards
   2. Artifact encryption and integrity controls
   3. EC2 Auto Scaling
   4. Route 53 health checks

Correct Answer: 2. Artifact encryption and integrity controls

Explanation:

CodePipeline artifacts can contain source packages, compiled application files, deployment templates, and other data that moves between pipeline stages. Protecting these artifacts is important because an unauthorized modification could cause an untrusted or incorrect package to reach production. Artifact stores can use encryption, including AWS KMS keys, to protect data at rest, while appropriate IAM permissions and bucket policies restrict who can access or modify the artifacts. Pipelines should also use controlled artifact locations and tightly scoped permissions. These practices help maintain the integrity of artifacts throughout the CI/CD process and reduce the possibility of unauthorized changes being introduced between stages.

Question 202. What does a CodeBuild batch build allow?

1. Running only one command per build
   2. Disabling build logs
   3. Running multiple related builds as one build operation
   4. Automatically creating IAM users

Correct Answer: 3. Running multiple related builds as one build operation

Explanation:

AWS CodeBuild batch builds allow multiple build executions to be coordinated as part of a single batch operation. This is useful when a project needs to build several configurations, platforms, environments, or test variations at the same time. Instead of manually starting separate builds and tracking them independently, a batch build can coordinate the related executions and report their results together. This capability is particularly useful for large CI workflows where different combinations need to be tested. Batch builds can improve automation and reduce unnecessary orchestration logic while still allowing each individual build to use its own commands, environment settings, and artifacts when configured appropriately.

Question 203. Which cache type can store CodeBuild dependencies in Amazon S3?

1. S3 cache
   2. DNS cache
   3. Route 53 cache
   4. IAM cache

Correct Answer: 1. S3 cache

Explanation:

CodeBuild supports caching to reduce build times by reusing files from previous builds instead of downloading or recreating them every time. An S3 cache stores cached build data in an Amazon S3 location. This can be useful for dependencies, package manager files, and other reusable content that changes less frequently than the application source code. During later builds, CodeBuild can restore the cache before executing the build commands, allowing the process to reuse available files. Cache configuration should be designed carefully because stale or unnecessary cached content can increase storage usage or cause unexpected build behavior. Proper cache paths and invalidation practices help maintain reliable build performance.

Question 204. Why is Docker layer caching useful in CodeBuild?

1. It creates IAM policies automatically
   2. It disables Docker commands
   3. It replaces Amazon ECR
   4. It can reuse unchanged Docker layers between builds

Correct Answer: 4. It can reuse unchanged Docker layers between builds

Explanation:

Docker images are constructed from multiple layers, and many layers may remain unchanged between builds. Docker layer caching allows CodeBuild to reuse previously created layers instead of rebuilding every layer from scratch. This can significantly reduce the time and resources required to create container images, especially when the Dockerfile contains stable dependency or operating-system layers followed by frequently changing application files. When implementing Docker builds in CodeBuild, the build environment must be configured appropriately for Docker operations, and the cache must be managed so that it remains useful without introducing stale content. Effective layer caching is especially valuable in frequent container-based CI workflows.

Question 205. What does an ECR pull-through cache provide?

1. Automatic EC2 patching
   2. Cached access to images from an upstream public registry
   3. Lambda function versioning
   4. CloudFormation stack recovery

Correct Answer: 2. Cached access to images from an upstream public registry

Explanation:

Amazon Elastic Container Registry pull-through cache rules allow an ECR repository to retrieve container images from supported upstream registries and cache them in an AWS-managed location. When an image is requested through the configured ECR path, ECR can retrieve it from the upstream registry when necessary and then make the image available through the ECR repository. Subsequent requests can use the cached image instead of repeatedly accessing the external registry. This can improve reliability, simplify network access, and provide better control over container image consumption. Organizations can also apply their existing ECR permissions, encryption, monitoring, and repository governance practices to the cached images.

Question 206. Which setting protects ECR images from being replaced by another image using the same tag?

1. Tag immutability
   2. CloudWatch Logs
   3. ECS desired count
   4. Lambda concurrency

Correct Answer: 1. Tag immutability

Explanation:

Amazon ECR tag immutability prevents an existing image tag from being overwritten by another image. Without immutability, a tag such as production or release could potentially be moved to a different image, making deployments less predictable. With immutable tags, once a tag is associated with an image, another image cannot reuse that same tag in the repository. This supports safer CI/CD practices because deployment systems can rely on a tag maintaining its original association. However, teams should still consider using image digests when they require an exact immutable reference to a specific image. Tag immutability is particularly helpful for preventing accidental or unauthorized image replacement.

Question 207. What is the purpose of ECR repository encryption?

1. To automatically deploy ECS services
   2. To change Dockerfile instructions
   3. To protect container images stored in the repository
   4. To increase task count

Correct Answer: 3. To protect container images stored in the repository

Explanation:

ECR repository encryption protects container images and associated data while they are stored in Amazon Elastic Container Registry. ECR supports encryption using AWS-managed or customer-managed AWS KMS keys depending on the repository configuration and requirements. Encryption helps protect image contents against unauthorized access to stored data, while IAM permissions and repository policies determine who can access or perform actions on the repository. In regulated or security-sensitive environments, customer-managed KMS keys can provide additional control over encryption-related permissions and key lifecycle management. Encryption is one part of a broader container security strategy that should also include access controls, vulnerability scanning, image lifecycle management, and secure deployment practices.

Question 208. Which ECS feature can automatically stop a failing deployment and roll it back?

1. ECS deployment circuit breaker
   2. Route 53 hosted zone
   3. S3 versioning
   4. IAM Access Analyzer

Correct Answer: 1. ECS deployment circuit breaker

Explanation:

The Amazon ECS deployment circuit breaker can help detect deployments that are unable to reach a stable state. When configured with rollback behavior, ECS can stop a failing deployment and return the service to the last deployment that reached a stable condition. This is useful for automated deployment pipelines because a failed application deployment does not necessarily need to remain active while engineers manually intervene. The circuit breaker works with ECS service deployments and evaluates whether tasks successfully progress toward a stable service. It should be combined with meaningful health checks, appropriate task configuration, and monitoring so that deployment failures are detected accurately and rollback behavior protects service availability.

Question 209. Which ECS setting delays health evaluation after a task starts?

1. Maximum healthy percentage
   2. Health check grace period
   3. Desired count
   4. Capacity provider weight

Correct Answer: 2. Health check grace period

Explanation:

The ECS service health check grace period gives newly started tasks time to initialize before the ECS service scheduler begins considering container health checks when determining whether a task should be considered unhealthy. This is useful for applications that require several seconds or minutes to start, establish connections, load configuration, or become ready to accept traffic. Without an appropriate grace period, ECS might interpret temporary startup failures as permanent health problems and repeatedly replace otherwise healthy tasks. The grace period should be long enough to accommodate normal startup behavior but not excessively long, because an overly large value can delay detection of genuinely failed deployments or unhealthy applications.

Question 210. What do ECS capacity providers help manage?

1. Distribution of tasks across compute capacity
   2. CloudFormation template syntax
   3. IAM password policies
   4. CodePipeline artifact encryption

Correct Answer: 1. Distribution of tasks across compute capacity

Explanation:

Amazon ECS capacity providers help control how ECS services and tasks use available compute capacity. Depending on the architecture, capacity providers can be associated with Amazon EC2 capacity or AWS Fargate and can be used with capacity provider strategies to influence how tasks are distributed. This allows organizations to design more flexible compute strategies instead of relying only on a fixed launch approach. For example, a service can use a capacity provider strategy to influence task placement across available capacity types. Capacity providers are especially useful when teams want ECS services to integrate more directly with their underlying compute capacity management and scaling approach.

Question 211. What does Lambda reserved concurrency primarily control?

1. Function log retention
   2. Maximum concurrent executions for a function
   3. S3 object versioning
   4. API Gateway cache size

Correct Answer: 2. Maximum concurrent executions for a function

Explanation:

AWS Lambda reserved concurrency establishes a dedicated concurrency limit for a specific function. It limits the maximum number of simultaneous executions that the function can consume and also reserves that amount of concurrency for the function from the account’s available concurrency pool. This can help prevent one function from consuming excessive account-level concurrency and affecting other functions. Reserved concurrency is different from provisioned concurrency, which keeps execution environments initialized to reduce startup latency. When configuring reserved concurrency, administrators should consider expected traffic, downstream service limits, and the function’s role within the application. Proper concurrency controls can protect both Lambda capacity and dependent services.

Question 212. What is the main benefit of Lambda provisioned concurrency?

1. It removes IAM permissions
   2. It stores container images
   3. It keeps execution environments initialized to reduce startup latency
   4. It creates CloudFormation stacks

Correct Answer: 3. It keeps execution environments initialized to reduce startup latency

Explanation:

Lambda provisioned concurrency keeps a configured number of execution environments initialized and ready to process requests. This can reduce the startup latency that may occur when Lambda needs to initialize a new execution environment, which is particularly important for latency-sensitive applications and APIs. Provisioned concurrency can be configured for specific Lambda function versions or aliases and can be adjusted according to expected demand. It does not eliminate the need for correct function configuration, monitoring, or concurrency management. Teams should balance the desired latency characteristics against the additional cost of keeping execution environments prepared. Provisioned concurrency is therefore a useful deployment and performance feature when predictable low-latency invocation behavior is important.

Question 213. Which AppConfig component validates configuration before deployment?

1. Validator
   2. Artifact store
   3. Capacity provider
   4. Deployment group

Correct Answer: 1. Validator

Explanation:

AWS AppConfig validators can check configuration data before it is deployed to an application. Validators help identify invalid configuration values or structures before those values reach running workloads. AppConfig supports validation approaches such as JSON Schema validation and Lambda-based validation, depending on the configuration requirements. This provides an important safety mechanism for configuration-driven deployments because a syntactically or logically incorrect configuration can potentially cause application failures even when the application code itself has not changed. Using validators as part of the deployment process helps enforce configuration quality and reduces the risk of publishing malformed or unacceptable settings to production environments.

Question 214. What does an AppConfig deployment strategy control?

1. IAM user creation
   2. ECR repository encryption
   3. CloudTrail log storage
   4. How configuration changes are gradually deployed

Correct Answer: 4. How configuration changes are gradually deployed

Explanation:

An AWS AppConfig deployment strategy determines how quickly a new configuration is made available to application clients. Instead of immediately exposing every client to a new configuration, AppConfig can use controlled deployment strategies that gradually increase the percentage of clients receiving the new configuration. This approach can reduce deployment risk because teams can observe application behavior as the configuration rollout progresses. Deployment strategies can include different growth rates and bake times depending on the desired rollout pattern. When combined with monitoring and deployment alarms, controlled configuration rollout can help detect problems early and support automatic rollback before a faulty configuration reaches the entire application population.

Question 215. Which CloudFormation policy controls what happens to a resource after stack deletion?

1. UpdatePolicy
   2. CreationPolicy
   3. DeletionPolicy
   4. StackPolicy

Correct Answer: 3. DeletionPolicy

Explanation:

The CloudFormation DeletionPolicy controls what CloudFormation should do with a resource when the resource is removed from a stack or when the stack itself is deleted, depending on the resource and operation. Common behaviors include deleting the resource, retaining it, or creating a snapshot for supported resource types. This is particularly important for stateful resources such as databases or storage because automatically deleting them could result in permanent data loss. A Retain policy can preserve a resource after stack deletion, while Snapshot can preserve supported resource data through a snapshot. DeletionPolicy should therefore be selected deliberately based on the resource’s data-retention and recovery requirements.

Question 216. What does CloudFormation CreationPolicy help coordinate?

1. Resource initialization completion
   2. IAM password rotation
   3. ECR image scanning
   4. Lambda concurrency

Correct Answer: 1. Resource initialization completion

Explanation:

A CloudFormation CreationPolicy can be used to prevent CloudFormation from considering certain resources successfully created until the expected initialization signals are received. This is particularly useful with resources such as EC2 instances that require additional configuration after infrastructure creation. A bootstrap process can perform installation or initialization tasks and then send a success signal to CloudFormation. CloudFormation waits for the configured conditions before continuing or declaring the resource creation successful. This helps coordinate infrastructure provisioning with application initialization and reduces the chance that later stack resources or outputs are treated as ready before the required setup has actually completed.

Question 217. What does CloudFormation UpdatePolicy primarily affect?

1. IAM policy evaluation
   2. How certain resources are updated
   3. CloudTrail event retention
   4. S3 bucket encryption

Correct Answer: 2. How certain resources are updated

Explanation:

CloudFormation UpdatePolicy provides specialized controls for how certain supported resources should be updated when a stack changes. A common example is an Auto Scaling group, where an update policy can control rolling updates or other update behavior. This allows infrastructure changes to be introduced in a controlled manner rather than replacing or modifying resources without considering application availability. UpdatePolicy is different from DeletionPolicy, which governs resource handling during removal, and CreationPolicy, which coordinates resource creation and initialization. Using appropriate update behavior can reduce disruption during infrastructure changes and can be an important part of safe infrastructure deployment practices.

Question 218. Which CloudFormation feature can process templates using custom transformations?

1. StackSets
   2. Drift detection
   3. Macros
   4. Outputs

Correct Answer: 3. Macros

Explanation:

CloudFormation macros allow templates to be transformed or processed before CloudFormation provisions the defined resources. A macro can perform custom transformations that modify or generate template content according to predefined logic. Macros can be useful when organizations need reusable abstractions or customized template processing beyond the standard CloudFormation syntax. They are different from nested stacks, which primarily help organize templates into reusable stack components, and from CloudFormation Hooks, which can enforce controls during resource operations. Because macros can significantly transform templates, they should be developed, tested, secured, and governed carefully. A poorly designed transformation could introduce unexpected resources or configuration changes into infrastructure deployments.

Question 219. Which EventBridge feature allows previously captured events to be processed again?

1. Event archive and replay
   2. IAM role chaining
   3. CloudFormation outputs
   4. ECR replication

Correct Answer: 1. Event archive and replay

Explanation:

Amazon EventBridge archives and replay features allow organizations to retain selected events and later replay those events to an event bus. This can be useful when testing new event-processing logic, recovering from an application issue, or validating a revised consumer without waiting for the original events to occur again. An archive stores matching events according to its configured retention period, while replay sends archived events back through EventBridge for processing. This capability is valuable in event-driven architectures because it provides a mechanism for controlled reprocessing of historical events. Teams should still design consumers to handle duplicate or repeated events safely when replay operations are used.

Question 220. What does an EventBridge retry policy control?

1. How long an S3 object is retained
   2. How many ECS tasks are created
   3. How CodeBuild stores artifacts
   4. How failed event delivery is retried

Correct Answer: 4. How failed event delivery is retried

Explanation:

An Amazon EventBridge retry policy controls how EventBridge attempts to deliver an event again when the target does not successfully process the event. Retry behavior can be configured to specify how long EventBridge should continue attempting delivery and how retry attempts are spaced. This is important for event-driven applications because temporary target failures should not necessarily result in immediate event loss. EventBridge can also work with dead-letter queues for events that cannot be successfully delivered after the configured retry behavior. Together, retry policies and dead-letter queues provide more resilient event delivery while giving operations teams a way to investigate events that could not reach their intended targets.