A company is implementing an Amazon Elastic Container Service (Amazon ECS) cluster to run its workload.
The company architecture will run multiple ECS services on the cluster.
The architecture includes an Application Load Balancer on the front end and uses multiple target groups to route traffic.
A DevOps engineer must collect application and access logs.
The DevOps engineer then needs to send the logs to an Amazon S3 bucket for near-real-time analysis.
Which combination of steps must the DevOps engineer take to meet these requirements? (Choose three.)
Q1
The Correct Answers are:
✅ Option B: Install the Amazon CloudWatch Logs agent on the ECS instances. Change the logging driver in the ECS task definition to awslogs.
✅ Option D: Activate access logging on the ALB. Then point the ALB directly to the logging S3 bucket.
✅ Option F: Create an Amazon Kinesis Data Firehose delivery stream that has a destination of the logging S3 bucket. Then create an Amazon CloudWatch Logs subscription filter for Kinesis Data Firehose.
✅ Here's why:
✅ Comprehensive Log Collection: Installing the CloudWatch Logs agent and changing the ECS task definition to use the awslogs driver allows for the collection of application logs directly from the ECS instances. This step ensures that application logs are captured in real-time and sent to CloudWatch Logs, providing visibility into the application's operation.
✅ Access Logging for Load Balancer: Activating access logging on the ALB and directing these logs to an S3 bucket captures information about the requests made to the ALB. This provides valuable insights into the traffic patterns and helps in identifying any potential issues at the load balancer level, such as unauthorized access attempts or spikes in traffic.
✅ Integration with Kinesis Data Firehose for Real-time Analysis: Creating a Kinesis Data Firehose delivery stream to send logs from CloudWatch Logs to an S3 bucket enables near-real-time log analysis. The use of a subscription filter for Kinesis Data Firehose allows for the automated, continuous delivery of logs to S3, facilitating immediate analysis and long-term storage.
🔴 Now, let's examine why the other options are not the best choice:
❌ Option A: While it mentions updating service definitions for logging, the approach of using a container instance from AWS as a task for logging is not a standard practice for capturing logs for analysis. This option does not directly contribute to the requirement of sending logs to S3 for analysis.
❌ Option C: Using EventBridge to schedule a Lambda function to export logs every 60 seconds introduces unnecessary complexity and potential delays in log processing. The direct integration of logging services with S3 via Kinesis Data Firehose provides a more efficient and streamlined approach.
❌ Option E: Activating access logging on target groups is not mentioned as a feature within AWS services, making this option not applicable to the scenario. Access logging is typically configured on the load balancer rather than on individual target groups.
A1
A company that uses electronic health records is running a fleet of Amazon EC2 instances with an Amazon Linux operating system.
As part of patient privacy requirements, the company must ensure continuous compliance for patches for operating system and applications running on the EC2 instances.
How can the deployments of the operating system and application patches be automated using a default and custom repository?
Q2
The Correct Answer is:
✅ Option A: Use AWS Systems Manager to create a new patch baseline including the custom repository. Execute the AWS-RunPatchBaseline document using the run command to verify and install patches.
✅ Here's why:
✅ Compliance with Patient Privacy Requirements: By using AWS Systems Manager to automate the patching process, the company ensures that EC2 instances are continuously compliant with patient privacy requirements by applying the latest patches for both the operating system and applications.
✅ Custom Repository Integration: Including the custom repository in the new patch baseline allows for the automation of patches not only from default Amazon Linux repositories but also from corporate or third-party repositories, ensuring comprehensive coverage of all necessary software updates.
✅ Operational Efficiency: Automating the patch deployment process using AWS Systems Manager's AWS-RunPatchBaseline document streamlines the maintenance tasks. It ensures that patches are verified and installed without manual intervention, reducing the risk of human error and operational overhead.
🔴 Now, let's examine why the other options are not the best choice:
❌ Option B: AWS Direct Connect is primarily used for establishing a dedicated network connection from one's premises to AWS. While it can facilitate the integration of corporate repositories, it does not directly address the deployment of patches or compliance reporting through CloudWatch.
❌ Option C: While using yum-config-manager to add and enable a custom repository on EC2 instances is a valid technical approach, it requires manual execution and does not inherently provide the automation or compliance tracking needed for patient privacy requirements.
❌ Option D: This option incorrectly suggests using the AWS-AmazonLinuxDefaultPatchBaseline document for a custom repository, which might not align with the specific requirements for including custom patches. The primary focus here is on automating patch compliance, including both default and custom repositories, which is more directly addressed by Option A.
A2
A company is using AWS CodePipeline to automate its release pipeline.
AWS CodeDeploy is being used in the pipeline to deploy an application to Amazon ECS using the blue/green deployment model.
The company wants to implement scripts to test the green version of the application before shifting traffic.
These scripts will complete in 5 minutes or less.
If errors are discovered during these tests, the application must be rolled back.
Which strategy will meet these requirements?
Q3
The Correct Answer is:
✅ Option C: Add a hooks section to the CodeDeploy AppSpec file. Use the AfterAllowTestTraffic lifecycle event to invoke an AWS Lambda function to run the test scripts. If errors are found, exit the Lambda function with an error to trigger rollback.
✅ Here's why:
✅ Integrated Testing and Rollback Mechanism: Utilizing the AfterAllowTestTraffic lifecycle event within the CodeDeploy AppSpec file allows the testing phase to be seamlessly integrated into the deployment process. This event is specifically designed for testing the new version (green environment) before traffic is fully shifted from the old version (blue environment).
✅ Use of AWS Lambda for Testing: By invoking an AWS Lambda function to run test scripts, the solution leverages AWS's serverless compute service to execute tests without provisioning or managing servers. This approach ensures that the testing process is scalable, cost-effective, and capable of automatically handling errors.
✅ Automatic Rollback on Error Detection: Exiting the AWS Lambda function with an error in case test scripts identify issues triggers an automatic rollback mechanism within AWS CodeDeploy. This ensures that if the new version of the application does not meet the required standards, the deployment process is halted, and the application reverts to the previous stable version, thereby minimizing potential impact on end-users.
🔴 Now, let's examine why the other options are not the best choice:
❌ Option A & Option B: Adding a stage to CodePipeline for testing prior to deployment does not leverage the built-in lifecycle events of AWS CodeDeploy for blue/green deployments, potentially complicating the rollback process if the new version fails the tests.
❌ Option D: The AfterAllowTraffic lifecycle event occurs after traffic has already been shifted to the new version, which might not be as effective for preventing impact on end-users if errors are discovered during tests. It's more efficient to test and potentially rollback before traffic is shifted, as facilitated by the AfterAllowTestTraffic event.
A3
A company uses AWS Storage Gateway in file gateway mode in front of an Amazon S3 bucket that is used by multiple resources.
In the morning when business begins, users do not see the objects processed by a third party the previous evening.
When a DevOps engineer looks directly at the S3 bucket, the data is there, but it is missing in Storage Gateway.
Which solution ensures that all the updated third-party files are available in the morning?
Q4
The Correct Answer is:
✅ Option A: Configure a nightly Amazon EventBridge (Amazon CloudWatch Events) event to trigger an AWS Lambda function to run the RefreshCache command for Storage Gateway.
✅ Here's why:
✅ Immediate Visibility of Updated Files: The RefreshCache command forces the Storage Gateway to check for and reflect any updates made directly to the S3 bucket. This ensures that the latest files processed by the third party and stored in S3 are visible and accessible through the file gateway in the morning.
✅ Automation of Cache Refresh Process: By automating this process with Amazon EventBridge (formerly CloudWatch Events) and AWS Lambda, the solution eliminates manual intervention, ensuring that the cache is consistently refreshed on a nightly basis without fail.
✅ Optimized for File Gateway Mode: This solution is directly applicable to AWS Storage Gateway in file gateway mode, where the synchronization between the S3 bucket and the Storage Gateway's cache can lag. The proposed solution directly addresses and resolves this lag by ensuring the cache is refreshed to include the latest S3 content.
🔴 Now, let's examine why the other options are not the best choice:
❌ Option B: While instructing the third party to use AWS Transfer for SFTP to put data into the S3 bucket may streamline the upload process, it does not address the issue of making sure that newly uploaded files are visible in the Storage Gateway without a manual refresh.
❌ Option C: Modifying Storage Gateway to run in volume gateway mode changes the functionality and use case of the Storage Gateway and does not address the need for automatic visibility of updates made directly to the S3 bucket.
❌ Option D: S3 same-Region replication is a method for replicating objects across S3 buckets within the same AWS Region. It does not directly address the challenge of refreshing the Storage Gateway's cache to reflect new or updated files in the S3 bucket.
A4
A DevOps Engineer needs to back up sensitive Amazon S3 objects that are stored within an S3 bucket with a private bucket policy using the S3 cross-region replication functionality.
The objects need to be copied to a target bucket in a different AWS Region and account.
Which actions should be performed to enable this replication? (Choose three.)
Q5
The Correct Answers are:
✅ Option A: Create a replication IAM role in the source account.
✅ Option D: Add statements to the target bucket policy allowing the replication IAM role to replicate objects.
✅ Option E: Create a replication rule in the source bucket to enable the replication.
✅ Here's why:
✅ IAM Role Creation in Source Account: Creating a replication IAM role in the source account is necessary to grant S3 permission to replicate objects on behalf of the source bucket to the target bucket, especially when the target bucket is in a different account.
✅ Policy Statement on Target Bucket: Adding statements to the target bucket policy to allow the replication IAM role from the source account to replicate objects is essential for cross-account replication. This ensures that the target bucket explicitly permits actions initiated by the replication role, addressing cross-account access control.
✅ Replication Rule in Source Bucket: Creating a replication rule in the source bucket is critical to define which objects to replicate, where to replicate them, and what role to use for replication. This step directly enables the replication process by specifying the conditions under which replication should occur and identifying the target bucket for replication.
🔴 Now, let's examine why the other options are not the best choice:
❌ Option B: While creating a replication IAM role in the target account might seem necessary, for S3 cross-region replication, the role is typically created in the source account, and permissions are granted to this role to replicate objects to the target bucket.
❌ Option C: Adding statements to the source bucket policy is not required for enabling replication. Replication permissions are primarily managed through the replication role and the target bucket policy.
❌ Option F: There is no need to create a replication rule in the target bucket. Replication rules are configured in the source bucket to dictate the replication process. The target bucket's role is to receive the replicated objects, governed by the permissions set in its bucket policy.
A5
A company has multiple child accounts that are part of an organization in AWS Organizations.
The security team needs to review every Amazon EC2 security group and their inbound and outbound rules.
The security team wants to programmatically retrieve this information from the child accounts using an AWS Lambda function in the master account of the organization.
Which combination of access changes will meet these requirements? (Choose three.)
Q6
The Correct Answers are:
✅ Option B: Create a trust relationship that allows users in the master account to assume the IAM roles of the child accounts.
✅ Option C: Create an IAM role in each child account that has access to the AmazonEC2ReadOnlyAccess managed policy.
✅ Option E: Create an IAM role in the master account that allows the sts:AssumeRole action against the child account IAM role's ARN.
✅ Here's why:
✅ Cross-Account Access: Creating a trust relationship that allows the master account to assume roles in the child accounts is essential for centralized management and review of resources, like EC2 security groups, across the organization. This setup facilitates secure cross-account access without sharing credentials.
✅ Necessary Permissions: By assigning the AmazonEC2ReadOnlyAccess managed policy to the roles in each child account, you ensure that the Lambda function in the master account has read-only access to EC2 instances and security group information, aligning with the principle of least privilege.
✅ Secure Role Assumption: The role in the master account designed to assume child account roles needs the sts:AssumeRole permission for those child account roles' ARNs. This setup streamlines the process of accessing resources across accounts securely and programmatically.
🔴 Now, let's examine why the other options are not the best choice:
❌ Option A & Option D: These options suggest a reverse trust relationship, which is not required for the scenario described. The master account needs to access resources in the child accounts, not the other way around.
❌ Option F: While creating an IAM role in the master account with AmazonEC2ReadOnlyAccess provides direct access within the master account, it doesn't facilitate access to resources in child accounts, which is the primary requirement.
A6
A space exploration company receives telemetry data from multiple satellites.
Small packets of data are received through Amazon API Gateway and are placed directly into an Amazon Simple Queue Service (Amazon SOS) standard queue.
A custom application is subscribed to the queue and transforms the data into a standard format.
Because of inconsistencies in the data that the satellites produce, the application is occasionally unable to transform the data.
In these cases, the messages remain in the SQS queue.
A DevOps engineer must develop a solution that retains the failed messages and makes them available to scientists for review and future processing.
Which solution will meet these requirements?
Q7
The Correct Answer is:
✅ Option C: Create an SOS dead-letter queue. Modify the existing queue by including a redrive policy that sets the Maximum Receives setting to 1 and sets the dead-letter queue ARN to the ARN of the newly created queue. Instruct the scientists to use the dead-letter queue to review the data that is not valid. Reprocess this data at a later time.
✅ Here's why:
✅ Efficient Handling of Unprocessable Messages: The use of a dead-letter queue (DLQ) for messages that cannot be processed (due to data inconsistencies or other issues) ensures that these messages are not lost. Instead, they are stored safely for review and rectification. This mechanism directly addresses the challenge of dealing with messages that the primary application cannot process.
✅ Simplified Review and Correction Process: By directing messages that fail processing to a DLQ, the solution provides a straightforward way for scientists or data analysts to access, review, and correct the data. This approach facilitates an efficient workflow for managing and rectifying data issues.
✅ Maintains Queue Efficiency: Including a redrive policy that automatically redirects messages to the DLQ after a specified number of unsuccessful processing attempts helps maintain the efficiency and cleanliness of the main SQS queue. This prevents the main queue from being clogged with unprocessable messages, ensuring that new, valid messages are received and processed in a timely manner.
🔴 Now, let's examine why the other options are not the best choice:
❌ Option A & Option B: These options involve more complex setups that might not directly address the requirement for storing failed messages for later review. Additionally, they require more operational overhead and may not provide a straightforward way for scientists to access and correct the data.
❌ Option D: Configuring API Gateway and using virtual queues would complicate the architecture unnecessarily for the given requirement. The solution should focus on efficiently managing and correcting failed messages rather than altering the message input mechanism.
A7
A company wants to use AWS CloudFormation for infrastructure deployment.
The company has strict tagging and resource requirements and wants to limit the deployment to two Regions.
Developers will need to deploy multiple versions of the same application.
Which solution ensures resources are deployed in accordance with company policy?
Q8
The Correct Answer is:
✅ Option D: Create AWS Service Catalog products with approved CloudFormation templates.
✅ Here's why:
✅ Control and Compliance: AWS Service Catalog allows organizations to create and manage catalogs of IT services that are approved for use on AWS. By using AWS Service Catalog, the company can ensure that all resources deployed via CloudFormation templates meet the company's strict tagging and resource requirements, as only pre-approved templates are made available to developers.
✅ Regional Deployment Limitation: With AWS Service Catalog, the company can control which regions the approved CloudFormation templates can be deployed in. This directly addresses the company's requirement to limit deployment to two regions, ensuring compliance with geographic or regulatory constraints.
✅ Versioning and Multiple Deployments: AWS Service Catalog supports versioning of products (which in this case would be CloudFormation templates). This feature enables developers to deploy multiple versions of the same application, catering to the need for flexibility in testing, staging, and production environments without compromising on policy compliance.
🔴 Now, let's examine why the other options are not the best choice:
❌ Option A: While AWS Trusted Advisor provides valuable insights into best practices and potential configuration issues, it is more reactive than proactive. It would not prevent unapproved deployments but rather identify them after the fact, which might not meet the company's policy enforcement goals.
❌ Option B: CloudFormation drift detection helps identify configuration drifts from the last known state of the stack but does not inherently limit resource deployment to specific regions or enforce tagging policies prior to deployment.
❌ Option C: Although CloudFormation StackSets can deploy stacks across multiple AWS accounts and regions, using StackSets alone does not provide a mechanism for ensuring that only approved templates are used, nor does it offer the catalog and product management features that AWS Service Catalog does for compliance and governance.
A8
A company requires that its internally facing web application be highly available.
The architecture is made up of one Amazon EC2 web server instance and one NAT instance that provides outbound internet access for updates and accessing public data.
Which combination of architecture adjustments should the company implement to achieve high availability? (Choose two.)
Q9
The Correct Answers are:
✅ Option B: Create additional EC2 instances spanning multiple Availability Zones. Add an Application Load Balancer to split the load between them.
✅ Option D: Replace the NAT instance with a NAT gateway in each Availability Zone. Update the route tables.
✅ Here's why:
✅ High Availability Through Redundancy: By creating additional EC2 instances across multiple Availability Zones, the company ensures that the web application remains available even if one zone goes down. This geographic distribution of resources enhances the overall availability and reliability of the application.
✅ Efficient Traffic Distribution: An Application Load Balancer intelligently distributes incoming application traffic across multiple targets, such as EC2 instances, in multiple Availability Zones. This not only improves the fault tolerance of the application but also optimizes performance by routing traffic to the most available and capable resources.
✅ Enhanced Scalability and Reliability with NAT Gateways: Replacing a single NAT instance with NAT gateways in each Availability Zone eliminates a single point of failure and provides built-in redundancy. NAT gateways are managed services, offering higher availability and bandwidth compared to NAT instances. They automatically scale to accommodate traffic load without the need to manually update route tables for each Availability Zone, simplifying network management and enhancing security for outbound traffic.
🔴 Now, let's examine why the other options are not the best choice:
❌ Option A: While adding the NAT instance to an Auto Scaling group could provide some level of high availability, NAT instances are manually managed and do not offer the same level of reliability and scalability as NAT gateways.
❌ Option C: Configuring an Application Load Balancer and CloudWatch alarms can improve the availability of the web server instance. However, it does not address the requirement for outbound internet access provided by the NAT instance or gateway, nor does it ensure redundancy across multiple Availability Zones for the NAT functionality.
❌ Option E: NAT gateways do not inherently span multiple Availability Zones; instead, you deploy them in each Availability Zone and route traffic accordingly. This option misunderstands the architecture of NAT gateways in AWS.
A9
A DevOps Engineer is building a multi-stage pipeline with AWS CodePipeline to build, verify, stage, test, and deploy an application.
There is a manual approval stage required between the test and deploy stages.
The Development team uses a team chat tool with webhook support.
How can the Engineer configure status updates for pipeline activity and approval requests to post to the chat tool?
Q10
The Correct Answer is:
✅ Option C: Create an AWS CloudWatch Events rule that filters on "CodePipeline Pipeline Execution State Change." Forward that to an Amazon SNS topic. Subscribe an AWS Lambda function to the Amazon SNS topic and have it forward the event to the chat webhook URL.
✅ Here's why:
✅ Direct Integration with CodePipeline Events: AWS CloudWatch Events can directly monitor and capture specific events from AWS CodePipeline, including state changes such as the initiation of a manual approval stage. This provides a real-time and automated way to capture pipeline status updates.
✅ Flexible Notification Mechanism: By forwarding these events to an Amazon SNS topic, the solution leverages a highly scalable and flexible notification service that can integrate with various endpoints, including AWS Lambda. This setup allows for custom processing or direct notification delivery based on the event details.
✅ Custom Processing with AWS Lambda: Subscribing an AWS Lambda function to the SNS topic allows for custom logic to be applied to the event data before forwarding it to the chat tool. This step is crucial for formatting the message appropriately for the chat tool's webhook URL, ensuring that the notification is both informative and adheres to the chat tool's requirements.
🔴 Now, let's examine why the other options are not the best choice:
❌ Option A: While creating a CloudWatch Logs subscription can capture logs and forward them, this approach is more suited for log data rather than acting on specific CodePipeline state change events for notification purposes.
❌ Option B: Triggering a Lambda function based on CloudTrail event log updates is a valid approach for capturing AWS API activity but may introduce unnecessary complexity and delay for this specific use case of pipeline state change notifications.
❌ Option D: Modifying the pipeline code to send notifications directly might work but lacks the centralization and ease of management provided by using AWS managed services like CloudWatch Events and SNS. It also requires additional coding and maintenance effort for each pipeline.
A10