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Amazon AWS Certified CloudOps Engineer - Associate Sample Questions (Q190-Q195):
NEW QUESTION # 190
A CloudOps engineer must ensure that all of a company's current and future Amazon S3 buckets have logging enabled. If an S3 bucket does not have logging enabled, an automated process must enable logging for the S3 bucket.
Which solution will meet these requirements?
- A. Configure an S3 bucket policy that requires all current and future S3 buckets to have logging enabled.
- B. Use the s3-bucket-logging-enabled AWS Config managed rule. Add a remediation action that uses the AWS-ConfigureS3BucketLogging AWS Systems Manager Automation runbook.
- C. Use the s3-bucket-logging-enabled AWS Config managed rule. Add a remediation action that uses an AWS Lambda function to enable logging.
- D. Use AWS Trusted Advisor to perform a check for S3 buckets that do not have logging enabled.
Configure the check to enable logging for S3 buckets that do not have logging enabled.
Answer: B
Explanation:
Comprehensive Explanation (250-350 words):
AWS Config is designed to continuously evaluate AWS resource configurations and detect noncompliance.
The s3-bucket-logging-enabled managed rule specifically checks whether server access logging is enabled on S3 buckets. This directly meets the detection requirement for both current and future buckets.
To satisfy the remediation requirement, AWS Config supports automatic remediation actions. Using the AWS-provided AWS-ConfigureS3BucketLogging Systems Manager Automation runbook enables logging without custom code. This reduces operational overhead, avoids Lambda function maintenance, and aligns with AWS best practices.
Option A is incorrect because Trusted Advisor does not support automatic remediation. Option B cannot enforce logging at creation time through bucket policies alone. Option C works but introduces unnecessary Lambda maintenance compared to using an AWS-managed automation runbook.
Thus, combining AWS Config managed rules with Systems Manager Automation provides continuous compliance with minimal operational effort.
NEW QUESTION # 191
A company asks a SysOps administrator to provision an additional environment for an application in four additional AWS Regions. The application is running on more than 100 Amazon EC2 instances in the us-east-
1 Region, using fully configured Amazon Machine Images (AMIs). The company has an AWS CloudFormation template to deploy resources in us-east-1.
What should the SysOps administrator do to provision the application in the MOST operationally efficient manner?
- A. Run the existing CloudFormation template in each additional Region based on the success of the template that is used currently in us-east-1.
- B. Update the CloudFormation template to include the additional Regions in the Auto Scaling group.Update the existing stack in us-east-1.
- C. Copy the AMI to each Region by using the aws ec2 copy-image command. Update the CloudFormation template to include mappings for the copied AMIs.
- D. Create a snapshot of the running instance. Copy the snapshot to the other Regions. Create an AMI from the snapshots. Update the CloudFormation template for each Region to use the new AMI.
Answer: C
Explanation:
Comprehensive and Detailed Explanation From Exact Extract of AWS CloudOps Documents:
The most operationally efficient approach is A: copy the AMI to each target Region using copy-image and update the CloudFormation template to reference the correct AMI IDs per Region (commonly via Mappings or parameters). AMIs are regional resources, so an AMI built in us-east-1 cannot be launched directly in other Regions without copying. The copy-image operation is the standard, supported method to replicate an AMI across Regions while preserving the image configuration and backing snapshots in the destination Region.
Once AMIs exist in each Region, CloudFormation can be executed in each Region using the same template logic. Adding mappings for AMI IDs keeps the deployment consistent and repeatable, aligning with Infrastructure as Code practices and minimizing manual steps.
Option B is more work than necessary because copying snapshots and re-creating AMIs adds extra steps and increases the chance of inconsistency. Option C is incomplete because the template will fail or launch incorrect resources if it references an AMI ID that does not exist in the target Region. Option D is not feasible because an Auto Scaling group is a regional construct and cannot span multiple Regions from a single stack update in us-east-1.
References:
Amazon EC2 User Guide - Copy an AMI across Regions (copy-image) and AMI regional scope AWS CloudFormation User Guide - Mappings/parameters for Region-specific values AWS SysOps Administrator Study Guide - Multi-Region provisioning and automation best practices
NEW QUESTION # 192
A company uses memory-optimized Amazon EC2 instances behind a Network Load Balancer (NLB) to run an application. The company launched the EC2 instances from an AWS-provided Red Hat Enterprise Linux (RHEL) AMI.
A CloudOps engineer must monitor RAM utilization in 5-minute intervals. The CloudOps engineer must ensure that the EC2 instances scale in and out appropriately based on incoming load.
Which solution will meet these requirements?
- A. Configure basic monitoring for the EC2 instances. Use the standard mem_used_percent metric for monitoring. Create an EC2 Auto Scaling group and Auto Scaling policy that is based on the mem_used_percent metric.
- B. Configure detailed monitoring for the EC2 instances. Configure the Amazon CloudWatch agent on the EC2 instances. Create an EC2 Auto Scaling group and Auto Scaling policy that is based on the mem_active metric.
- C. Configure detailed monitoring for the EC2 instances. Use the mem_used_percent metric that the detailed monitoring feature provides. Create an IAM role that allows the CloudWatch agent to upload data. Create an EC2 Auto Scaling group and Auto Scaling policy that is based on the mem_used_percent metric.
- D. Configure basic monitoring for the EC2 instances. Configure the Amazon CloudWatch agent on the EC2 instances. Create an IAM role that allows the CloudWatch agent to upload data. Create an EC2 Auto Scaling group and Auto Scaling policy that is based on the mem_used_percent metric.
Answer: D
Explanation:
EC2 does not publish RAM utilization as a native CloudWatch metric by default. Memory metrics such as mem_used_percent are typically collected by the CloudWatch Agent, which runs on the instance and publishes custom metrics to CloudWatch. Because the requirement is RAM utilization at 5-minute intervals, the CloudWatch Agent can be configured to emit metrics at that cadence (or faster).
"Detailed monitoring" for EC2 mainly affects EC2-provided metrics (like CPU) by changing the period from
5 minutes (basic) to 1 minute (detailed). It does not magically provide memory utilization. Therefore, the key requirement is installing/configuring the CloudWatch Agent and ensuring it has permissions to publish metrics (via an IAM role attached to the instance / instance profile).
Option C correctly combines: (1) basic monitoring (fine for the ask), (2) CloudWatch Agent to publish mem_used_percent, (3) IAM role permissions to allow publishing, and (4) Auto Scaling policy that scales based on the memory metric.
Option B incorrectly implies detailed monitoring provides mem_used_percent (it does not). Option D assumes a "standard" memory metric exists without the agent, which is not correct. Option A references mem_active, which is not the typical metric name exposed by CloudWatch Agent's standard memory measurements for scaling policies, and also omits the IAM role requirement needed for publishing custom metrics.
Thus, C is the AWS-correct path for memory-based scaling using CloudWatch custom metrics.
NEW QUESTION # 193
A CloudOps engineer wants to configure observability of specific metrics for a public website that runs on Amazon Elastic Kubernetes Service (Amazon EKS). The CloudOps engineer wants to observe latency, traffic, errors, and saturation metrics. The CloudOps engineer wants to define service level objectives (SLOs) and monitor service level indicators (SLIs). The CloudOps engineer also wants to correlate metrics, logs, and traces to support faster issue resolution.
Which solution will meet these requirements with the LEAST operational effort?
- A. Configure AWS Distro for OpenTelemetry and use Amazon Managed Service for Prometheus and Amazon Managed Grafana.
- B. Configure Amazon CloudWatch Application Insights.
- C. Configure Amazon CloudWatch RUM and CloudWatch Synthetics canaries.
- D. Use Amazon CloudWatch Application Signals to automatically collect and monitor the specified metrics for the EKS workloads.
Answer: D
Explanation:
Amazon CloudWatch Application Signals is designed to provide built-in observability for containerized workloads, including Amazon EKS. It automatically collects golden signals such as latency, traffic, errors, and saturation without requiring complex instrumentation.
Application Signals supports SLO definition and SLI monitoring and correlates metrics, logs, and traces within CloudWatch. This significantly reduces operational overhead compared to manually configuring OpenTelemetry pipelines, Prometheus, and Grafana.
CloudWatch RUM and Synthetics focus on frontend monitoring, not backend service observability.
Application Insights does not provide full SLO/SLI support for EKS workloads.
Therefore, CloudWatch Application Signals is the correct and least-effort solution.
NEW QUESTION # 194
A company's security policy requires incoming SSH traffic to be restricted to a defined set of addresses. The company is using an AWS Config rule to check whether security groups allow unrestricted incoming SSH traffic.
A CloudOps engineer discovers a noncompliant resource and fixes the security group manually. The CloudOps engineer wants to automate the remediation of other noncompliant resources.
What is the MOST operationally efficient solution that meets these requirements?
- A. Configure an automatic remediation action on the AWS Config rule using AWS- DisableIncomingSSHOnPort22.
- B. Create an EventBridge rule for AWS Config events and invoke a Lambda function.
- C. Run a scheduled Lambda function to inspect and remediate security groups.
- D. Create a CloudWatch alarm for the AWS Config rule and invoke a Lambda function to remediate.
Answer: A
Explanation:
AWS Config supports automatic remediation for both managed and custom rules. When a resource is found noncompliant, AWS Config can automatically invoke an AWS Systems Manager Automation document to remediate the issue. The managed automation document AWS-DisableIncomingSSHOnPort22 is specifically designed to remove unrestricted SSH access (0.0.0.0/0) from security group inbound rules.
This approach is the most operationally efficient because it requires no custom code, no event orchestration, and no ongoing maintenance. The remediation runs immediately when AWS Config detects noncompliance and ensures consistent enforcement of security policy across all applicable resources.
Options A, C, and D rely on Lambda functions and event-driven glue logic, which significantly increase operational overhead, complexity, and long-term maintenance costs. These approaches are unnecessary when AWS provides a fully managed remediation capability.
Therefore, configuring an automatic remediation action directly on the AWS Config rule is the correct and most efficient solution.
NEW QUESTION # 195
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