Amazon SOA-C02 AWS Certified SysOps Administrator - Associate Exam Practice Test

Answer : B

Scaling Policies in Auto Scaling:

When multiple scaling policies trigger at the same time, each policy is executed independently.

If both policies are set to add 5 instances when CPU utilization reaches 80%, they will both be executed when the threshold is met.

Therefore, the total number of instances added will be the sum of the instances specified in both policies.

In this case, 5 instances from one policy and 5 instances from the other policy will result in a total of 10 instances being added.

Steps to Configure and Verify Scaling Policies:

Go to the AWS Management Console.

Navigate to EC2 and select 'Auto Scaling Groups.'

Select your Auto Scaling group and review the scaling policies.

Ensure that both scaling policies are configured to trigger at 80% CPU utilization.

Monitor the Auto Scaling group's activity to verify the addition of instances when the CPU utilization threshold is reached.

Topic 2, Simulation

Answer : C, D

AWS Config Managed Rule for S3 Logging:

The s3-bucket-logging-enabled AWS Config rule checks whether S3 buckets have logging enabled.

Steps:

Go to the AWS Management Console.

Navigate to AWS Config.

Create a rule using s3-bucket-logging-enabled.

Add a remediation action using an AWS Lambda function or Systems Manager Automation runbook.

Using AWS Lambda for Remediation:

Create a Lambda function that enables logging on S3 buckets.

Steps:

Write a Lambda function in Python or Node.js to enable logging.

Configure the function to trigger on non-compliant buckets.

Using AWS Systems Manager Automation:

The AWS-ConfigureS3BucketLogging runbook automates enabling logging.

Steps:

Go to the AWS Management Console.

Navigate to Systems Manager.

Create an Automation document or use the existing AWS-ConfigureS3BucketLogging runbook.

Configure the remediation action to use this runbook.

Answer : A, C

Enable Access Logging for the ALB:

Access logging provides detailed information about requests sent to your load balancer.

Steps:

Go to the AWS Management Console.

Navigate to EC2 and select 'Load Balancers.'

Select your Application Load Balancer.

Under the 'Attributes' tab, enable 'Access logs.'

Specify an S3 bucket where the logs will be saved.

Use Amazon Athena to Query the ALB Logs:

Athena allows you to run SQL queries on data stored in S3.

Steps:

Go to the AWS Management Console.

Navigate to Athena.

Create a table for the ALB logs using the appropriate schema.

Run queries to calculate the total bytes sent and received, grouped by the target

field.

Example query:

SELECT target, SUM(received_bytes) as total_received, SUM(sent_bytes) as total_sent

FROM alb_logs

GROUP BY target, port

Answer : B

Enabling Instance Scale-In Protection:

Instance scale-in protection prevents Auto Scaling from terminating specific instances.

Steps:

Go to the AWS Management Console.

Navigate to EC2 and select 'Auto Scaling Groups.'

Select your Auto Scaling group.

Go to the 'Instance management' tab.

Select the instances you want to protect and click 'Actions.'

Choose 'Enable scale-in protection.'

This ensures that instances are not terminated during troubleshooting.

Answer : A, C, E

Create an IAM role with the CloudWatchAgentServerPolicy:

This policy grants the necessary permissions for the CloudWatch agent to collect and send metrics.

Steps:

Go to the AWS Management Console.

Navigate to IAM and create a new role.

Choose 'EC2' as the trusted entity.

Attach the 'CloudWatchAgentServerPolicy' managed policy to the role.

Attach this IAM role to your EC2 instances.

Install and start the CloudWatch agent:

The CloudWatch agent must be installed and configured to collect disk utilization metrics.

Steps:

Use AWS Systems Manager or SSH to connect to your instances.

Install the CloudWatch agent using the following commands:

sudo yum install amazon-cloudwatch-agent

sudo /opt/aws/amazon-cloudwatch-agent/bin/amazon-cloudwatch-agent-config-wizard

sudo /opt/aws/amazon-cloudwatch-agent/bin/amazon-cloudwatch-agent-ctl -a fetch-config -m ec2 -c file:/path/to/your-config-file.json -s

Start the agent:

sudo systemctl start amazon-cloudwatch-agent

Configure a CloudWatch alarm:

Create an alarm based on the disk_used_percent metric.

Steps:

Go to the AWS Management Console.

Navigate to CloudWatch and select 'Alarms' from the left-hand menu.

Click on 'Create alarm.'

Select the disk_used_percent metric.

Set the threshold to 80% and configure the alarm actions (e.g., sending a notification).

Answer : A

Amazon CloudWatch Synthetics:

CloudWatch Synthetics allows you to create canaries to monitor your endpoints and API calls, simulating user behavior to detect issues before users do.

Steps:

Go to the AWS Management Console.

Navigate to CloudWatch and select 'Synthetics.'

Click on 'Create canary.'

Choose 'Heartbeat monitoring' as the blueprint.

Configure the canary to point to the FQDN of the website.

Set the frequency and retention settings as per your requirement.

Create the canary.

This setup continuously checks the operational status of your website, alerting you if it becomes unreachable or has issues.

Answer : D

Aurora Auto Scaling:

Aurora Auto Scaling adjusts the number of Aurora Replicas in response to changes in connectivity or workload.

Steps:

Go to the AWS Management Console.

Navigate to RDS and select the Aurora cluster.

Under 'Actions,' choose 'Add Aurora Replica' to initially add replicas if needed.

Go to the 'Auto Scaling' section and create an auto scaling policy.

Set the target value for the DatabaseConnections metric to 195.

Define the minimum and maximum number of replicas.

Save the configuration.

This ensures that the Aurora cluster scales automatically when the number of connections approaches the threshold, improving read performance.