Amazon SOA-C02 Practice Test - Questions Answers, Page 38

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.

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.

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).

Step Scaling Policy:

Step scaling policies allow you to define scaling actions based on different levels of CloudWatch alarms.

Steps:

Go to the AWS Management Console.

Navigate to EC2 Auto Scaling.

Select your Auto Scaling group.

Create or edit a scaling policy and choose 'Step scaling.'

Define different steps based on CloudWatch alarm thresholds (e.g., CPU usage or request count).

Configure larger adjustments for higher thresholds and smaller adjustments for lower thresholds.

Example Configuration:

For CPU > 80%, increase capacity by 4 instances.

For CPU > 60%, increase capacity by 2 instances.

For CPU > 40%, increase capacity by 1 instance.

NAT Gateway Setup:

A NAT gateway allows instances in a private subnet to connect to the internet or other AWS services, but prevents the internet from initiating a connection with those instances.

Steps:

Go to the AWS Management Console.

Navigate to VPC and select 'NAT Gateways.'

Create a NAT gateway in the public subnet of each Availability Zone.

Allocate an Elastic IP address to each NAT gateway.

Update the route tables for the private subnets to route internet-bound traffic to the NAT gateways.

Cluster Placement Group:

Cluster placement groups are used to ensure low-latency networking between EC2 instances. They place instances physically close to each other within the same Availability Zone.

Steps:

Go to the AWS Management Console.

Navigate to EC2 and select 'Placement Groups.'

Create a new cluster placement group.

Back up the existing EC2 instance to an AMI.

Launch new EC2 instances from the AMI into the cluster placement group.

Ensure all instances are in the same Availability Zone.

Content-MD5 Header:

The Content-MD5 header provides an MD5 checksum of the object being uploaded. Amazon S3 uses this checksum to verify the integrity of the object.

Steps:

When uploading an object to S3, calculate the MD5 checksum of the object.

Include the Content-MD5 header with the base64-encoded MD5 checksum value in the upload request.

This ensures that S3 can detect if the object is corrupted during the upload process.

STORAGE_FULL State:

When an RDS instance is in the STORAGE_FULL state, automated backups cannot be performed because there is insufficient storage available.

Steps to Resolve:

Go to the AWS Management Console.

Navigate to RDS and select the DB instance.

Check the storage metrics to confirm the STORAGE_FULL state.

Increase the allocated storage for the DB instance to provide sufficient space for automated backups.

AWS Config Managed Rule:

AWS Config can be used to assess, audit, and evaluate the configurations of AWS resources. The managed rule can check if instances are launched from approved AMIs.

Steps:

Go to the AWS Management Console.

Navigate to AWS Config.

Create a managed rule that checks for EC2 instances running approved AMIs.

Configure the rule to use a list of approved AMIs.

Automatic Remediation with Systems Manager Automation:

AWS Systems Manager Automation runbooks can automate the process of remediating non-compliant resources.

Steps:

Create a Systems Manager Automation runbook that terminates instances not running approved AMIs.

Attach the runbook to the AWS Config rule for automatic remediation.