SOA-C02 AWS Certified SysOps Administrator - Associate (SOA-C02) Questions and Answers

In AWS, there are default limits (also known as quotas) for the number of various resources that can be created in an account. One of these limits is the number of Virtual Private Clouds (VPCs) that can be created in a single AWS account within a Region. The default limit for the number of VPCs per account per Region is typically 5.

If an organization is running multiple applications, each requiring a new VPC, it is possible to reach this limit, causing subsequent CloudFormation stack deployments that attempt to create additional VPCs to fail.

Check VPC Limits:

To verify the current limit and usage of VPCs in your account, you can use the AWS Service Quotas console.

Open the Service Quotas console at Service Quotas Console.

Navigate to AWS services and select Amazon VPC.

Check the VPCs per Region quota to see the limit and how many VPCs are currently in use.

Requesting a Quota Increase:

If the default limit is reached, you can request a quota increase.

In the Service Quotas console, select the quota and choose Request quota increase.

Fill in the required information and submit the request. AWS typically reviews and approves these requests, but it may take some time.

CloudFormation Stack Failure:

When a CloudFormation stack fails due to reaching the VPC limit, the error message will indicate the issue related to the quota being exceeded.

You can view the specific error in the CloudFormation console under the Events tab of the stack.

Preventative Measures:

To avoid this issue, monitor resource usage and limits regularly.

Consolidate applications within fewer VPCs if possible, using subnets and security groups to isolate resources.

References:

Amazon VPC Quotas

Service Quotas for VPC

Requesting a Quota Increase

To ensure that the CloudFormation stack fails and rolls back if the process stalls, you should add a CreationPolicy with a timeout set to 4 hours to the CloudFormation template.

CreationPolicy:

The CreationPolicy attribute enables you to specify how long CloudFormation should wait for a resource to be created or updated.

You can use this to ensure that the instance completes its software installation process within a specified period.

Adding CreationPolicy to the Template:

Add the CreationPolicy attribute to the EC2 resource in the CloudFormation template.

Set the Timeout to 4 hours (PT4H).

Example:

Resources:

MyInstance:

Type: 'AWS::EC2::Instance'

Properties:

InstanceType: t2.micro

ImageId: ami-0abcdef1234567890

CreationPolicy:

ResourceSignal:

Count: 1

Timeout: PT4H

Ensuring Rollback:

If the instance does not signal success within the specified timeout, CloudFormation will mark the stack as failed and roll back the changes.

References:

AWS CloudFormation CreationPolicy

Using Creation Policies with CloudFormation

DependsOn Attribute in CloudFormation:

The DependsOn attribute in AWS CloudFormation ensures that one resource is created only after another resource has been successfully created. In this case, it ensures that the EC2 instance is fully launched before the custom resource (the Lambda function) is executed.

Steps:

Update the CloudFormation template to include the DependsOn attribute for the custom resource.

Ensure that the custom resource references the EC2 instance.

Resources:

MyEC2Instance:

Type: AWS::EC2::Instance

Properties:

# EC2 properties

MyCustomResource:

Type: Custom::MyCustomResource

DependsOn: MyEC2Instance

Properties:

ServiceToken: !GetAtt MyLambdaFunction.Arn

# Other properties

To address high I/O requirements during the bootstrap process, increasing both IOPS and throughput on the EBS volume is recommended:

Increase EBS Volume IOPS: Enhances the instance’s ability to handle multiple read and write operations per second, essential for data-heavy tasks like downloading Docker images.

Increase EBS Volume Throughput: Provides higher data transfer rates, reducing bottlenecks during intensive I/O operations.

Increasing instance size is unnecessary if the primary issue is disk I/O, and changing from Nitro-based instances would not address the underlying storage performance need.

Ref. https://aws.amazon.com/es/blogs/storage/adding-and-removing-object-tags-with-s3-batch-operations/

Amazon S3 Batch Operations is a feature that lets you perform large-scale batch operations on S3 objects. It is the most operationally efficient way to replace a tag on all objects in an S3 bucket.

Create an S3 Batch Operations Job:

Open the Amazon S3 console at Amazon S3 Console.

Navigate to Batch Operations and create a new job.

Specify the Operation:

Choose the operation to replace all object tags.

Provide a manifest that lists the objects in the bucket. You can generate this manifest using an S3 inventory report.

Execute the Job:

Review the job configuration and submit it.

Monitor the job execution to ensure all tags are replaced as specified.

Using S3 Batch Operations automates the process and minimizes manual effort.

References:

Amazon S3 Batch Operations

Tagging Amazon S3 Objects

To allow AWS Systems Manager Patch Manager to access your EC2 instances, you need to attach an IAM instance profile with the necessary permissions to the instances.

Create IAM Role for Systems Manager:

Open the IAM console at IAM Console.

Create a new role and choose EC2 as the trusted entity.

Attach the AmazonEC2RoleforSSM managed policy to the role.

Attach IAM Role to Instances:

Open the Amazon EC2 console at Amazon EC2 Console.

Select the instances that you want to manage with Systems Manager.

Choose Actions, then Instance Settings, and select Attach/Replace IAM Role.

Attach the IAM role you created.

This setup ensures that Systems Manager has the necessary permissions to manage the instances.

References:

Setting Up AWS Systems Manager

Create an IAM Instance Profile for Systems Manager

To monitor free space on Amazon EBS volumes attached to Microsoft Windows-based Amazon EC2 instances and receive email alerts before low storage space affects performance, follow these steps:

Install the Amazon CloudWatch Agent:

Download and install the CloudWatch agent on your Windows EC2 instances.

Snapshot Deletion Policy:

The Snapshot Deletion Policy ensures that a snapshot is created when an RDS instance is deleted as part of a CloudFormation stack deletion.

Steps:

Update your CloudFormation template to include the DeletionPolicy attribute for the RDS instance resource.

Example template snippet:

Resources:

MyDBInstance:

Type: AWS::RDS::DBInstance

Properties:

# DB instance properties

DeletionPolicy: Snapshot

 This configuration retains a snapshot of the RDS instance data when the stack is deleted.

 Reference: AWS CloudFormation DeletionPolicy

To securely connect to the S3 buckets over a private connection from EC2 instances without incurring additional costs, the SysOps administrator can create a gateway VPC endpoint.

Create a Gateway VPC Endpoint:

Navigate to the VPC console.

Create a gateway VPC endpoint for Amazon S3.

The best combination of steps to meet this requirement is to sign in to the new account by using root user credentials and change the support plan, and to create an IAM user that has administrator privileges in the new account.

Signing in to the new account by using root user credentials will allow the SysOps administrator to access the account and change the support plan to AWS Business Support. Additionally, creating an IAM user that has administrator privileges in the new account will ensure that the SysOps administrator has the necessary access to manage the account and make changes to the support plan if necessary.

When managing performance and cost for EC2 instances across different families, the following steps are recommended:

Utilize AWS Compute Optimizer: This service provides recommendations for EC2 instances based on historical usage patterns and existing configurations. It helps identify optimal EC2 instance types and sizes that could deliver better performance and cost savings for your specific workload.

Implement Compute Savings Plans: After determining the most suitable instance types and sizes through Compute Optimizer, purchasing Compute Savings Plans can offer significant cost savings. These savings plans apply to any instance family across any region, providing flexibility and cost efficiency without upfront commitment to specific instance types.

AWS Documentation Reference:Further details can be found in the AWS documentation on Compute Optimizer and Compute Savings Plans:

AWS Compute Optimizer

AWS Compute Savings Plans.

The provided IAM policy grants the following permissions:

Describe AWS Load Balancers:

The policy allows actions with the prefix elasticloadbalancing:. This includes actions like DescribeLoadBalancers and other Describe* actions related to Elastic Load Balancing.

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.

To improve security and availability, the best approach is to configure Multi-AZ for both the web and database tiers.

Multi-AZ Auto Scaling for Web Tier: Deploying the web-tier instances in an Auto Scaling group across multiple AZs with an internet-facing ALB provides high availability and fault tolerance.

RDS Multi-AZ for SQL Server: Migrating the SQL Server to RDS with Multi-AZ deployment ensures database redundancy and failover without additional management overhead.

Placing the web tier in multiple Regions would add unnecessary complexity, and migrating the database to DynamoDB is not suitable for applications requiring SQL Server’s relational capabilities.

To send local logs from a fleet of servers to Amazon CloudWatch:

Install the Unified CloudWatch Agent: The unified CloudWatch agent is capable of collecting both logs and metrics from servers. This agent supports various operating systems and can be configured according to specific logging requirements.

Configuration of the Agent: The agent's configuration involves specifying which log files to monitor and how they should be processed. This configuration can be done manually or through the AWS Systems Manager for automated deployment across multiple servers.

Send Logs to CloudWatch: Once configured and running, the CloudWatch agent will continuously monitor the specified log files and send the log data to Amazon CloudWatch Logs, allowing you to view, search, and set alarms on log data.

This setup ensures a robust and scalable way to manage log data across a fleet of servers, leveraging AWS native services for seamless integration and management.

https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/CloudWatch-Agent-procstat-process-metrics.html

A mount target provides an IP address for an NFSv4 endpoint at which you can mount an Amazon EFS file system. You mount your file system using its Domain Name Service (DNS) name, which resolves to the IP address of the EFS mount target in the same Availability Zone as your EC2 instance. You can create one mount target in each Availability Zone in an AWS Region. If there are multiple subnets in an Availability Zone in your VPC, you create a mount target in one of the subnets. Then all EC2 instances in that Availability Zone share that mount target. https://docs.aws.amazon.com/efs/latest/ug/how-it-works.html

To reduce costs effectively for jobs that are flexible in their scheduling and have a clear, predictable runtime:

Spot Instances with Defined Duration (Spot Blocks): Spot Instances offer significant discounts compared to On-Demand pricing. For workloads like the described jobs that have a predictable duration (slightly less than 2 hours), requesting Spot Instances with a defined duration (also known as Spot Blocks) is ideal. This option allows you to request Spot Instances guaranteed to not be terminated by AWS due to price changes for the duration specified.

Cost Efficiency: This method ensures that the instances will run for the duration required to complete the jobs without interruption, unless AWS experiences an exceptional shortage of capacity. The cost savings compared to On-Demand Instances can be substantial, especially for regular, predictable workloads.

Risk Mitigation: Although Spot Instances can be interrupted, using them with a defined duration reduces the risk of interruptions within the set time frame, making them suitable for jobs that can tolerate a restart in rare cases of interruption after the block time expires.

This strategy combines cost savings with the performance requirements of the jobs, making it an optimal choice for tasks that are not time-critical but need completion within a predictable timeframe.

To allow access using current LDAP credentials while migrating to AWS, the best approach is to federate the LDAP directory with IAM using SAML.

Set Up SAML-Based Federation:

AWS supports identity federation using SAML (Security Assertion Markup Language) 2.0. You need to configure your LDAP directory to federate with AWS IAM via SAML.

Increasing the amount of memory for the Lambda function will help to improve the performance of the function. This is because the Lambda function is CPU-intensive and increasing the memory will give it access to more CPU resources and help it run faster. The other options (activating hyperthreading in the CPU launch options for the Lambda function, turning off the AWS managed encryption, and loading the required code into a custom layer) will not help to improve the performance of the Lambda function and are not the correct solutions for this issue.

https://docs.aws.amazon.com/lambda/latest/dg/configuration-function-common.html#configuration-memory-console

To optimize the cost of a computing environment consisting of control nodes that are always on and task nodes that operate for a limited number of hours each day, consider the following strategies:

Purchase EC2 Instance Savings Plans for the Control Nodes: Since the control nodes are required to be operational 24/7, purchasing EC2 Instance Savings Plans is a cost-effective choice. These plans provide a lower price compared to on-demand instances, in exchange for a commitment to a consistent amount of usage (measured in $/hour) for a one or three-year period.

Use Spot Instances for the Task Nodes: Given that task nodes are used for a shorter duration (4 hours a day) and presumably can tolerate interruptions, using Spot Instances can significantly reduce costs. Spot Instances offer unused EC2 capacity at a fraction of the regular price, which can lead to substantial cost savings. Additionally, configure the system to fall back to On-Demand Instances during periods when Spot Instances are not available to ensure availability.

This combination leverages cost savings for continuous use and flexible, lower-cost options for intermittent use, optimizing overall operational costs efficiently.

When an EC2 instance stops responding and the system status checks are failing, the recommended first step is to stop and then start the instance. This action will cause the instance to be moved to a new host, potentially resolving the underlying hardware issue.

Stop and Start the Instance:

In the AWS Management Console, navigate to the EC2 dashboard and stop the affected instance.

After the instance has stopped, start it again to launch it on a new host.

To view the cost details of each project in an AWS account using Cost Explorer, you need to activate cost allocation tags and tag the resources with a project identifier.

Activate Cost Allocation Tags:

Navigate to the AWS Billing and Cost Management console.

In the navigation pane, choose "Cost allocation tags".

Select the tags you want to activate (e.g., "Project") and click "Activate".

Tag Resources with Project Identifier:

Go to the AWS Management Console for each service where resources are deployed (e.g., EC2, S3, RDS).

For each resource, add a tag with the key "Project" and a value that identifies the project (e.g., "ProjectA").

Ensure that all relevant resources are tagged appropriately.

View Cost Allocation in Cost Explorer:

Navigate to the Cost Explorer console.

Use the "Group by" option to group costs by the "Project" tag.

Review the cost details for each project based on the tags applied to the resources.

References:

Using Cost Allocation Tags

Analyzing Your Costs with Cost Explorer

CloudWatch Metrics Explorer is a powerful tool for creating dynamic dashboards based on tags. This method is efficient for monitoring Auto Scaling groups:

Use Metrics Explorer: Navigate to the Metrics Explorer in the CloudWatch console and select the CPUUtilization metric. Use the aws:autoscaling:groupName tag to filter the metric, ensuring that it only shows data for EC2 instances within the specified Auto Scaling group.

Create Visualization: Configure the visualization settings as needed and add it to a CloudWatch dashboard.

Monitor Automatically: This setup will automatically update to include metrics from new EC2 instances that join the Auto Scaling group, without any need for manual intervention or scripting.

AWS Documentation Reference:You can learn more about using Metrics Explorer here: Using CloudWatch Metrics Explorer.

The requirement to share the same underlying files among EC2 instances with data consistency is best met by using Amazon Elastic File System (EFS), which supports concurrent access from multiple EC2 instances. A new launch template version should include user data scripts that mount the EFS file system on each instance launched by the Auto Scaling group. Older instances can be cycled out to ensure all instances use the new configuration. Option A is correct and provides the necessary solution while ensuring data consistency and availability. For implementation guidance, refer to the AWS documentation on integrating EFS with EC2 Amazon EFS Integration with EC2.

Implement an Amazon CloudFront distribution to offload the traffic from the Auto Scaling group does not breach the requirement of no changes in the network infrastructure. Reason is that cloudfront is a distribution that allows you to distribute content using a worldwide network of edge locations that provide low latency and high data transfer speeds. It plug in to existing setup, not changes to it.

When troubleshooting inability to access an EC2 instance from the internet, you should:

A: Verify that the security group rules allow inbound HTTP and HTTPS traffic on ports 80 and 443. Security groups act as a virtual firewall to control the traffic to instances.

D: Check that outbound rules in the network ACL allow traffic for ephemeral ports 1024-65535. This is crucial for return traffic from web requests, which typically use these higher port numbers for responses.

E: Confirm that any software-based firewalls on the instance (such as Windows Firewall or iptables in Linux) are configured to allow inbound traffic on HTTP and HTTPS. These steps will ensure that the web server is correctly configured to receive and respond to web traffic from the internet. AWS provides guidelines on these configurations in their documentation on security groups EC2 Security Groups and network ACLs Network ACLs.

To improve application responsiveness and handle high CPU utilization:

Create Auto Scaling Group:

Create an Auto Scaling group (ASG) for the EC2 instances running the application.

You might want to use Transfer Acceleration on a bucket for various reasons: ->Your customers upload to a centralized bucket from all over the world. ->You transfer gigabytes to terabytes of data on a regular basis across continents. ->You can't use all of your available bandwidth over the internet when uploading to Amazon S3." https://docs.aws.amazon.com/AmazonS3/latest/userguide/transfer-acceleration.html

https://docs.aws.amazon.com/awscloudtrail/latest/userguide/cloudtrail-log-file-validation-intro.html

"When you enable log file integrity validation, CloudTrail creates a hash for every log file that it delivers. Every hour, CloudTrail also creates and delivers a file that references the log files for the last hour and contains a hash of each. This file is called a digest file. Validated log files are invaluable in security and forensic investigations"

To route traffic to the Network Load Balancer (NLB) using Amazon Route 53 cost-effectively, creating an alias record is the best solution.

Alias Record:

Alias records are a Route 53-specific extension to DNS functionality.

They provide a way to map a domain name to an AWS resource, such as an NLB, without incurring additional charges.

Steps to Implement:

Open the Route 53 console.

Select the hosted zone and choose "Create Record Set."

Choose "Alias" and select the NLB from the drop-down list.

References:

Creating Alias Records

 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.

To maintain a documented trail of any changes made to the security groups and receive notifications, AWS Config is the best solution.

AWS Config:

AWS Config continuously monitors and records your AWS resource configurations and allows you to automate the evaluation of recorded configurations against desired configurations.

You can set up AWS Config to record changes to your security groups.

Setting Up AWS Config:

Open the AWS Config console and choose "Set up AWS Config."

Select the resource types you want to record (in this case, security groups).

Specify an Amazon S3 bucket to store configuration snapshots and history files.

Notifications:

Create an Amazon SNS topic for notifications about configuration changes.

Subscribe the SysOps administrator's email address to the SNS topic.

References:

AWS Config

Setting Up AWS Config

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.

https://docs.aws.amazon.com/AmazonS3/latest/userguide/object-lock-overview.html In governance mode, users can 't overwrite or delete an object version or alter its lock settings unless they have special permissions. With governance mode, you protect objects against being deleted by most users, but you can still grant some users permission to alter the retention settings or delete the object if necessary. You can also use governance mode to test retention-period settings before creating a compliance-mode retention period. In compliance mode, a protected object version can't be overwritten or deleted by any user, including the root user in your AWS account. When an object is locked in compliance mode, its retention mode can't be changed, and its retention period can't be shortened. Compliance mode helps ensure that an object version can't be overwritten or deleted for the duration of the retention period.

"You can add tags to resources when you create the resource. You can use the resource's service console or API to add, change, or remove those tags one resource at a time. To add tags to—or edit or delete tags of—multiple resources at once, use Tag Editor. With Tag Editor, you search for the resources that you want to tag, and then manage tags for the resources in your search results." https://docs.aws.amazon.com/ARG/latest/userguide/tag-editor.html

To analyze CloudWatch logs across multiple AWS Lambda functions for historical errors, the most operationally efficient way is to use AWS Glue and Amazon Athena.

AWS Glue and Amazon Athena:

AWS Glue can crawl the data in S3, creating a catalog that makes it queryable.

Amazon Athena allows you to run SQL queries on the data cataloged by AWS Glue.

Steps to Implement:

Set up an AWS Glue crawler to index the logs stored in S3.

Configure the crawler to create a table in the AWS Glue Data Catalog.

Use Amazon Athena to query the table for errors using SQL. Since errors have a common string prefix, you can use SQL queries to filter and find these errors.

References:

AWS Glue

Amazon Athena

To handle the increased message load with minimal operational effort, implementing an Amazon Simple Queue Service (SQS) queue between the frontend and backend is an ideal solution. SQS decouples the frontend and backend by queuing messages, enabling the backend to process messages at its own pace without losing any.

SQS Queue: Acts as a buffer, ensuring messages are not lost if the backend application cannot immediately process them.

Decoupling: With SQS, the frontend can continue sending messages without concern for the backend's processing speed, providing a scalable solution with minimal management requirements.

Low Operational Overhead: SQS is fully managed, reducing the need for infrastructure management.

https://aws.amazon.com/blogs/database/improving-application-availability-with-amazon-rds-proxy/

To improve RDS performance during peak traffic when resources are over-utilized due to read traffic, the SysOps administrator can take the following actions:

Add a Read Replica:

Amazon RDS Read Replicas provide enhanced performance and durability for database instances.

By creating a read replica, you can offload read traffic from the primary database instance to the replica.

This reduces the load on the primary instance and improves overall performance.

To implement a highly available solution that provides the functionality to use a minimum of three On-Demand instances and three Spot instances when prices are at a certain threshold, defining an Amazon EC2 Auto Scaling group using a launch template is the most suitable solution. This approach minimizes operational overhead by consolidating configuration and management tasks.

Define a Launch Template:

Use the provided AMI in the launch template.

Configure the instance type, key pair, security groups, and other necessary parameters.

Create an Auto Scaling Group:

Use the launch template for the Auto Scaling group.

Specify a desired capacity of three On-Demand instances.

Configure the Auto Scaling group to use mixed instances policies, which allow you to specify a combination of On-Demand and Spot instances.

Set the maximum price for Spot instances in the launch template to ensure that Spot instances are used only when their prices are below the specified threshold.

Configuration Steps:

Open the EC2 console and navigate to "Launch Templates."

Create a new launch template with the necessary configurations.

Navigate to "Auto Scaling Groups" and create a new Auto Scaling group using the launch template.

Configure the desired capacity, minimum capacity, and maximum capacity.

Under "Advanced Options," specify the mixed instances policy and set the maximum price for Spot instances.

References:

Amazon EC2 Auto Scaling Launch Templates

Auto Scaling Mixed Instances Policies

To optimize the routing of requests to the application for users in different geographic locations, use Amazon Route 53's latency-based routing:

Latency Routing Policy: Modify the Route 53 DNS settings for app.anycompany.com by changing the routing policy to latency. This policy routes user requests to the server that has the lowest latency relative to the user's location.

Configure Latency Records: Create latency records for each ALB—one for the ALB in us-west-2 and another for the new ALB in ap-southeast-2. Route 53 will automatically direct traffic to the endpoint that provides the lowest latency connection to the user.

Seamless User Experience: By using latency routing, the URL remains the same (app.anycompany.com), but the backend service location varies based on which endpoint is likely to respond the fastest. This setup provides a seamless experience for users, reducing latency without requiring any changes to how they access the application.

This method leverages Route 53's advanced DNS capabilities to ensure optimal performance and user experience by dynamically routing traffic based on geographic latency considerations.

Retain the Security Group:

When deleting a CloudFormation stack, you can specify resources to be retained instead of deleted.

Steps:

Go to the AWS Management Console.

Navigate to CloudFormation and select the stack.

Choose to delete the stack.

In the deletion options, specify that the security group should be retained.

This will delete the stack but keep the security group, ensuring no impact on other applications.

AWS Single Sign-On (AWS SSO) provides a centralized interface to manage SSO access to multiple AWS accounts and business applications. AWS SSO integrates with AWS Organizations and supports SAML 2.0 identity providers, making it an ideal solution for centrally managing user access and permissions across multiple AWS accounts.

AWS Single Sign-On (AWS SSO):

AWS SSO allows you to manage SSO access and user permissions to all of your AWS accounts and applications.

It integrates seamlessly with AWS Organizations.

Integration with SAML 2.0 IdP:

AWS SSO supports integration with third-party SAML 2.0 identity providers.

This allows centralized management of user identities and access.

Steps to Implement:

Enable AWS SSO in your AWS Organizations management account.

Configure AWS SSO to connect with your third-party SAML 2.0 IdP.

Assign user permissions and roles for each AWS account through AWS SSO.

References:

AWS Single Sign-On

Integrating AWS SSO with SAML 2.0 Identity Providers

Using CloudFormation Stack Sets:

CloudFormation stack sets allow you to deploy CloudFormation stacks across multiple AWS accounts and regions.

Steps:

Go to the AWS Management Console.

Navigate to CloudFormation and select "StackSets."

Click on "Create StackSet."

Provide the template URL or upload a template file.

Configure the stack set options and specify the accounts and regions.

Deploy the stack set to the specified accounts and regions.

To centrally manage application logs and retain them for no more than 90 days, you can use the Amazon CloudWatch Logs agent to send logs to a CloudWatch log group and configure the log group's retention period.

Update the Launch Template User Data:

Navigate to the EC2 console.

Select the launch template used by the Auto Scaling group.

Edit the launch template to include the following user data script:

#!/bin/bash

yum update -y

yum install -y awslogs

cat < /etc/awslogs/awslogs.conf

[general]

state_file = /var/lib/awslogs/agent-state

[/var/log/messages]

file = /var/log/messages

log_group_name = /my-log-group

log_stream_name = {instance_id}/messages

datetime_format = %b %d %H:%M:%S

[/var/log/secure]

file = /var/log/secure

log_group_name = /my-log-group

log_stream_name = {instance_id}/secure

datetime_format = %b %d %H:%M:%S

EOF

systemctl start awslogsd

systemctl enable awslogsd

Replace /my-log-group with the name of your CloudWatch log group.

Configure the Log Group Retention Period:

Navigate to the CloudWatch console.

In the navigation pane, choose "Logs".

Select the log group created by the CloudWatch Logs agent.

Click on "Actions" and then "Edit retention settings".

Set the retention period to 90 days.

Verify the Configuration:

Ensure that logs from the EC2 instances are being sent to the CloudWatch log group.

Verify that the log group's retention period is correctly set to 90 days.

References:

Amazon CloudWatch Logs Agent

Setting Log Retention in CloudWatch

When setting up an AWS managed VPN connection and creating a customer gateway resource, if the customer gateway device resides behind a NAT device, you should use the public IP address of the NAT device. This is because the VPN connection from AWS will be established to the public IP address that AWS can reach.

Identify the Public IP Address of the NAT Device:

Determine the public IP address assigned to the NAT device in front of the customer gateway.

Create Customer Gateway Resource:

Navigate to the VPC console in the AWS Management Console.

In the navigation pane, choose "Customer Gateways" and then click "Create Customer Gateway".

Enter a name for the customer gateway.

For the "IP Address", enter the public IP address of the NAT device.

Configure VPN Connection:

Create a VPN connection by navigating to the "VPN Connections" section and clicking "Create VPN Connection".

Select the created customer gateway and complete the VPN setup wizard.

Update Routing and Configuration:

Ensure that the routing configurations on both the AWS side and the on-premises side are updated to route traffic through the VPN connection.

Configure the customer gateway device (behind the NAT) to accept traffic from the NAT device and route it appropriately.

References:

AWS Managed VPN Connections

Customer Gateway Resource

AWS CloudFormation StackSets extends the capability of stacks by enabling you to create, update, or delete stacks across multiple accounts and AWS Regions

If a Lambda function is not being invoked by an Amazon EventBridge (formerly CloudWatch Events) rule, the likely issue is a missing permission. The Lambda function needs permission to be invoked by the EventBridge rule.

Steps:

Add Permission to Lambda Function:

Open the AWS Lambda console.

Select your Lambda function.

Choose "Configuration" and then "Permissions".

Under the "Resource-based policy" section, add a policy that grants EventBridge permission to invoke your function.

Example policy:

json

Copy code

{

"Version": "2012-10-17",

"Statement": [

{

"Effect": "Allow",

"Principal": {

"Service": "events.amazonaws.com"

},

"Action": "lambda:InvokeFunction",

"Resource": "arn:aws:lambda:REGION:ACCOUNT_ID:function:FUNCTION_NAME",

"Condition": {

"ArnLike": {

"AWS:SourceArn": "arn:aws:events:REGION:ACCOUNT_ID:rule/RULE_NAME"

}

}

}

]

}

Verify the EventBridge Rule:

Open the Amazon EventBridge console.

Select the rule that targets your Lambda function.

Ensure that the rule is correctly configured to match events and the target is your Lambda function.

References:

AWS Lambda Permissions Model

Amazon EventBridge Rules

Specifying the capacity-optimized allocation strategy for Spot Instances and adding more instance types to the Auto Scaling group is the best action to meet the requirements. Increasing the size of the instances in the Auto Scaling group will not necessarily help with the launch time or reduce interruptions, as the Spot Instances could still be interrupted even with larger instance sizes.

"Scheduled scaling helps you to set up your own scaling schedule according to predictable load changes. For example, let's say that every week the traffic to your web application starts to increase on Wednesday, remains high on Thursday, and starts to decrease on Friday. You can configure a schedule for Amazon EC2 Auto Scaling to increase capacity on Wednesday and decrease capacity on Friday." https://docs.aws.amazon.com/autoscaling/ec2/userguide/schedule_time.html

Using an AMI with CloudWatch Agent:

The CloudWatch agent can collect memory utilization metrics and send them to CloudWatch.

Steps:

Create or use an existing AMI that includes the CloudWatch agent installed and configured.

Ensure the CloudWatch agent is configured to collect memory metrics.

Use this AMI for instances in the Auto Scaling group.

Technology to use is a VPC endpoint - "A VPC endpoint enables private connections between your VPC and supported AWS services and VPC endpoint services powered by AWS PrivateLink. AWS PrivateLink is a technology that enables you to privately access services by using private IP addresses. Traffic between your VPC and the other service does not leave the Amazon network." S3 is an example of a gateway endpoint. We want to see services in AWS while not leaving the VPC.

For predictable, significant traffic increases during a specific time period every day:

EC2 Auto Scaling Group: Set up an Auto Scaling group for the EC2 instances running the web application. This group automatically adjusts the number of instances based on policies defined.

Scheduled Scaling Policy: Use a scheduled scaling policy to pre-emptively increase the number of instances before the expected increase in traffic each day. Scheduled scaling allows you to specify the scaling actions to occur at specific times, based on known or expected demand patterns.

Attach to ALB: Ensure the Auto Scaling group is attached to the Application Load Balancer, which will distribute incoming traffic across the dynamically adjusted pool of EC2 instances.

This approach ensures that the application scales up resources ahead of the expected load, maintaining performance and user experience without manual intervention.

To delete the AWS CloudFormation stack without deleting the DynamoDB table, you need to apply a deletion policy to the DynamoDB resource. The Retain deletion policy ensures that the specified resource is not deleted when the stack is deleted. Instead, it is retained.

Steps:

Modify the CloudFormation Template:

Add a deletion policy to the DynamoDB table resource.

json

Copy code

{

"Resources": {

"MyDynamoDBTable": {

"Type": "AWS::DynamoDB::Table",

"DeletionPolicy": "Retain",

}

}

}

The problem requires modifying the inbound SSH rule to restrict access to a list of trusted IPs instead of deleting it entirely. AWS Config rules can be configured with automatic remediation actions using either Systems Manager Automation runbooks or Lambda functions. However, AWS Systems Manager Automation runbooks are often more appropriate for managing infrastructure changes like security group modifications because they are reusable, parameterized, and easier to audit.

Create a Systems Manager Automation runbook: This runbook will contain steps to add or modify the existing security group rule, allowing SSH access only from the specified IP addresses.

Update the AWS Config rule: Modify the Config rule to call this new runbook for its automatic remediation. This will prevent deletion of the SSH rule and instead update it based on the IP list.

The error message indicates that the current quota for the number of EC2 instances allowed in the specified region has been reached. To resolve this issue, a quota increase must be requested.

Request Quota Increase:

Open the Service Quotas console at Service Quotas Console.

Navigate to Amazon EC2 service.

Find the specific quota for the instance type family that you need to increase.

Select the quota and choose Request quota increase.

Provide the necessary details and submit the request.

This action will initiate a request to AWS to increase the limit, allowing you to launch additional instances once the request is approved.

References:

Service Quotas

Requesting a Quota Increase

To resolve DNS across VPCs in different accounts, you should:

Authorization: In Account B, initiate a VPC association authorization for the private hosted zone. This action allows another AWS account to associate a VPC with this hosted zone.

Association: In Account A, after receiving the authorization from Account B, associate its VPC with the private hosted zone that exists in Account B. This step will enable EC2 instances within the VPC in Account A to resolve DNS records hosted in Account B.

AWS Documentation Reference:AWS provides detailed guidance on associating VPCs with private hosted zones across accounts in their documentation: Associating VPCs and Private Hosted Zones Across Accounts.

https://docs.aws.amazon.com/AmazonElastiCache/latest/red-ug/scaling-redis-cluster-mode-enabled.html As demand on your clusters changes, you might decide to improve performance or reduce costs by changing the number of shards in your Redis (cluster mode enabled) cluster. We recommend using online horizontal scaling to do so, because it allows your cluster to continue serving requests during the scaling process. https://d ocs.aws.amazon.com/AmazonElastiCache/latest/red-ug/redis-cluster-vertical-scaling-scaling-down.html

To efficiently find out how often the AWS Lambda function has failed in the last 7 days, use Amazon CloudWatch Logs Insights.

Access CloudWatch Logs Insights:

Navigate to the CloudWatch console.

Select "Logs Insights" from the navigation pane.

Here are the steps to configure an Amazon S3 bucket to serve a static error page in the event of a failure at the primary site:

Log in to the AWS Management Console and navigate to the S3 service in the us-east-2 Region.

Find the existing S3 bucket named lab-751906329398-26023898.com and click on it.

In the "Properties" tab, click on "Static website hosting" and select "Use this bucket to host a website".

In "Index Document" field, enter the name of the object that you want to use as the index document, in this case, "index.html"

In the "Permissions" tab, click on "Block Public Access", and make sure that "Block all public access" is turned OFF.

Click on "Bucket Policy" and add the following policy to allow public read access:

{

"Version": "2012-10-17",

"Statement": [

{

"Sid": "PublicReadGetObject",

"Effect": "Allow",

"Principal": "*",

"Action": "s3:GetObject",

"Resource": "arn:aws:s3:::lab-751906329398-26023898.com/*"

}

]

}

Now navigate to the Amazon Route 53 service, and find the existing hosted zone named lab-751906329398-26023898.com.

Click on the "A record" and update the routing policy to "Primary - Failover" and add the existing ALB as the primary record.

Click on "Create Record" button and create a new secondary failover alias record for the domain lab-751906329398-26023898.com that routes traffic to the existing S3 bucket.

Now, when the primary site (ALB) goes down, traffic will be automatically routed to the S3 bucket serving the static error page.

Note:

You can use CloudWatch to monitor the health of your ALB.

You can use Amazon S3 to host a static website.

You can use Amazon Route 53 for routing traffic to different resources based on health checks.

You can refer to the AWS documentation for more information on how to configure and use these services:

https://aws.amazon.com/s3/

https://aws.amazon.com/route53/

https://aws.amazon.com/cloudwatch/

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Amazon GuardDuty is a threat detection service that continuously monitors for malicious activity and unauthorized behavior to protect AWS accounts and workloads. It provides detailed monitoring for unauthorized access attempts, including console login attempts from unusual locations.

Amazon GuardDuty:

GuardDuty analyzes VPC flow logs, AWS CloudTrail logs, and DNS logs to detect suspicious activity.

It generates findings, such as UnauthorizedAccess

/ConsoleLoginSuccess, to alert administrators about potential security issues.

Setup:

Enable GuardDuty in your AWS account.

Configure GuardDuty to monitor unauthorized console logins.

Set up notifications for the relevant findings to alert administrators.

References:

Amazon GuardDuty

GuardDuty Finding Types

Here are the steps to update an existing AWS CloudFormation stack:

Log in to the AWS Management Console and navigate to the CloudFormation service in the us-east-2 Region.

Find the existing stack named 1700182 and click on it.

Click on the "Update" button.

Choose "Replace current template" and upload the updated CloudFormation template from the Amazon S3 bucket named "cloudformation-bucket"

In the "Parameter" section, update the EC2 instance type to us-east-t2.nano and add the IP address range 192.168.100.0/30 for SSH access.

Replace the instance profile IAM role with IamRoleB.

In the "Capabilities" section, check the checkbox for "IAM Resources"

Choose the role CFServiceR01e and click on "Update Stack"

Wait for the stack to be updated.

Once the update is complete, navigate to the stack and click on the "Stack options" button, and select "Prevent updates to prevent accidental deletion"

To get the value of the Prodlnstanceld , navigate to the "Outputs" tab in the CloudFormation stack and find the key "Prodlnstanceld". The value corresponding to it is the value that you need to enter in the text box below.

Note:

You can use AWS CloudFormation to update an existing stack.

You can use the AWS CloudFormation service role to deploy updates.

You can refer to the AWS CloudFormation documentation for more information on how to update and manage stacks: https://aws.amazon.com/cloudformation/

Here are the steps to configure Amazon EventBridge to meet the above requirements:

Log in to the AWS Management Console by using the AWS Management Console shortcut from the VM desktop. Make sure that you are logged in to the desired AWS account.

Go to the EventBridge service in the us-east-2 Region.

In the EventBridge service, navigate to the "Event buses" page.

Click on the "Create event bus" button.

Give a name to your event bus, and select "default" as the event source type.

Navigate to "Rules" page and create a new rule named "RunFunction"

In the "Event pattern" section, select "Schedule" as the event source and set the schedule to run every 15 minutes.

In the "Actions" section, select "Send to Lambda" and choose the existing AWS Lambda function named "LogEventFunction"

Create another rule named "SpotWarning"

In the "Event pattern" section, select "EC2" as the event source, and filter the events on "EC2 Spot Instance interruption"

In the "Actions" section, select "Send to SNS topic" and create a new standard Amazon SNS topic named "TopicEvents"

In the "Input Transformer" section, set the Input Path to {“instance” : “$.detail.instance-id”} and Input template to “The EC2 Spot Instance has been interrupted on account.

Now all Amazon EC2 events in the default event bus will be replayable for past 90 days.

Note:

You can use the AWS Management Console, AWS CLI, or SDKs to create and manage EventBridge resources.

You can use CloudTrail event history to replay events from the past 90 days.

You can refer to the AWS EventBridge documentation for more information on how to configure and use the service: https://aws.amazon.com/eventbridge/

To meet the requirement of having 50% CPU available to accommodate bursts of traffic and to handle the significant load increase between 09:00 and 17:00, you need a combination of target tracking and scheduled scaling policies.

Target Tracking Scaling Policy:

Create a target tracking scaling policy that keeps the CPU utilization at 50%. This ensures that the fleet scales in or out to maintain the target CPU utilization.

This policy will ensure that the fleet scales automatically based on actual CPU usage, maintaining availability and performance.

Scheduled Scaling Policies:

First Policy: Create a scheduled scaling policy to scale out the fleet at 09:00 when the load increases.

In the AWS Management Console, navigate to the EC2 Auto Scaling Groups.

Select your Auto Scaling group and choose Actions > Edit.

Add a new scheduled action to increase the desired capacity at 09:00.

Second Policy: Create another scheduled scaling policy to scale in the fleet at 17:00 when the load decreases.

Similarly, add another scheduled action to decrease the desired capacity at 17:00.

This approach ensures that the fleet is prepared for the increased load during peak hours while maintaining efficient resource usage during off-peak times.

References:

Target Tracking Scaling Policies

Scheduled Scaling

Increasing DB Instance Size:

Increasing the instance size provides more CPU and memory resources, which can help handle higher loads.

Steps:

Go to the AWS Management Console.

Navigate to RDS and select the DB instance.

Modify the instance to increase its size.

Apply the changes during the next maintenance window or immediately if it is a critical issue.

Monitoring Performance:

After resizing, monitor the instance during the next report run to ensure that it handles the load effectively.

Storage Auto Scaling:

Aurora storage auto scaling automatically increases the storage capacity of the database cluster when free storage space is running low.

Steps:

Go to the AWS Management Console.

Navigate to RDS and select your Aurora DB cluster.

Modify the DB cluster configuration to enable storage auto scaling.

Apply the changes.