SOA-C02 Questions and Answers

Step-by-Step Explanation:

Understand the Problem:

The company has a stateless application on 10 EC2 On-Demand Instances in an Auto Scaling group.

At least 6 instances are needed to meet service requirements.

The goal is to maintain uptime cost-effectively.

Analyze the Requirements:

Maintain a minimum of 6 instances to meet service requirements.

Optimize costs by using a mix of instance types.

Evaluate the Options:

Option A: Use a Spot Fleet with an On-Demand capacity of 6 instances.

Spot Fleets allow you to request a combination of On-Demand and Spot Instances.

Ensuring a minimum of 6 On-Demand Instances guarantees the required capacity while leveraging lower-cost Spot Instances to meet additional demand.

Option B: Update the Auto Scaling group with a minimum of 6 On-Demand Instances and a maximum of 10 On-Demand Instances.

This option ensures the minimum required capacity but does not optimize costs since it only uses On-Demand Instances.

Option C: Update the Auto Scaling group with a minimum of 1 On-Demand Instance and a maximum of 6 On-Demand Instances.

This does not meet the requirement of maintaining at least 6 instances at all times.

Option D: Use a Spot Fleet with a target capacity of 6 instances.

This option relies entirely on Spot Instances, which may not always be available, risking insufficient capacity.

Select the Best Solution:

Option A: Using a Spot Fleet with an On-Demand capacity of 6 instances ensures the necessary uptime with a cost-effective mix of On-Demand and Spot Instances.

Amazon EC2 Auto Scaling

Amazon EC2 Spot Instances

Spot Fleet Documentation

Using a Spot Fleet with a combination of On-Demand and Spot Instances offers a cost-effective solution while ensuring the required minimum capacity for the application.

To configure an Amazon RDS database for high availability, you can use the Multi-AZ deployment option. Multi-AZ deployments provide enhanced availability and durability for RDS instances, making them a suitable choice for production environments. Here’s a step-by-step guide to achieve this:

Login to AWS Management Console:

Open the Amazon RDS console at Amazon RDS Console.

Select the RDS Instance:

In the navigation pane, choose Databases.

Select the database instance that you want to modify.

Modify the Instance:

Choose the Modify button.

In the Availability & durability section, select the option to enable Multi-AZ deployment.

Choose the appropriate instance class and storage settings if needed.

Apply Changes:

Review your settings, and then choose Continue.

Choose Apply immediately if you want the changes to take effect immediately. Otherwise, the changes will be applied during the next maintenance window.

Review and Confirm:

Confirm the changes and the instance will start modifying to a Multi-AZ deployment. This process might take some time, depending on the size of your database.

Modifying an Amazon RDS DB instance

Multi-AZ Deployments

When you create a hosted zone, Route 53 automatically creates a name server (NS) record and a start of authority (SOA) record for the zone. https://docs.aws.amazon.com/Route53/latest/DeveloperGuide/migrate-dns-domain-in-use.html#migrate-dns-create-hosted-zone

https://en.wikipedia.org/wiki/SOA_record

Problem Analysis:

The CloudWatch agent configuration is inconsistent across instances.

A centralized and automated mechanism is needed for consistent configuration management.

Action: Store Configuration in Systems Manager Parameter Store:

Parameter Store allows for secure, centralized storage of configuration files.

Steps:

Open Systems Manager Console.

Navigate to Parameter Store.

Create a parameter with the CloudWatch agent configuration file content.

Action: Use State Manager to Apply Configuration:

Systems Manager State Manager automates repetitive tasks such as ensuring consistent configuration.

Steps:

Open State Manager Console.

Create an association using the AmazonCloudWatch-ManageAgent document.

Configure the document to use Parameter Store as the configuration source.

Use tags (key = "OS", value = "Windows") to target the Windows EC2 instances.

Why Other Options Are Incorrect:

A: Using an S3 bucket for configuration storage lacks integration with Systems Manager for automation.

B: OpsCenter is for managing operational issues, not configuration files.

E: S3 as a configuration source is valid but introduces additional operational complexity compared to Parameter Store.

To automatically shut down EC2 instances with low CPU utilization:

Create CloudWatch Alarms:

Go to the CloudWatch console and create an alarm for each EC2 instance.

Set the alarm to monitor the CPUUtilization metric with a period of 1 hour and a threshold of 10%.

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.

Step-by-Step Explanation:

Understand the Problem:

The threat of ransomware encrypting and holding company data hostage.

Need to protect an Amazon S3 bucket.

Analyze the Requirements:

Ensure that data in the S3 bucket is protected against unauthorized encryption or deletion.

Evaluate the Options:

Option A: Deny Post, Put, and Delete on the bucket.

Denying these actions would prevent any uploads or modifications to the bucket, making it unusable.

Option B: Enable server-side encryption on the bucket.

Server-side encryption protects data at rest but does not prevent the encryption of data by ransomware.

Option C: Enable Amazon S3 versioning on the bucket.

S3 versioning keeps multiple versions of an object in the bucket. If a file is overwritten or encrypted by ransomware, previous versions of the file can still be accessed.

Option D: Enable snapshots on the bucket.

Amazon S3 does not have a snapshot feature; this option is not applicable.

Select the Best Solution:

Option C: Enabling Amazon S3 versioning is the best solution as it allows access to previous versions of objects, providing protection against ransomware encryption by retaining prior, unencrypted versions.

Amazon S3 Versioning

Best Practices for Protecting Data with Amazon S3

Enabling S3 versioning ensures that previous versions of objects are preserved, providing a safeguard against ransomware by allowing recovery of unencrypted versions of data.

To meet the requirement of consistent performance of 10,000 IOPS with the least cost, the SysOps administrator should use a General Purpose SSD (gp3) Amazon EBS volume:

General Purpose SSD (gp3) EBS Volume:

The gp3 volume type can be provisioned with the required IOPS without the need for additional capacity, making it a cost-effective solution compared to Provisioned IOPS SSD (io1) volumes.

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.

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.

The most operationally efficient way to monitor state changes in EC2 instances and notify the operations team is by using Amazon EventBridge. EventBridge can be configured with a rule that listens for state change events from EC2 instances. These events can then be directed to an Amazon Simple Notification Service (Amazon SNS) topic, which will distribute the notification to the relevant parties. This solution does not require deploying additional scripts or functions, thereby enhancing operational efficiency. Option B is correct. For more details, see the Amazon EventBridge documentation Amazon EventBridge.

To control the production account efficiently, the most operationally efficient solution is to create a service control policy (SCP) and apply it to the production OU. SCPs allow you to manage permissions for AWS Organizations at the organizational unit (OU) or account level.

Service Control Policies (SCPs):

SCPs are a type of policy that can restrict what services and actions can be used in the accounts within an OU.

They are applied at the organizational unit level and provide a way to enforce corporate policies across multiple AWS accounts.

Steps to Implement:

Navigate to the AWS Organizations console.

Create a new SCP that specifies the allowed or denied services and actions.

Apply the SCP to the production OU.

AWS Organizations SCPs

Amazon CloudWatch does not collect memory utilization and disk space metrics from EC2 instances by default. To monitor these metrics, you need to:

Install and Configure the CloudWatch Agent:The unified CloudWatch agent enables you to collect internal system-level metrics, including memory utilization and disk space, from Amazon EC2 instances.

Attach an IAM Role to the Instances:The EC2 instances require an IAM role that grants permissions to write metrics to CloudWatch. This role should have the necessary policies attached to allow the CloudWatch agent to function correctly.

By following these steps, you can effectively monitor memory and disk space metrics on your EC2 instances in compliance with AWS best practices.

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.

To deliver digital content to authorized users through CloudFront while restricting unauthorized access, you can use an origin access identity (OAI) with signed URLs.

Store Content in S3 with Public Access Blocked:

Ensure the S3 bucket has public access blocked.

Navigate to the S3 console, select the bucket, and configure the "Block Public Access" settings.

To provision AWS accounts for each team with a defined baseline and governance guardrails in a scalable and efficient way, using AWS Control Tower is the best solution.

AWS Control Tower:

AWS Control Tower provides a straightforward way to set up and govern a secure, multi-account AWS environment based on best practices.

It uses Account Factory, a feature that automates the creation of new AWS accounts with predefined configurations.

Creating Accounts with Control Tower:

Navigate to the AWS Control Tower console.

Use Account Factory to create a new account.

Customize the account template to include the necessary configurations, such as organizational units (OUs), guardrails, and baselines.

Advantages:

Ensures consistent security and compliance across all accounts.

Automates account creation and configuration, saving time and reducing errors.

AWS Control Tower

Setting Up Account Factory

The most operationally efficient solution is to use the organization ARN to share the AMI across all accounts within AWS Organizations.

AMI Sharing with Organization ARN: AWS allows you to share AMIs with an entire AWS Organization by specifying the organization’s ARN, simplifying access management for multiple accounts.

Efficient Management: This approach eliminates the need to share AMIs individually with each account or make them public, and it avoids the complexity of using snapshots.

Making the AMI public is not secure, and using AWS Marketplace or snapshots does not provide the operational efficiency required.

"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

Amazon Elastic File System (EFS) provides a scalable and highly available file storage solution for use with Amazon EC2 instances. To achieve high availability and durability:

EFS Standard Storage Class: Stores data redundantly across multiple Availability Zones, ensuring data durability and availability.

Mount Targets: For optimal performance and availability, create a mount target in each Availability Zone. EC2 instances should connect to the mount target in their respective Availability Zone.

By configuring EFS in this manner, the company ensures that all EC2 instances, regardless of their Availability Zone, have reliable and efficient access to shared data.

To prioritize alarm notifications over information notifications in an Amazon SQS environment, creating separate queues for each type of notification is the best approach. This allows the application processing the queues to prioritize fetching messages from the alarm notifications queue first. Option D directly addresses the need for prioritization without complicating the existing infrastructure. This setup is supported by best practices for using Amazon SQS, where using multiple queues to segregate message types is a recommended strategy Amazon SQS Best Practices.

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.

AWS Global Accelerator:

AWS Global Accelerator is a service that improves the availability and performance of your applications with a global user base. It provides static IP addresses that act as a fixed entry point to your application endpoints (such as ALBs).

Steps:

Go to the AWS Management Console.

Navigate to Global Accelerator.

Click on "Create accelerator."

Configure the accelerator by providing a name and adding listeners.

Add your Application Load Balancer as an endpoint.

Allocate two static IP addresses.

This setup ensures that your application is accessible via two static IP addresses, fulfilling the requirement.

AWS Global Accelerator

https://aws.amazon.com/blogs/compute/using-amazon-rds-proxy-with-aws-lambda/

RDS Proxy acts as an intermediary between your application and an RDS database. RDS Proxy establishes and manages the necessary connection pools to your database so that your application creates fewer database connections. Your Lambda functions interact with RDS Proxy instead of your database instance. It handles the connection pooling necessary for scaling many simultaneous connections created by concurrent Lambda functions. This allows your Lambda applications to reuse existing connections, rather than creating new connections for every function invocation.

Check "Database proxy for Amazon RDS" section in the link to see how RDS proxy help Lambda handle huge connections to RDS MySQL https://aws.amazon.com/blogs/compute/using-amazon-rds-proxy-with-aws-lambda/

To allow the EC2 instance in the private subnet to establish a secure connection to an external web server, follow these steps:

Modify Security Group:

Add an outbound rule to the security group of the EC2 instance with the following parameters:

Type: HTTPS

Destination: 0.0.0.0/0

This allows outbound HTTPS traffic to the internet.

To address the performance issues of a CPU-heavy application running on a t2.large EC2 instance, the best course of action is to upgrade to a compute-optimized instance. Compute-optimized instances provide a higher ratio of CPU resources compared to memory, making them ideal for applications that require high CPU performance.

Upgrade to a Compute-Optimized Instance:

Identify a suitable compute-optimized instance type, such as the c5.large, which offers better CPU performance compared to the t2.large.

Stop the current EC2 instance and change the instance type to the chosen compute-optimized instance.

To reduce S3 storage costs while ensuring the images remain highly available and immediately accessible, transitioning the images to S3 Standard-IA after 7 days is the most cost-effective solution.

Understand Storage Classes:

S3 Standard-IA (Infrequent Access) is designed for data that is accessed less frequently but requires rapid access when needed. It offers lower storage costs compared to S3 Standard, but higher retrieval costs.

You are correct that an A record typically points to an IP address. However, in the case of an Application Load Balancer (ALB), you cannot use an A record with an IP address because the IP addresses of an ALB can change over time. Instead, you can use an alias record to point to the DNS name of the ALB. An alias record is a Route 53 extension to DNS that allows you to route traffic to selected AWS resources, such as an ALB, by using a friendly DNS name, such as example.com, instead of the resource’s IP address or DNS name.

Understand the Problem:

All AWS resources must be tagged according to a company policy.

Continuous identification and enforcement of non-compliant resources are required.

Analyze the Requirements:

Monitor resources for compliance with tagging policies.

Enforce tagging policies and provide ongoing compliance reporting.

Evaluate the Options:

Option A: AWS CloudTrail.

Tracks user activity and API usage but does not enforce tagging policies.

Option B: Amazon Inspector.

Provides security assessments but does not monitor or enforce resource tagging.

Option C: AWS Config.

Monitors and evaluates the configurations of AWS resources.

AWS Config rules can be used to enforce tagging policies and continuously monitor compliance.

Option D: AWS Systems Manager.

Provides operational insights and management but does not specifically enforce tagging compliance.

Select the Best Solution:

Option C: AWS Config is designed for compliance and configuration monitoring, making it the ideal service for enforcing and identifying non-compliant resource tags.

AWS Config

Managing Resource Tag Compliance with AWS Config

AWS Config provides the necessary tools to enforce and monitor resource tagging compliance, ensuring all resources adhere to the set policy.

To upgrade the instance type of a Memcached cluster in Amazon ElastiCache due to increased usage and the need for more memory:

ModifyCacheCluster API: Utilize the ModifyCacheCluster API call. This API allows you to change various settings of an existing cache cluster, including the instance type, which is referred to as cacheNodeType.

Instance Upgrade: Specify a new, larger cacheNodeType that provides more memory. This upgrade will involve a brief interruption as nodes are replaced with the larger type, but it is necessary to accommodate the increased load and memory requirements.

Cluster Availability: Ensure that the Memcached cluster is configured for minimal downtime during this change. The upgrade process is handled by ElastiCache, and the new nodes will join the cluster with more memory capacity.

This approach enables you to effectively scale up the resources available to your Memcached cluster, enhancing its performance and capacity to handle larger workloads.

The Compute Savings Plan is the most flexible pricing model among AWS's long-term commitment options. It allows the company to commit to a consistent amount of usage (measured in $/hour) for a 1- or 3-year term, and in return, it offers significant savings over On-Demand pricing.

From the AWS Savings Plans Documentation:

Compute Savings Plans provide the most flexibility and apply to any EC2 instance regardless of region, instance family, operating system, or tenancy, and also apply to AWS Fargate and AWS Lambda usage.

This exactly matches the company's needs:

Uses EC2, Fargate, and Lambda

Operates in multiple regions and OS types

Requires cost savings with flexibility for changes

❌ Why the other options are incorrect:

B. EC2 Instance Savings Plans only apply to specific instance families within a region and do not apply to Lambda or Fargate.

C. Reserved Instances are very rigid — tied to instance type, OS, region, and tenancy. Not ideal for changing environments.

D. Spot Instances offer savings but are not suitable for 24/7 core applications, as they can be interrupted.

Using AWS CloudFormation stack sets allows you to manage CloudWatch alarms across multiple accounts efficiently:

Create Stack Set: Use a CloudFormation template that defines the required CloudWatch alarms and configures them to publish alerts to an SNS topic.

Specify SNS Topic: Ensure the SNS topic is located in the logging account and has the necessary permissions set to receive publications from all accounts in the organization.

Deploy Across Organization: Implement the stack set across all accounts, ensuring centralized management and standardized deployment.

AWS Documentation Reference:

Learn more about deploying resources with CloudFormation StackSets: Working with AWS CloudFormation StackSets.

To prevent accounts from leaving an AWS Organization, an SCP that denies the LeaveOrganization action should be applied to the root organizational unit (OU).

Service Control Policy (SCP): By denying LeaveOrganization, member accounts are restricted from leaving the organization.

Root OU Application: Applying this policy at the root level ensures that no account in the organization can bypass it.

The RemoveAccountFromOrganization action pertains to removing an account by the organization’s management account rather than preventing member accounts from leaving. AWS Config’s account-part-of-organizations rule does not enforce this restriction but only monitors it.

To restrict EC2 resource deployment in a specific region and restrict root credentials usage:

Create Service Control Policies (SCPs):

Use AWS Organizations to create SCPs that restrict actions for all member accounts.

Create an SCP to deny the creation of EC2 instances in the ap-southeast-2 region.

Create an SCP to deny the use of root credentials in member accounts.

To ensure that the AWS CloudFormation template works in every region, you should use the Mappings section to specify region-specific AMI IDs. This allows the template to dynamically reference the correct AMI ID based on the region where the stack is being deployed.

Steps:

Add Mappings to the Template:

Define the AMI IDs for each region in the Mappings section of the CloudFormation template.

json

Copy code

{

"Mappings": {

"RegionMap": {

"us-east-1": { "AMI": "ami-0123456789abcdef0" },

"us-west-2": { "AMI": "ami-abcdef0123456789" }

}

}

}

Reference the Mapping in the Template:

Use the Fn::FindInMap function to reference the correct AMI ID based on the region.

json

Copy code

{

"Resources": {

"MyEC2Instance": {

"Type": "AWS::EC2::Instance",

"Properties": {

"ImageId": { "Fn::FindInMap": [ "RegionMap", { "Ref": "AWS::Region" }, "AMI" ] },

}

}

}

}

Deploy the Template:

Deploy the CloudFormation stack in any region, and it will use the correct AMI ID.

To enforce compliance with tagging policies in real-time:

AWS Config Setup: Implement an AWS Config rule to continuously monitor and evaluate EC2 instances for compliance with the tagging requirements. The required-tags managed rule can be configured to specifically check for the presence of a 'department' tag.

Automatic Remediation: Configure AWS Config to automatically execute the AWS-TerminateEC2Instance Systems Manager Automation document as a remediation action. This runbook will terminate any EC2 instance identified as noncompliant due to missing required tags.

Operational Efficiency: This setup allows for the enforcement of company tagging policies automatically and in near real-time, reducing the manual overhead of monitoring and ensuring compliance.

This method provides an efficient and effective solution to ensure that all EC2 instances meet the company's tagging requirements and that any noncompliant instances are dealt with promptly.

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.

Amazon EC2 Auto Scaling Launch Templates

Auto Scaling Mixed Instances Policies

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.

Step Scaling for Amazon EC2 Auto Scaling

Understand the Problem:

A user attempts to deploy a CloudFormation template to create an S3 bucket but the stack creation fails.

The user authenticates using Active Directory credentials.

Analyze the Requirements:

Identify permissions required for successful CloudFormation stack creation.

Evaluate the Options:

Option A: The user's IAM policy does not allow the cloudformation:CreateStack action.

Without this permission, the user cannot create CloudFormation stacks.

Option B: The user's IAM policy does not allow the cloudformation:CreateStackSet action.

StackSet is used for managing stacks across multiple accounts and regions, not relevant for a single stack creation.

Option C: The user's IAM policy does not allow the s3:CreateBucket action.

This permission is required to create an S3 bucket as part of the stack.

Option D: The user's IAM policy explicitly denies the s3:ListBucket action.

This permission is not required for bucket creation but for listing existing buckets.

Option E: The user's IAM policy explicitly denies the s3:PutObject action.

This permission is required to put objects in a bucket, not to create the bucket.

Select the Best Solution:

Option A and C: The user must have permissions for cloudformation:CreateStack and s3:CreateBucket to successfully create the stack and the S3 bucket.

AWS CloudFormation Permissions

IAM Policies and Permissions

Ensuring the user has the required permissions for cloudformation:CreateStack and s3:CreateBucket is crucial for successful stack creation.

https://docs.aws.amazon.com/AmazonCloudFront/latest/DeveloperGuide/private-content-restricting-access-to-s3.html

To ensure that users access objects in Amazon S3 by using only CloudFront URLs, the SysOps administrator should create an origin access identity (OAI) and grant it permissions to read objects in the S3 bucket.

Create an Origin Access Identity (OAI):

OAI is a special CloudFront user that you associate with your distribution to restrict access to the S3 bucket.

This ensures that only CloudFront can access the S3 bucket directly, and users must go through CloudFront to access the content.

Steps to Implement:

Open the CloudFront console.

Select your distribution and go to the "Origins and Origin Groups" tab.

Edit the S3 origin and create a new OAI or use an existing one.

Update the S3 bucket policy to grant the OAI read permissions.

Bucket Policy Example:

{

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

"Statement": [

{

"Effect": "Allow",

"Principal": {

"AWS": "arn:aws:iam::cloudfront:user/CloudFront Origin Access Identity [OAI_ID]"

},

"Action": "s3:GetObject",

"Resource": "arn:aws:s3:::your-bucket-name/*"

}

]

}

Using an Origin Access Identity to Restrict Access to Your S3 Content

To resolve the issue of an AWS Lambda function unable to connect to a database that has been moved to a private subnet, the Lambda function needs to be connected to the same VPC as the database. This is done by configuring the Lambda function with VPC access. This involves specifying the VPC, subnets, and security groups for the Lambda function so that it can communicate with the database using its private endpoint. Option B is correct as it directly addresses the issue without compromising security. AWS documentation on configuring VPC access for Lambda provides guidance on this setup Configuring VPC Access for Lambda.

If EC2 instances in one region (eu-central-1) need to access a database in another (us-east-1), and the database must remain only in us-east-1, the most operationally efficient solution is a VPC peering connection.

From the VPC Peering documentation:

Inter-Region VPC peering enables routing of traffic between VPCs in different AWS Regions using private IP addresses, without VPN or additional hardware.

Also:

You must manually update security group rules to allow traffic from the peered VPC.

So:

Create the VPC peering

Add the private IP range of the remote EC2 instances to the inbound rules of the database’s security group

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.

AWS Config

Setting Up AWS Config

To host a static website on Amazon S3, the SysOps administrator needs to configure the bucket for public access and set up the static website hosting. Here's how to complete this process:

Turn off "Block all public access": Amazon S3 buckets have "Block all public access" settings enabled by default for security. Since the webpage needs to be accessible publicly, this setting must be disabled. This step is crucial to allow public read access to the web content.

Set a bucket policy: After disabling "Block all public access," set a bucket policy that explicitly allows public read access to the S3 bucket. This policy should allow the s3:GetObject action for everyone, which can be set by specifying "Principal": "*". This policy ensures that anyone can view the webpage but does not grant permissions to modify or delete the content.

Create an index.html document and configure static website hosting: The next step is to create an index.html file, which will serve as the entry point of the website. After creating this file, upload it to the bucket. Then, configure the bucket for static website hosting through the S3 management console. This setting enables the S3 bucket to serve the webpage directly from the index.html file.

Combining these actions, the S3 bucket will be properly configured to host and serve the static website with minimal operational overhead and maximum accessibility.

AWS Budgets allows you to set custom cost and usage budgets that alert you when you exceed your thresholds. This feature helps teams to monitor their spending and ensure it aligns with the set budget.

Steps:

Open AWS Budgets:

Sign in to the AWS Management Console.

Open the AWS Budgets dashboard.

Create a New Budget:

Click on "Create a budget".

Select "Cost budget" and click "Next".

Set Budget Details:

Enter a unique name for the budget.

Define the period (e.g., quarterly) and start date.

Set the budgeted amount as specified by the finance department.

Define Filters:

Use the filters to select the specific services each team is responsible for (e.g., storage, compute, database).

Set Alerts:

Specify the threshold for forecasted cost that will trigger an alert (e.g., 80% of the budget).

Enter the email addresses of the recipients (the respective teams).

Review and Create:

Review the configuration and click "Create budget".

By setting up individual budgets for each team and filtering by services, you can ensure that each team is alerted when their projected spend approaches the threshold. This method does not incur additional compute, storage, or database costs.

If an EC2 instance does not appear in the Systems Manager Session Manager list, it is likely because the instance does not have an attached IAM role that allows Session Manager to connect.

Attach IAM Role with Necessary Permissions:

Ensure the EC2 instance has an IAM role attached with the AmazonSSMManagedInstanceCore policy.

Steps to Attach IAM Role:

Open the EC2 console, select the instance, and choose "Actions" -> "Instance Settings" -> "Attach/Replace IAM Role."

Select or create an IAM role with the necessary permissions for Session Manager.

Permissions for Session Manager:

The AmazonSSMManagedInstanceCore policy provides the required permissions for the Systems Manager agent to interact with the Systems Manager service.

Session Manager Prerequisites

Attach an IAM Role to an Instance

To quickly remediate resources and bring them back into compliance with patch standards, AWS Systems Manager is the appropriate service to use.

Use AWS Systems Manager:

Leverage Systems Manager Patch Manager to automate the process of patching managed instances.

Use Systems Manager State Manager to ensure that resources remain in compliance with the desired configurations.

To count application errors grouped by type across all CloudWatch Logs log groups, use CloudWatch Logs Insights.

Steps:

Access CloudWatch Logs Insights:

Open the CloudWatch console and navigate to Logs Insights.

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/systems-manager/latest/userguide/systems-manager-automation.html

To ensure all EC2 instances have the required tags and terminate any noncompliant instances, AWS Config can be used to check the compliance, and AWS Systems Manager Automation can be invoked to take action on noncompliant instances.

Create AWS Config Rule:

Open the AWS Config console at AWS Config Console.

Create a new rule to check for the required tags on EC2 instances. Use the managed rule required-tags.

Create AWS Systems Manager Automation Document:

Open the AWS Systems Manager console at AWS Systems Manager Console.

Create an Automation document to terminate noncompliant instances.

Link AWS Config Rule to Automation:

In the AWS Config console, configure the rule to invoke the Systems Manager Automation document if an instance is found to be noncompliant.

AWS Config Rules

AWS Systems Manager Automation

AWS Config Managed Rules

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.

Amazon CloudWatch Logs Agent

Setting Log Retention in CloudWatch

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.

Step-by-Step Explanation:

Understand the Problem:

Minimize potential data loss and recovery time for a MySQL database running on an Amazon EC2 instance.

Analyze the Requirements:

Reduce the risk of data loss.

Ensure quick recovery in the event of a database failure.

Aim for operational efficiency.

Evaluate the Options:

Option A: Create a CloudWatch alarm to invoke a Lambda function that stops and starts the EC2 instance.

This addresses system failures but does not help with minimizing data loss or ensuring database redundancy.

Option B: Create an Amazon RDS for MySQL Multi-AZ DB instance and use a MySQL native backup stored in Amazon S3.

RDS Multi-AZ deployments provide high availability and durability by automatically replicating data to a standby instance in a different Availability Zone.

Using a MySQL native backup stored in Amazon S3 ensures data can be restored efficiently.

Option C: Create an RDS for MySQL Single-AZ DB instance with a read replica.

This provides read scalability but does not ensure high availability or failover capabilities.

Option D: Use Amazon DLM to take hourly snapshots of the EBS volume.

This helps with backups but does not provide immediate failover capabilities or minimize downtime effectively.

Select the Best Solution:

Option B: Using Amazon RDS for MySQL Multi-AZ ensures high availability and automated backups, significantly minimizing data loss and recovery time.

Amazon RDS Multi-AZ Deployments

Backing Up and Restoring an Amazon RDS DB Instance

Using Amazon RDS for MySQL Multi-AZ provides a highly available and durable solution with automated backups, ensuring minimal data loss and quick recovery.

To enforce the use of approved EC2 instance configurations across different business units efficiently:

AWS Service Catalog: Utilize AWS Service Catalog to manage and govern commonly deployed IT services. Create a catalog of pre-approved products (in this case, EC2 instance configurations).

Publish Products: Define and publish EC2 instance configurations as products within the Service Catalog. These products will incorporate all the necessary and approved configurations, options, and software.

Launch Constraints: Assign launch constraints to these products, ensuring that users can only launch EC2 instances as defined by the pre-approved configurations.

Control Access: Grant business units access only to the Service Catalog for provisioning EC2 instances. This ensures they use only those configurations that comply with company policies and standards.

This approach not only standardizes resource deployment but also simplifies management and enhances compliance across the organization.

Objective:

Resolve the failure of the CloudFormation Auto Scaling group resource creation due to a missing wait condition signal.

cfn-signal:

The cfn-signal command is used in user data scripts to signal CloudFormation that the resource has been successfully created or configured.

This ensures the stack creation process continues as expected.

Steps to Implement:

At the end of the user data script in the EC2 launch template:

Add the command: cfn-signal --stack --resource --region

Replace , , and with appropriate values.

AWS References:

cfn-signal:Using cfn-signal to Signal Completion

Why Other Options Are Incorrect:

Option B: While port 443 is necessary for CloudFormation signaling, the main issue is the absence of cfn-signal.

Option C: Reducing DesiredCapacity may bypass the error but does not solve the root cause.

Option D: Associating a public IP may help connectivity but is unrelated to the wait condition.

To meet the requirements of logging all access attempts to the S3 bucket and receiving immediate notification about any delete events, the company can enable S3 server access logging and set up an Amazon Simple Notification Service (Amazon SNS) notification for the S3 bucket. The S3 server access logs will record all access attempts to the bucket, including delete events, and the SNS notification can be configured to send an alert when a DeleteObject event occurs.

# Enable instance scale-in protection for specific instance.

aws autoscaling set-instance-protection --instance-ids i-5f2e8a0d --auto-scaling-group-name my-asg --protected-from-scale-in

# Disable instance scale-in protection for the specified instance.

aws autoscaling set-instance-protection --instance-ids i-5f2e8a0d --auto-scaling-group-name my-asg --no-protected-from-scale-in

https://docs.aws.amazon.com/autoscaling/ec2/userguide/ec2-auto-scaling-instance-protection.html

To ensure that EC2 instances in an Auto Scaling group are not interrupted during message processing, the most effective method is to implement scale-in protection for the instances while they are actively processing messages. This can be done programmatically by modifying the Auto Scaling group's settings using the Amazon EC2 Auto Scaling API.

Starting Message Processing: When an instance begins processing a message, your application should make an API call to enable scale-in protection. This is done using the SetInstanceProtection action, setting the ProtectedFromScaleIn parameter to true for that specific instance.

Completing Message Processing: Once the message has been processed, another API call should be made to disable scale-in protection. This is done by calling the SetInstanceProtection action again, but this time setting the ProtectedFromScaleIn parameter to false.

This method ensures that while messages are being processed, the instances are not terminated by the Auto Scaling group regardless of any scale-in activities that might be triggered by other parameters like CPU utilization or a decrease in the number of messages in the queue.

AWS Documentation Reference:

You can refer to the AWS documentation on managing instance scale-in protection in Auto Scaling groups for more details: Instance Scale-In Protection.

In AWS CloudFormation, the PrivateDnsName property of an EC2 instance cannot be directly set within the template. This property is automatically assigned by AWS when the instance is launched within a VPC and is associated with the private IP address of the instance. The attempt to explicitly set PrivateDnsName in a CloudFormation template will result in an error, causing the stack creation to fail. Therefore, option C is correct. For reference, the AWS documentation on EC2 instances in CloudFormation does not list PrivateDnsName as a configurable property AWS CloudFormation User Guide.

AWS provides a native integration with Slack via the AWS Support App, which allows:

Real-time updates for AWS Support cases in Slack

Replying to support cases and adding comments from Slack

Case creation and escalation from Slack

From the AWS Support App in Slack Documentation:

You must first authorize the Slack workspace in your AWS account using the AWS Support App setup process.

Then, add the specific Slack channel by specifying the channel ID and required case types (e.g., account, service limit, technical).

❌ Why the other options are incorrect:

A: Slack must authorize the workspace first, not just an AWS account.

C and D: Using SNS + EventBridge + Lambda is not necessary, as AWS provides a native Slack integration with full support case features.

Objective:

Provision Spot Instances with the highest availability while using a wide range of instance types.

Capacity Optimized Strategy:

The capacity optimized strategy ensures that Spot Instances are launched from the pools with the highest available capacity at the time of the request.

This approach minimizes the likelihood of interruptions and increases the chances of launching the desired capacity.

Steps to Implement:

In the Auto Scaling group configuration, set the Spot Allocation Strategy to Capacity Optimized.

Define multiple instance types in the launch template to allow flexibility.

AWS References:

Spot Allocation Strategies:Spot Instance Allocation Strategies

Capacity Optimized Details:Capacity Optimized Spot Instances

Why Other Options Are Incorrect:

Option A: Simply launching up to maximum capacity does not address availability concerns.

Option B: The diversified strategy spreads instances across Spot pools but does not prioritize capacity.

Option D: Spot Instance Advisor provides recommendations but is not a direct allocation strategy.

Enabling the organizational view in AWS Health will allow the SysOps administrator to consolidate the alerts from each account’s Personal Health Dashboard. It will also provide the administrator with a single view of all the accounts in the organization, allowing them to easily monitor the health of all the accounts in the organization.

To implement a caching service while maintaining high availability for an Amazon RDS DB instance, the combination of Amazon ElastiCache for Redis and enabling Multi-AZ for the data store will meet these requirements.

Create an Amazon ElastiCache for Redis Data Store:

Redis is an in-memory data structure store that can be used as a database, cache, and message broker. It provides high availability through its replication feature.

Go to the ElastiCache console.

Choose "Create" and select "Redis."

Configure the Redis cluster with the required parameters.

Enable Multi-AZ for the Data Store:

Multi-AZ deployment provides enhanced availability and durability for Redis. In case of a failure, it automatically fails over to the replica node.

During the creation of the Redis cluster, enable Multi-AZ.

This ensures that there is a standby replica in another Availability Zone, providing high availability.

Amazon ElastiCache for Redis

ElastiCache for Redis Multi-AZ

To automate the initialization of additional EBS volumes on Windows EC2 instances, the most effective approach is to integrate initialization scripts within the instance so that they execute upon startup:

Configure Initialization Script: Use a Windows PowerShell script (InitializeDisks.ps1) to initialize and format the additional EBS volumes. The script can assign drive letters based on configurations specified in DriveLetterMappingConfig.json.

Automate at Launch: Ensure that the PowerShell script runs automatically upon instance startup. This can be configured through Windows Task Scheduler or by setting it up in the startup folder.

Create a Custom AMI: Once the instance is configured with the script and successfully initializes the disks on startup, create a new AMI from this setup. This AMI can then be used to launch new instances that will automatically initialize their additional EBS volumes with no manual intervention required.

This method leverages native Windows tools and AWS capabilities to automate EBS volume initialization, enhancing operational efficiency without additional external dependencies.

To ensure all objects in the S3 bucket are encrypted, including future objects, the following steps should be taken:

Enable Default Server-Side Encryption:

Edit the properties of the S3 bucket to enable default server-side encryption. This ensures that all new objects written to the bucket are encrypted by default.

Navigate to the S3 console, select the bucket, go to the "Properties" tab, and under "Default encryption", select the encryption method (SSE-S3, SSE-KMS, etc.).

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"

The issues experienced by users with legacy browsers typically stem from the SSL/TLS ciphers that are supported or enforced by the ALB. Modern security policies may exclude older ciphers that are necessary for compatibility with older browsers. Here’s how to resolve it:

Access the ALB Settings: Go to the AWS Management Console, navigate to the ALB settings, and locate the SSL negotiation configurations.

Modify Security Policy: Update the SSL/TLS security policy on the ALB to include ciphers that are compatible with legacy browsers. AWS provides predefined security policies, and some of these policies are designed to support older ciphers while still maintaining a level of security that complies with general best practices.

Apply Changes: Once the security policy is updated, the ALB will start using this new configuration, which should resolve compatibility issues with legacy browsers without needing to replace the SSL certificate or alter the infrastructure.

This solution maintains the operational efficiency of the setup and avoids the need for additional resources like a second ALB or new certificates.

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.

AWS CloudFormation CreationPolicy

Using Creation Policies with CloudFormation

The S3 bucket is being used as the origin for a CloudFront distribution. To serve content via CloudFront:

You must point the DNS record to the CloudFront domain name (e.g., d11111abcdef8.cloudfront.net)

Not directly to the S3 bucket, even if that's the origin

From CloudFront with S3 static website hosting:

To use CloudFront to serve your content, update your DNS settings so your domain name (CNAME) points to your CloudFront distribution.

Amazon Macie is a security service designed to help organizations find, classify, and protect sensitive data stored in Amazon S3. Amazon Macie uses machine learning to automatically discover, classify, and protect sensitive data in Amazon S3. Creating a discovery job with the managed data identifier will allow Macie to identify sensitive personal information in the S3 files and classify it accordingly. Enabling AWS Config and Amazon GuardDuty will not help with this requirement as they are not designed to automatically classify and protect data.

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.

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

AWS Backup supports automated backups for EC2 (including attached EBS volumes). It allows:

Central management

Scheduled daily backups

Low operational overhead

From AWS Backup documentation:

You can create backup plans with schedules and retention rules, and assign resources like EC2 instances for automated backup.

Using AWS Systems Manager Distributor and State Manager is an automated and scalable solution for managing software installation across EC2 instances.

Systems Manager Distributor: Allows packaging and distributing the auditing software across multiple Regions.

State Manager Association: Automates software installation on both existing and new instances, ensuring consistent deployment across all managed instances.

Manually connecting to instances or using Lambda is not scalable or efficient for this type of ongoing software management.

"In EventBridge, you can create an archive of events so that you can easily replay them at a later time. For example, you might want to replay events to recover from errors or to validate new functionality in your application." https://docs.aws.amazon.com/eventbridge/latest/userguide/eb-archive.html

To automate the execution of a Python script every night efficiently:

Convert Python Script to Lambda:

Create an AWS Lambda function and upload the Python script.

Ensure the function has the necessary IAM permissions to perform the required maintenance tasks.

"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

To manage incomplete multipart uploads in an Amazon S3 bucket, creating an S3 Lifecycle rule to specifically address these uploads is the most effective method. The rule can be configured to automatically delete expired multipart upload parts, which helps in cleaning up unused data and reducing storage costs. Option A is correct as it directly addresses the requirement to manage incomplete uploads effectively. Reference on setting up S3 Lifecycle policies can be found here Amazon S3 Lifecycle.

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 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/

Graphical user interface, application, Teams Description automatically generated

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/