Amazon AWS Certified SysOps Administrator - Associate Practice Test Questions, Exam Dumps

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AWS Certified SysOps Administrator - Associate Amazon Practice Test Questions and Exam Dumps

Question No 1:

A company has an internal web application that runs on Amazon EC2 instances behind an Application Load Balancer. The instances run in an Amazon EC2 Auto Scaling group in a single Availability Zone. A SysOps administrator must make the application highly available.

Which action should the SysOps administrator take to meet this requirement?

A. Increase the maximum number of instances in the Auto Scaling group to meet the capacity that is required at peak usage.
B. Increase the minimum number of instances in the Auto Scaling group to meet the capacity that is required at peak usage.
C. Update the Auto Scaling group to launch new instances in a second Availability Zone in the same AWS Region.
D. Update the Auto Scaling group to launch new instances in an Availability Zone in a second AWS Region.

Correct answer: C

Explanation:

To make the web application highly available, the application needs to be distributed across multiple Availability Zones within the same AWS Region. This ensures that if one Availability Zone experiences an outage, the application can still function by serving requests from instances in the other Availability Zone(s).

Let’s evaluate each option:

A. Increasing the maximum number of instances in the Auto Scaling group might help handle increased traffic during peak usage, but it does not address high availability. The application would still be limited to a single Availability Zone, and there is no redundancy in case of a failure within that zone. Thus, A does not meet the high availability requirement.
B. Increasing the minimum number of instances would ensure that a specific number of instances are always running, but this does not address high availability. Again, the instances would still be confined to a single Availability Zone, leaving the application vulnerable to Availability Zone failures. Thus, B is not sufficient for high availability.
C. Updating the Auto Scaling group to launch new instances in a second Availability Zone in the same AWS Region is the correct approach. By using multiple Availability Zones, the application can remain available even if one Availability Zone becomes unavailable. The Application Load Balancer can then distribute traffic across instances in multiple Availability Zones, improving fault tolerance and high availability. Therefore, C is the correct choice.
D. Updating the Auto Scaling group to launch instances in a second AWS Region would add a level of geographic redundancy, but it's more complex and unnecessary for high availability within a single region. The Auto Scaling group and the Application Load Balancer would typically operate within a single region, and introducing multiple regions would add complexity without providing immediate benefit for high availability in this case. Hence, D is not required and is overkill for the given scenario.

In summary, to make the application highly available, the most appropriate action is to distribute the instances across multiple Availability Zones within the same region, as indicated in C.

Question No 2:

A company hosts a website on multiple Amazon EC2 instances that run in an Auto Scaling group. Users are reporting slow responses during peak times between 6 PM and 11 PM every weekend. A SysOps administrator must implement a solution to improve performance during these peak times.

What is the MOST operationally efficient solution that meets these requirements?

A. Create a scheduled Amazon EventBridge (Amazon CloudWatch Events) rule to invoke an AWS Lambda function to increase the desired capacity before peak times.
B. Configure a scheduled scaling action with a recurrence option to change the desired capacity before and after peak times.
C. Create a target tracking scaling policy to add more instances when memory utilization is above 70%.
D. Configure the cooldown period for the Auto Scaling group to modify desired capacity before and after peak times.

Correct answer: B

Explanation:

The company is facing slow responses during peak times on weekends, specifically between 6 PM and 11 PM, and the goal is to improve performance during these times by scaling the Amazon EC2 instances in the Auto Scaling group.

Let's break down the options to determine which provides the most operationally efficient solution:

Option A: Create a scheduled Amazon EventBridge (Amazon CloudWatch Events) rule to invoke an AWS Lambda function to increase the desired capacity before peak times.
This option involves setting up a scheduled event using Amazon EventBridge (formerly CloudWatch Events) to trigger a Lambda function that changes the desired capacity of the Auto Scaling group. While this could technically meet the requirement, it introduces an extra layer of complexity—setting up the Lambda function to modify Auto Scaling settings and managing the event schedule. This solution is not as operationally efficient as others because it requires more manual setup and maintenance. It also involves additional resources, such as Lambda, which makes it less streamlined than other options.

Option B: Configure a scheduled scaling action with a recurrence option to change the desired capacity before and after peak times.
This is the most operationally efficient solution. AWS Auto Scaling allows you to set scheduled scaling actions, which can automatically change the desired capacity of an Auto Scaling group at specified times. In this case, you can configure a scheduled scaling action to increase the desired capacity before the peak times (e.g., 6 PM on weekends) and then scale down after the peak times end (e.g., 11 PM). This solution is simple, direct, and integrated with Auto Scaling, without the need for additional services like Lambda or EventBridge. This is the most automated and easy-to-manage approach to meet the requirement.

Option C: Create a target tracking scaling policy to add more instances when memory utilization is above 70%.
A target tracking scaling policy adjusts the number of instances based on metrics like CPU utilization, memory usage, or other custom metrics. While this approach can help adjust the Auto Scaling group based on resource utilization, it is not directly linked to the specified peak times (6 PM to 11 PM). Memory utilization may not always correlate with peak traffic, and this scaling policy would only react when a certain threshold is crossed, not proactively addressing the time-based demand increase. Therefore, while this could help with scaling based on demand, it is less effective for the defined peak times and doesn't guarantee the performance improvement needed during weekends.

Option D: Configure the cooldown period for the Auto Scaling group to modify desired capacity before and after peak times.
The cooldown period is the amount of time Auto Scaling waits after a scaling action before taking another one. While this setting can help prevent Auto Scaling from making too many rapid adjustments, it does not address the peak demand itself. The cooldown period controls how often scaling actions can occur, but it does not provide a proactive solution to increase capacity during the specified peak times. Therefore, this option would not directly solve the problem of ensuring adequate capacity during peak times.

In conclusion, Option B—configuring a scheduled scaling action with recurrence to adjust capacity before and after the peak times—is the most operationally efficient solution because it directly addresses the time-based demand fluctuations without requiring additional services or complex setups. It provides an automated, integrated solution within Auto Scaling, ensuring the capacity is adequate during peak periods while scaling down during off-peak hours.

Question No 3:

A company is running a website on Amazon EC2 instances behind an Application Load Balancer (ALB). The company configured an Amazon CloudFront distribution and set the ALB as the origin. The company created an Amazon Route 53 CNAME record to send all traffic through the CloudFront distribution. As an unintended side effect, mobile users are now being served the desktop version of the website.

Which action should a SysOps administrator take to resolve this issue?

A. Configure the CloudFront distribution behavior to forward the User-Agent header.

B. Configure the CloudFront distribution origin settings. Add a User-Agent header to the list of origin custom headers.

C. Enable IPv6 on the ALB. Update the CloudFront distribution origin settings to use the dualstack endpoint.

D. Enable IPv6 on the CloudFront distribution. Update the Route 53 record to use the dualstack endpoint.

Correct Answer: A

Explanation:

The issue described involves mobile users being served the desktop version of the website, which suggests that the application is not properly detecting whether the user is on a mobile or desktop device. Typically, websites adapt their content based on the User-Agent header sent by the client, which indicates whether the request is coming from a mobile device or a desktop.

CloudFront and the User-Agent Header:

Amazon CloudFront acts as a content delivery network (CDN) that can cache content and serve it from edge locations. By default, CloudFront may not forward certain HTTP headers, such as the User-Agent header, to the origin (the ALB in this case). This means that the website could be receiving requests from mobile users but without the User-Agent information, resulting in the desktop version of the site being served to mobile users.

To resolve this issue, the SysOps administrator needs to configure CloudFront to forward the User-Agent header to the origin. This allows the ALB to properly detect the type of device (mobile or desktop) making the request and serve the appropriate version of the website.

Steps to Resolve the Issue:

Go to the CloudFront console.
Select the distribution that is configured to use the ALB as the origin.
Modify the cache behavior associated with the distribution.
Configure the behavior to forward the User-Agent header from the viewer request to the origin.

By forwarding the User-Agent header, the origin (ALB) will be able to properly identify whether the user is on a mobile or desktop device and deliver the appropriate version of the website.

Other Options Analysis:

B. Configure the CloudFront distribution origin settings. Add a User-Agent header to the list of origin custom headers: This option suggests adding a custom header at the origin level, but this isn't necessary for resolving the issue. The solution lies in forwarding the User-Agent header from CloudFront to the ALB, rather than adding it as a custom header at the origin level.
C. Enable IPv6 on the ALB. Update the CloudFront distribution origin settings to use the dualstack endpoint: Enabling IPv6 or changing the endpoint type to dualstack (which supports both IPv4 and IPv6) does not address the issue with mobile users being served the desktop version. This option relates to network protocol configurations and is not relevant to solving the device detection problem.
D. Enable IPv6 on the CloudFront distribution. Update the Route 53 record to use the dualstack endpoint: Similar to option C, enabling IPv6 on CloudFront and updating the Route 53 record to use the dualstack endpoint does not address the core issue of serving the correct version of the website to mobile users. This option is related to network configuration, not device detection.

Conclusion: The correct solution to ensure that mobile users are served the mobile version of the website is to configure the CloudFront distribution to forward the User-Agent header to the origin. This will allow the application to detect the type of device and serve the appropriate version of the site. Therefore, the correct answer is A.

Question No 4:

What should the SysOps administrator do to meet the requirement of re-enabling AWS CloudTrail immediately if it is disabled, without writing custom code?

A. Add the AWS account to AWS Organizations. Enable CloudTrail in the management account.
B. Create an AWS Config rule that is invoked when CloudTrail configuration changes. Apply the AWS-ConfigureCloudTrailLogging automatic remediation action.
C. Create an AWS Config rule that is invoked when CloudTrail configuration changes. Configure the rule to invoke an AWS Lambda function to enable CloudTrail.
D. Create an Amazon EventBridge (Amazon CloudWatch Event) hourly rule with a schedule pattern to run an AWS Systems Manager Automation document to enable CloudTrail.

Correct Answer: B

Explanation:

To meet the requirement of automatically re-enabling AWS CloudTrail if it is disabled, AWS Config is the best tool for this task, as it enables continuous monitoring and remediation without the need to write custom code. Let's break down the options:

A. Add the AWS account to AWS Organizations. Enable CloudTrail in the management account.

Adding an AWS account to AWS Organizations and enabling CloudTrail in the management account can help centrally manage and track CloudTrail configuration across multiple accounts. However, this doesn't directly address the requirement of re-enabling CloudTrail automatically if it is disabled. The solution still requires manual intervention or a more automated approach to ensure CloudTrail is immediately re-enabled if it gets disabled. Therefore, A is not the correct option.

B. Create an AWS Config rule that is invoked when CloudTrail configuration changes. Apply the AWS-ConfigureCloudTrailLogging automatic remediation action.

This is the correct approach. AWS Config allows you to create compliance rules that monitor the configuration of AWS resources. In this case, an AWS Config rule can monitor the CloudTrail configuration and check if it is disabled. When this rule detects that CloudTrail is disabled, it can automatically apply the AWS-ConfigureCloudTrailLogging automatic remediation action, which will re-enable CloudTrail without requiring any custom code. This is a straightforward solution to meet the requirement. Therefore, B is the correct answer.

C. Create an AWS Config rule that is invoked when CloudTrail configuration changes. Configure the rule to invoke an AWS Lambda function to enable CloudTrail.

While creating a Config rule that invokes an AWS Lambda function can also re-enable CloudTrail, it requires writing custom code for the Lambda function to specifically handle the enabling of CloudTrail. The question explicitly asks for a solution that does not require custom code, making C an incorrect choice for this requirement.

D. Create an Amazon EventBridge (Amazon CloudWatch Event) hourly rule with a schedule pattern to run an AWS Systems Manager Automation document to enable CloudTrail.

Using Amazon EventBridge with a schedule to invoke an AWS Systems Manager Automation document can certainly help automate tasks, but it requires more complex setup and is not as direct as the solution using AWS Config. This solution also involves setting up scheduled checks, whereas AWS Config provides a more efficient and immediate reaction to configuration changes (like CloudTrail being disabled). Therefore, D is more complex than necessary and doesn't fully align with the requirement.

To immediately re-enable CloudTrail when it is disabled without writing custom code, the best approach is to use AWS Config with an automatic remediation action. B is the correct solution because it enables the automatic enforcement of CloudTrail's configuration without requiring custom Lambda functions or complex scheduled tasks.

Question No 5:

A company hosts its website on Amazon EC2 instances behind an Application Load Balancer. The company manages its DNS with Amazon Route 53 and wants to point its domain's zone apex to the website.

Which type of record should be used to meet these requirements?

A. An AAAA record for the domain’s zone apex
B. An A record for the domain’s zone apex
C. A CNAME record for the domain’s zone apex
D. An alias record for the domain’s zone apex

Correct answer: D

Explanation:

In Amazon Route 53, when pointing the domain’s zone apex (the root domain, such as example.com) to an Amazon resource like an Elastic Load Balancer (ELB), you need to use an alias record. Alias records are a unique feature of Route 53 that allow you to map the root domain (zone apex) to AWS resources such as an Application Load Balancer, CloudFront distribution, or S3 bucket without needing an IP address.

The key reason to use an alias record instead of a traditional DNS record (like an A or CNAME record) is that Route 53 supports alias records at the zone apex, while traditional DNS specifications do not allow CNAME records for the apex domain.

Let’s review the other options:

Option A (An AAAA record for the domain’s zone apex): An AAAA record maps a domain name to an IPv6 address. While this can be used for pointing to an IPv6 address, it is not suitable for pointing to an Elastic Load Balancer, which uses a DNS name rather than a specific IP address.

Option B (An A record for the domain’s zone apex): An A record maps a domain to an IP address. You could use an A record if you had a static IP, but since ELB instances do not have static IPs, this is not the correct approach. For Amazon EC2 instances behind an Application Load Balancer, you should use an alias record to point to the load balancer.

Option C (A CNAME record for the domain’s zone apex): CNAME records cannot be used for the zone apex of a domain. CNAME records are typically used for subdomains (e.g., www.example.com), but they are not allowed at the root level of the domain (e.g., example.com). Therefore, a CNAME record will not work for pointing the zone apex to the website.

Option D (An alias record for the domain’s zone apex): Correct. Alias records are designed specifically for AWS resources and can point the domain apex to resources such as Application Load Balancers in Route 53. Alias records eliminate the need for managing IP addresses and are fully integrated with AWS services like EC2 and ELB.

Question No 6:

What actions will ensure that any objects uploaded to an S3 bucket are encrypted? (Choose two.)

A. Implement AWS Shield to protect against unencrypted objects stored in S3 buckets.
B. Implement Object access control list (ACL) to deny unencrypted objects from being uploaded to the S3 bucket.
C. Implement Amazon S3 default encryption to make sure that any object being uploaded is encrypted before it is stored.
D. Implement Amazon Inspector to inspect objects uploaded to the S3 bucket to make sure that they are encrypted.
E. Implement S3 bucket policies to deny unencrypted objects from being uploaded to the buckets.

Correct Answers: C, E

Explanation:

To ensure that all objects uploaded to an Amazon S3 bucket are encrypted, we need to focus on methods that enforce encryption during the upload process and prevent the upload of unencrypted objects. Let’s analyze each option:

Option A: Implement AWS Shield to protect against unencrypted objects stored in S3 buckets

AWS Shield is a managed DDoS protection service that defends against distributed denial-of-service attacks. While AWS Shield provides protection against such attacks, it does not address object encryption in S3 buckets. Shield does not provide any encryption-related functionality, so this option is not relevant to the requirement of ensuring uploaded objects are encrypted. Therefore, A is incorrect.

Option B: Implement Object access control list (ACL) to deny unencrypted objects from being uploaded to the S3 bucket

ACLs in Amazon S3 control access to objects at a granular level (e.g., specifying who can read or write to a specific object). However, ACLs cannot be used to enforce encryption on uploaded objects. ACLs can only control permissions, not encryption rules. Therefore, B is not an appropriate solution for ensuring that all objects are encrypted before being uploaded to the S3 bucket.

Option C: Implement Amazon S3 default encryption to make sure that any object being uploaded is encrypted before it is stored

This is the correct answer. Amazon S3 default encryption allows you to automatically encrypt all objects uploaded to an S3 bucket without requiring the client to specify encryption settings. You can configure default encryption to use either SSE-S3 (server-side encryption with S3-managed keys) or SSE-KMS (server-side encryption with AWS Key Management Service-managed keys). This ensures that all objects uploaded to the S3 bucket will be encrypted automatically, even if the upload request does not explicitly specify encryption. Therefore, C is a valid solution.

Option D: Implement Amazon Inspector to inspect objects uploaded to the S3 bucket to make sure that they are encrypted

Amazon Inspector is a security assessment service that helps identify vulnerabilities in applications deployed on Amazon EC2 and other AWS resources. While it can assess security aspects, it is not designed to inspect or enforce encryption on objects uploaded to Amazon S3. Therefore, D is not the correct solution for enforcing encryption on S3 objects.

Option E: Implement S3 bucket policies to deny unencrypted objects from being uploaded to the buckets

This is also a correct answer. You can create an S3 bucket policy that denies the upload of objects that are not encrypted. The policy can be written to check for the presence of encryption and deny any requests that do not meet this condition. For example, you can write a policy that only allows objects uploaded with encryption enabled (either SSE-S3 or SSE-KMS). This ensures that no unencrypted objects can be uploaded to the bucket, providing an additional layer of security.

In conclusion, to ensure that all objects uploaded to an S3 bucket are encrypted, you can:

Implement S3 default encryption to automatically encrypt uploaded objects.
Implement S3 bucket policies to deny uploads of unencrypted objects.

Question No 7:

What combination of actions should a SysOps administrator take to resolve random logouts from a stateful web application hosted behind an ALB and CloudFront?

A. Change to the least outstanding requests algorithm on the ALB target group.
B. Configure cookie forwarding in the CloudFront distribution cache behavior.
C. Configure header forwarding in the CloudFront distribution cache behavior.
D. Enable group-level stickiness on the ALB listener rule.
E. Enable sticky sessions on the ALB target group.

Correct Answer: B, E

Explanation:

The scenario describes a stateful web application hosted on Amazon EC2 instances in an Auto Scaling group, with an Application Load Balancer (ALB) as the frontend. The application is also behind a CloudFront distribution, and users are experiencing random logouts, which is likely related to session persistence or sticky sessions. Let’s examine each option to resolve this issue:

Option A: Change to the least outstanding requests algorithm on the ALB target group
The least outstanding requests algorithm helps distribute traffic across instances that currently have the least load, meaning it attempts to balance traffic based on current request loads. However, this does not directly solve the sticky session issue, where users need to maintain consistent session data with the same backend instance. This option would help with load balancing efficiency but won’t specifically address the root cause of the random logouts. Therefore, A is incorrect.

Option B: Configure cookie forwarding in the CloudFront distribution cache behavior
When using CloudFront as a CDN in front of an ALB, it’s crucial to manage how cookies are handled. Cookie forwarding ensures that CloudFront forwards cookies from the client request to the ALB, which allows for session persistence. If cookies are not forwarded correctly, CloudFront might route requests to different EC2 instances in the Auto Scaling group, causing the user to lose session data, leading to random logouts. This option directly addresses the issue of session persistence by enabling cookie forwarding. Therefore, B is correct.

Option C: Configure header forwarding in the CloudFront distribution cache behavior
Header forwarding typically allows CloudFront to forward headers, such as user-agent or authorization headers, to the ALB for more granular routing decisions. While this can be useful for caching or specific routing needs, it does not directly address sticky session issues or session persistence. Therefore, C is incorrect in solving the random logout problem.

Option D: Enable group-level stickiness on the ALB listener rule
Group-level stickiness refers to a setting where an ALB routes all requests from a given client to a specific target group. This doesn’t directly solve the problem since sticky sessions are generally configured at the target group level (not listener rules). While it might help in some cases, it is not the best practice or most direct solution. Therefore, D is incorrect.

Option E: Enable sticky sessions on the ALB target group
Sticky sessions (also known as session affinity) allow the ALB to maintain the session for a specific user by ensuring that all requests from that user are directed to the same backend EC2 instance. This is a key feature for stateful applications, where session data is stored locally on the instance. Enabling sticky sessions on the ALB target group is essential for preventing random logouts as it ensures users are consistently directed to the same instance. Therefore, E is correct.

The issue of random logouts in a stateful web application is most likely caused by session persistence issues, which can be addressed by enabling cookie forwarding in CloudFront and enabling sticky sessions on the ALB target group. These actions ensure that session data is preserved across requests and that users consistently hit the same backend instance.

Question No 8:

What should a SysOps administrator do to resolve the "too many connections" errors that occur when the AWS Lambda function attempts to connect to the Amazon RDS for MySQL DB instance, given that the company has already configured the database to use the maximum max_connections value?

A. Create a read replica of the database. Use Amazon Route 53 to create a weighted DNS record that contains both databases.
B. Use Amazon RDS Proxy to create a proxy. Update the connection string in the Lambda function.
C. Increase the value in the max_connect_errors parameter in the parameter group that the database uses.
D. Update the Lambda function’s reserved concurrency to a higher value.

Correct Answer: B

Explanation:

The issue described — "too many connections" errors — occurs when the number of simultaneous database connections exceeds the configured limit. Since the company has already reached the maximum value for max_connections, the solution needs to handle connections more efficiently to reduce the pressure on the database.

Option B, Use Amazon RDS Proxy to create a proxy, is the correct solution. Amazon RDS Proxy is a fully managed, highly available database proxy for Amazon RDS that helps to manage database connections more efficiently. It acts as a connection pooler, which helps to reduce the number of active connections to the database by pooling and reusing connections. This is especially useful in serverless environments like AWS Lambda, where the function may open many short-lived connections to the database. By using RDS Proxy, you can mitigate the "too many connections" errors and manage the connections more effectively. To implement this, you would update the Lambda function’s connection string to point to the RDS Proxy instead of directly connecting to the RDS database.

Let’s review the other options:

Option A, Create a read replica of the database, would provide a read-only copy of the database, but this does not directly address the issue of too many connections. Creating a read replica is typically used for scaling read operations, not for managing excessive connections. Additionally, using Route 53 to create a weighted DNS record to load balance between the primary and replica databases would not help mitigate the connection problem, as both databases would likely still have connection limits.

Option C, Increase the value in the max_connect_errors parameter, is not the right solution because max_connect_errors is a parameter that determines how many connection attempts from a specific host can fail before the server blocks further attempts from that host. This parameter is unrelated to managing the total number of allowed connections (max_connections). The error the application is encountering is related to too many connections, not connection failures, so this adjustment would not resolve the issue.

Option D, Update the Lambda function’s reserved concurrency, would not directly address the root cause of the issue. Increasing the reserved concurrency for the Lambda function would allocate more concurrent execution slots for Lambda, but it would not solve the issue of the Lambda function exhausting the available database connections. The problem lies in the database connection limit, which requires a solution like RDS Proxy to manage connections efficiently.

In summary, Option B is the best choice because it addresses the connection management problem by using Amazon RDS Proxy to efficiently pool and manage database connections, allowing the Lambda function to avoid exhausting the max_connections limit on the database.

Question No 9:

A SysOps administrator is deploying an application on 10 Amazon EC2 instances. The application must be highly available. The instances must be placed on distinct underlying hardware.

What should the SysOps administrator do to meet these requirements?

A. Launch the instances into a cluster placement group in a single AWS Region.
B. Launch the instances into a partition placement group in multiple AWS Regions.
C. Launch the instances into a spread placement group in multiple AWS Regions.
D. Launch the instances into a spread placement group in a single AWS Region.

Correct answer: D

Explanation:

To achieve high availability and ensure that EC2 instances are placed on distinct underlying hardware, the spread placement group is the most suitable choice. This type of placement group helps distribute instances across different hardware within a single availability zone, which minimizes the risk of correlated failures.

Let's break down each option and why D is the best answer:

Cluster placement group in a single AWS Region:

A cluster placement group is designed for high-performance computing (HPC) applications where instances need to be close together in terms of network latency for high-bandwidth applications. However, instances in a cluster placement group are not distributed across distinct hardware. This means that if underlying hardware fails, multiple instances in the cluster could be affected. This does not meet the requirement of ensuring instances are placed on distinct hardware, so this option is not appropriate.

Partition placement group in multiple AWS Regions:

A partition placement group is used for distributed applications that require high availability across multiple partitions (such as Hadoop or Cassandra). This allows instances to be spread across different partitions in a single region. However, using multiple regions is not typically necessary for applications within a single region. Multiple regions could introduce unnecessary complexity and latency issues, and it doesn’t directly address the need for instances to be placed on distinct underlying hardware in a single region. This option is not ideal for the requirements.

Spread placement group in multiple AWS Regions:

A spread placement group ensures that instances are spread across distinct underlying hardware within a single availability zone or region. While this option is valid for ensuring instances are placed on distinct hardware, using multiple regions is unnecessary and could increase network latency and complexity. The requirement of high availability can be met effectively by placing the instances in a spread placement group within a single region, making this option overcomplicated.

Spread placement group in a single AWS Region:

A spread placement group in a single region is the most appropriate solution. This placement group ensures that instances are placed on different physical hardware in the same availability zone or across multiple availability zones within the region. This minimizes the risk of correlated failures due to hardware issues. Since the requirement is to place instances on distinct underlying hardware while maintaining high availability, a spread placement group in a single AWS Region is the optimal choice.

In conclusion, the best option to ensure that the EC2 instances are placed on distinct underlying hardware while maintaining high availability is D, launching the instances into a spread placement group in a single AWS Region.

Question No 10:

A SysOps administrator is troubleshooting an AWS CloudFormation template whereby multiple Amazon EC2 instances are being created. The template is working in us-east-1, but it is failing in us-west-2 with the error code: AMI [ami-12345678] does not exist.

How should the Administrator ensure that the AWS CloudFormation template is working in every region?

A. Copy the source region’s Amazon Machine Image (AMI) to the destination region and assign it the same ID.
B. Edit the AWS CloudFormation template to specify the region code as part of the fully qualified AMI ID.
C. Edit the AWS CloudFormation template to offer a drop-down list of all AMIs to the user by using the AWS::EC2::AMI::ImageID control.
D. Modify the AWS CloudFormation template by including the AMI IDs in the Mappings section. Refer to the proper mapping within the template for the proper AMI ID.

Correct Answer: D

Explanation:

When working with AWS CloudFormation templates that deploy resources across multiple regions, it's common to encounter issues where resources, such as Amazon Machine Images (AMIs), are region-specific. In this case, the administrator is seeing an error because the AMI ID ami-12345678 exists in the us-east-1 region but not in the us-west-2 region. To resolve this and ensure the template works in every region, you should modify the template to account for region-specific AMI IDs.

The best solution is to use the Mappings section in the CloudFormation template. This allows you to define a set of key-value pairs that map region names to corresponding AMI IDs. You can then use these mappings within the template to reference the correct AMI ID based on the region where the stack is being created.

Here’s why the other options are not ideal:

A. Copy the source region’s Amazon Machine Image (AMI) to the destination region and assign it the same ID.
This option is not a recommended practice because AMI IDs are unique to each region. Copying the AMI would create a new AMI ID in the destination region, and the CloudFormation template would still fail to recognize the AMI because the ID would be different in the destination region. The solution lies in referencing the correct region-specific AMI ID.

B. Edit the AWS CloudFormation template to specify the region code as part of the fully qualified AMI ID.
While you can refer to the AMI using a fully qualified ID, the CloudFormation template does not support specifying the region code as part of the AMI ID directly in the way suggested. Region-specific AMI IDs are required, and this would not solve the problem in a scalable manner across multiple regions.

C. Edit the AWS CloudFormation template to offer a drop-down list of all AMIs to the user by using the AWS::EC2::AMI::ImageID control.
AWS CloudFormation does not natively support a drop-down list for AMIs or user input for the ImageID in the way described here. The approach of defining the correct AMI in the template itself using mappings is more effective and automates the process.

Therefore, D is the correct solution because the Mappings section is the proper way to ensure that your template can handle region-specific resources like AMI IDs, allowing the CloudFormation stack to deploy successfully in multiple regions.