In this scenario, VPC A has a CIDR block of 10.0.0.0/16, which allows for IP addresses ranging from 10.0.0.0 to 10.0.255.255, while VPC B has a CIDR block of 10.1.0.0/16, covering IP addresses from 10.1.0.0 to 10.1.255.255. Since these CIDR blocks do not overlap, they can successfully communicate through the peering connection once it is established. While configuring security groups to allow traffic, setting up route tables, and enabling DNS resolution are also important steps in the process, they are secondary to the fundamental requirement of non-overlapping CIDR blocks. If the CIDR blocks were overlapping, no amount of configuration would allow for successful communication between the VPCs. Therefore, understanding and verifying the CIDR block configuration is paramount before proceeding with any other setup tasks. This highlights the importance of proper network design and planning in AWS environments, especially when dealing with multiple accounts and VPCs.

In the context of the security analyst’s findings, emphasizing the principle of least privilege would lead to a more robust security posture. It encourages the organization to not only focus on external threats but also to scrutinize internal access controls and permissions. This approach aligns with the need for comprehensive assessments that include internal vulnerabilities, as it helps identify and rectify excessive permissions that could be exploited by malicious insiders or compromised accounts. On the other hand, the principle of full disclosure, while important for transparency, does not directly contribute to the internal security posture. Black-box testing focuses on external assessments without prior knowledge of the system, which is not applicable when addressing internal vulnerabilities. Lastly, non-repudiation relates to ensuring accountability for actions taken within a system, but it does not address the proactive measures needed to secure access controls and permissions. Thus, the principle of least privilege stands out as the most relevant and effective principle to emphasize in this scenario.

In the context of the security analyst’s findings, emphasizing the principle of least privilege would lead to a more robust security posture. It encourages the organization to not only focus on external threats but also to scrutinize internal access controls and permissions. This approach aligns with the need for comprehensive assessments that include internal vulnerabilities, as it helps identify and rectify excessive permissions that could be exploited by malicious insiders or compromised accounts. On the other hand, the principle of full disclosure, while important for transparency, does not directly contribute to the internal security posture. Black-box testing focuses on external assessments without prior knowledge of the system, which is not applicable when addressing internal vulnerabilities. Lastly, non-repudiation relates to ensuring accountability for actions taken within a system, but it does not address the proactive measures needed to secure access controls and permissions. Thus, the principle of least privilege stands out as the most relevant and effective principle to emphasize in this scenario.

To calculate the number of missed violations, we can use the following formula: \[ \text{Missed Violations} = \text{Total Compliance Checks} \times (1 – \text{Accuracy Rate}) \] Substituting the values into the formula: \[ \text{Missed Violations} = 200 \times (1 – 0.95) = 200 \times 0.05 = 10 \] This calculation shows that the system would likely miss 10 compliance violations out of the 200 checks. Understanding continuous compliance monitoring is crucial for organizations, especially in regulated industries. Continuous compliance involves not just periodic audits but ongoing assessments of security controls and configurations against established standards such as ISO 27001, NIST SP 800-53, or industry-specific regulations like HIPAA or PCI DSS. The effectiveness of such systems is often measured by their accuracy and the rate at which they can detect deviations from compliance. In this scenario, the implications of missing compliance violations can be significant, leading to potential security breaches, regulatory fines, or reputational damage. Therefore, organizations must continuously evaluate and improve their monitoring systems to enhance accuracy and reduce the risk of non-compliance. This includes regular updates to compliance standards, training for personnel, and leveraging advanced technologies such as machine learning to improve detection capabilities.

While manually removing the malicious software from each affected system may seem thorough, it carries a significant risk of human error and may not guarantee that all traces of the malware are removed. Additionally, this method can be time-consuming and may lead to inconsistencies across systems. Implementing a network segmentation strategy is a proactive measure that can help contain future incidents but does not directly address the current threat. It is more of a preventive measure rather than a solution for eradication. Updating all software and applying security patches is essential for maintaining a secure environment, but it does not directly remove the existing threat. If the malware is still present, simply updating software may not be sufficient to eradicate it. Therefore, the priority should be on conducting a full system wipe and restoring from a clean backup, as this method provides the highest assurance that the threat has been completely eradicated while allowing the organization to return to a secure operational state. This approach aligns with best practices outlined in frameworks such as NIST SP 800-61, which emphasizes the importance of thorough eradication in the incident response lifecycle.

AWS IAM policies are evaluated based on a set of rules where explicit denies take precedence over allows. By creating a policy that denies access to sensitive data for users in conflicting groups, the security team can enforce stricter access controls without needing to overhaul the entire group structure. This approach also aligns with compliance requirements, as it minimizes the risk of unauthorized access to sensitive information. On the other hand, simply removing users from all groups (option b) could disrupt their ability to perform their jobs, as they may lose necessary permissions. Increasing permissions across the board (option c) contradicts the principle of least privilege and could expose sensitive data unnecessarily. Lastly, creating a new group that consolidates permissions (option d) may lead to further complications and does not address the underlying issue of conflicting permissions. Therefore, the most effective solution is to implement explicit deny policies to manage access appropriately.

For instance, in VPC A’s route table, a route should be added that directs traffic for 10.1.0.0/16 to the peering connection. Similarly, VPC B’s route table must include a route for 10.0.0.0/16. This two-way routing is crucial for bi-directional communication. Moreover, security groups must be configured to allow traffic from the CIDR block of the peer VPC. This means that if instances in VPC A need to communicate with instances in VPC B, the security group rules in VPC A must permit inbound traffic from 10.1.0.0/16, and vice versa for VPC B. The other options present various shortcomings. For example, modifying only one route table (as in option b) would prevent instances in VPC B from initiating communication with instances in VPC A. Using the same security group across both VPCs (as in option c) is not feasible since security groups are specific to a VPC and cannot span multiple VPCs. Lastly, enabling DNS resolution without updating the route tables (as in option d) would not facilitate any communication, as the necessary routing paths would still be absent. In summary, the correct approach involves establishing the peering connection, updating both route tables, and configuring security groups appropriately to ensure secure and efficient communication between the two VPCs.

The correct configuration involves setting the threshold for average CPU utilization at 75% and evaluating the metric every 1 minute. This means that the alarm will check the average CPU utilization every minute, allowing for a more responsive monitoring setup. By requiring the condition to be met for 2 consecutive periods, the team ensures that transient spikes in CPU usage do not trigger unnecessary alerts, which could lead to alarm fatigue. Option b is incorrect because it uses maximum CPU utilization instead of average, which does not align with the requirement. Option c incorrectly monitors minimum CPU utilization, which is not relevant to the scenario. Lastly, option d evaluates every 5 minutes and only requires 1 consecutive period, which does not meet the specified requirement of 2 consecutive evaluations. In summary, the correct approach is to create a CloudWatch alarm that monitors average CPU utilization with a threshold of 75%, evaluated every 1 minute, and configured to trigger if the condition is met for 2 consecutive periods. This setup ensures that the team receives timely and relevant alerts regarding their application’s performance, allowing them to take appropriate action when necessary.

For data at rest, AES is the preferred encryption standard due to its efficiency and security. AES is a symmetric encryption algorithm that is widely recognized for its strength and speed, making it suitable for encrypting large volumes of data. It supports key lengths of 128, 192, and 256 bits, providing flexibility in security levels based on the sensitivity of the data. In contrast, the other options present various weaknesses. SSL is outdated and less secure than TLS, while RSA is primarily used for secure key exchange rather than bulk data encryption. Relying solely on HTTPS does not provide protection for data at rest, which is critical for compliance with regulations such as GDPR or PCI DSS. Lastly, while IPsec can secure data in transit, 3DES is considered weak by modern standards and is not recommended for protecting sensitive information. Thus, the combination of TLS for data in transit and AES for data at rest represents a comprehensive approach to safeguarding sensitive customer data, ensuring compliance with industry regulations, and maintaining a robust security posture.

On the other hand, AWS Managed Keys (also known as AWS Key Management Service (KMS) keys) are designed for ease of use and are automatically managed by AWS. While they simplify the key management process, they do not offer the same level of control as CMKs. Organizations using AWS Managed Keys cannot customize key policies or perform detailed audits of key usage, which may not satisfy the compliance requirements of a financial institution. A hybrid approach using both key types could provide some flexibility, but it may complicate the key management process and still fall short of the institution’s need for strict control. Relying on no encryption at all would expose sensitive customer data to significant risks, making it an unacceptable option. In summary, for organizations that require stringent control over key management, especially in regulated environments, Customer Managed Keys are the most suitable choice. They enable organizations to meet compliance requirements effectively while maintaining the necessary security posture.

Regular code reviews are a critical component of this strategy, as they allow for peer evaluation of code, ensuring that security best practices are followed and that any overlooked vulnerabilities are caught before the application goes live. This aligns with the OWASP Top Ten, which emphasizes the importance of secure coding practices to mitigate risks associated with common vulnerabilities such as SQL injection and cross-site scripting (XSS). In contrast, relying solely on automated security testing tools after deployment (as suggested in option b) can lead to significant gaps in security, as these tools may not catch all vulnerabilities and often require human oversight to interpret results accurately. Focusing exclusively on network security measures (option c) neglects the application layer, which is often the target of attacks. Lastly, while conducting security training for end-users (option d) is important, it does not address the inherent security issues within the application itself. Therefore, a holistic approach that includes secure coding practices, regular code reviews, and adherence to established security frameworks is essential for building a secure application that complies with industry standards.

The “Identify” function encompasses several key activities, such as asset management, governance, risk assessment, and risk management strategy. These activities help organizations to recognize their critical assets and the threats they face, which is essential for informed decision-making. This foundational understanding is vital for the subsequent functions of the framework—Protect, Detect, Respond, and Recover—ensuring that the organization can implement appropriate measures to mitigate risks effectively. In contrast, focusing solely on technical controls (as suggested in option b) neglects the broader context of risk management and may lead to gaps in security. Similarly, concentrating only on incident response (option c) without integrating it into the overall risk management strategy can result in reactive rather than proactive security measures. Lastly, ensuring compliance with external regulations (option d) without considering the organization’s unique risk profile can lead to a false sense of security, as compliance does not necessarily equate to effective risk management. Thus, the primary purpose of the “Identify” function is to develop a thorough understanding of the organization’s risk environment, which is essential for establishing a robust risk management framework that aligns with the organization’s objectives and enhances its overall cybersecurity posture.

Regarding Network ACLs, the public subnet should allow all outbound traffic to ensure that the web application can communicate freely with the database. The private subnet’s Network ACL should be configured to allow inbound traffic specifically from the web application’s security group on port 3306, ensuring that only legitimate requests from the web application reach the database. This layered security approach, combining security groups and Network ACLs, adheres to the principle of least privilege, which is a fundamental concept in cloud security. The other options present various flaws: allowing unrestricted access to the database from any IP address (option b) compromises security; denying all outbound traffic from the public subnet (option c) would prevent the web application from functioning correctly; and allowing inbound traffic from the internet to the database (option d) exposes the database to potential attacks. Thus, the outlined configuration effectively meets the security requirements while maintaining necessary functionality.

On the other hand, IAM roles provide a secure way to grant permissions to your EC2 instances to access other AWS services without embedding static credentials in your application. This is a best practice as it allows for temporary credentials that are automatically rotated, reducing the risk of credential leakage. In contrast, configuring NACLs to allow all traffic (as suggested in option b) undermines the security benefits of using security groups, as it opens the network to potential threats. Similarly, using IAM users with static credentials (option c) is not recommended due to the security risks associated with managing static credentials. Lastly, allowing all traffic in security groups while using NACLs to block specific IPs (option d) is ineffective because it does not prevent unauthorized access from other sources. Thus, the best strategy combines the use of security groups to restrict traffic effectively and IAM roles to manage permissions securely, ensuring a robust security posture for the EC2 instances while allowing necessary traffic for the application to function correctly.

To achieve this, the SCP must first explicitly deny access to the S3 service for all accounts in the organization. This is done by creating a policy that includes a “Deny” statement for the S3 service. However, since the finance department needs access to S3, the SCP must also include an exception that allows access specifically for the finance department’s account. This is accomplished by specifying the account ID of the finance department in an “Allow” statement that overrides the general “Deny” for that specific account. The other options present flawed approaches. Allowing access to S3 for all accounts (option b) would not meet the requirement of restricting access for other departments. Denying access for the finance department (option c) contradicts their need for access. Lastly, simply allowing access for the finance department without specifying account IDs (option d) would not effectively restrict access for other departments, as it would not create a clear boundary for the policy application. Thus, the correct structure of the SCP is to deny access to S3 for all accounts while allowing access for the finance department, ensuring compliance and security across the organization. This nuanced understanding of SCPs and their hierarchical nature is crucial for effectively managing permissions in AWS Organizations.

In this scenario, the finance department user is attempting to access a database that resides within the operations micro-segment. Given that ZTA employs micro-segmentation, each segment has its own access policies tailored to the specific roles and responsibilities of users. Since the finance user does not have the necessary permissions to access resources in the operations segment, the ZTA will enforce the access control policies that have been established. This means that the user will be denied access outright, as their role does not align with the permissions required to access the operations database. This strict enforcement of access controls is crucial in preventing lateral movement within the network, which is a common tactic used by attackers to exploit vulnerabilities. The other options present misconceptions about how ZTA operates. Granting access solely based on organizational affiliation undermines the Zero Trust principle. Allowing temporary access while performing a security check could introduce risks, as it does not adhere to the strict access policies. Monitoring for unusual activity after granting access does not address the fundamental issue of unauthorized access and could lead to potential data breaches. Thus, the expected behavior of the ZTA in this context is to deny access to the user from the finance department, reinforcing the importance of stringent access controls and the principle of least privilege in a Zero Trust environment.

In contrast, manually configuring the Lambda function and API Gateway through the AWS Management Console may provide immediate control over settings, but it lacks the benefits of automation, versioning, and repeatability that infrastructure as code offers. This method can lead to configuration drift and is not ideal for maintaining high availability and cost-effectiveness in a production environment. Using AWS CloudFormation directly is a valid approach, but it does not provide the same level of abstraction and ease of use as the CDK. The CDK allows developers to leverage programming constructs, making it easier to manage complex infrastructure setups and integrate with existing codebases. Lastly, while third-party tools for infrastructure management may offer additional features, they can introduce complexity and potential compatibility issues with AWS services. Relying on AWS CDK ensures that the team is using a native AWS solution that is continuously updated and supported by AWS, thus providing a more seamless experience for deploying and managing serverless applications. Overall, the best approach for the team is to utilize AWS CDK to define their infrastructure, ensuring scalability, maintainability, and cost-effectiveness.

Furthermore, the requirement to create the S3 bucket only if the RDS instance is successfully provisioned can be accomplished using the `DependsOn` attribute. This attribute explicitly defines the order of resource creation, ensuring that the S3 bucket is created only after the RDS instance has been successfully provisioned. This is crucial because it prevents any potential race conditions where the S3 bucket might be created before the RDS instance is ready, which could lead to misconfigurations or access issues. The other options present various shortcomings. For instance, creating a separate CloudFormation stack for the RDS instance complicates the infrastructure management process and does not directly address the dependency requirement for the S3 bucket. Using the `Condition` function without specifying a security group for the EC2 instance fails to enforce the necessary access restrictions, potentially exposing the RDS database and S3 bucket to unwanted access. Lastly, implementing an IAM policy alone does not provide the necessary network-level security that security groups offer, which is essential for controlling traffic between resources in a VPC. Thus, the best approach is to combine the use of the `DependsOn` attribute for the S3 bucket and the `SecurityGroupIds` property for the EC2 instance, ensuring both the correct provisioning order and access control are maintained.

\[ \text{Current Total Time} = \text{Detection Time} + \text{Response Time} = 30 \text{ minutes} + 90 \text{ minutes} = 120 \text{ minutes} \] The institution aims to reduce the overall incident response time by 50%. This reduction applies to the total time, not just the response time. Thus, we calculate the reduction as follows: \[ \text{Reduction} = 0.50 \times \text{Current Total Time} = 0.50 \times 120 \text{ minutes} = 60 \text{ minutes} \] Now, we subtract the reduction from the current total time to find the new average total time: \[ \text{New Total Time} = \text{Current Total Time} – \text{Reduction} = 120 \text{ minutes} – 60 \text{ minutes} = 60 \text{ minutes} \] This scenario illustrates the importance of security automation in incident response, as it not only streamlines processes but also significantly reduces the time taken to detect and respond to incidents. By automating repetitive tasks and integrating systems, organizations can enhance their security posture and ensure quicker remediation of threats. This aligns with best practices in security orchestration, which emphasize the need for efficient workflows and timely responses to minimize potential damage from security incidents.

Implementing automated security scanning tools is an effective strategy for enhancing the security of IaC deployments. These tools can analyze CloudFormation templates for IAM policy permissions, identifying overly permissive policies and suggesting adjustments to adhere to the principle of least privilege. This approach not only streamlines the review process but also ensures that security checks are consistently applied across all templates, reducing the risk of human error that can occur during manual reviews. On the other hand, while manual reviews (option b) can be beneficial, they are often time-consuming and prone to oversight, especially in larger environments with numerous templates. Centralizing IAM policies (option c) contradicts the principle of least privilege, as it can lead to excessive permissions being granted to users or services that do not require them. Lastly, creating a separate CloudFormation stack for IAM roles and policies (option d) may complicate management and does not inherently address the issue of overly permissive permissions. In summary, leveraging automated security scanning tools provides a scalable and efficient method to ensure that IAM roles and policies in CloudFormation templates are aligned with security best practices, thereby enhancing the overall security posture of the IaC deployment.

On the other hand, using a single IAM role with broad permissions (option b) can lead to significant security vulnerabilities, as it increases the attack surface and makes it easier for malicious actors to exploit any function. Storing sensitive data in plaintext (option c) is a critical mistake, as it exposes the data to potential breaches and does not comply with best practices for data protection, which typically require encryption both at rest and in transit. Lastly, relying solely on the built-in security features of the serverless platform (option d) is insufficient, as it does not account for the unique security challenges posed by serverless architectures, such as function-level vulnerabilities and the need for comprehensive monitoring and logging. In summary, the correct strategy involves a proactive approach to security by implementing fine-grained access controls, which not only protects sensitive data but also supports compliance with relevant regulations, ensuring that the serverless application remains secure while benefiting from the scalability that serverless architectures provide.

In this context, the hybrid model facilitates a dual approach: local teams can address specific risks and compliance issues pertinent to their regions, while the central governance body ensures that these localized strategies align with the organization’s overall security objectives. This adaptability is crucial in a global landscape where regulations can vary significantly, such as the General Data Protection Regulation (GDPR) in Europe versus the California Consumer Privacy Act (CCPA) in the United States. Moreover, this model encourages collaboration between local and central teams, fostering a culture of shared responsibility for security. It empowers local teams to make informed decisions based on their unique threat landscapes, which can enhance the organization’s overall resilience against cyber threats. However, it is essential to manage this hybrid approach carefully. If not implemented correctly, it could lead to confusion among local teams due to conflicting directives from the central governance body, potentially resulting in compliance gaps. Therefore, clear communication and well-defined roles are critical to ensure that local teams understand their responsibilities within the broader governance framework. In summary, a hybrid governance model effectively balances localized risk management with centralized oversight, promoting compliance and security across diverse regulatory environments while mitigating the risks associated with miscommunication and misalignment.

In contrast, relying solely on predefined rules can lead to rigidity in the system, as these rules may not account for novel attack vectors or sophisticated tactics employed by adversaries. Furthermore, implementing machine learning models without regular updates can result in a degradation of performance over time, as the models may become outdated and less effective against new threats. Using a static dataset for training is also problematic, as it limits the model’s ability to generalize and adapt to new patterns of behavior that may emerge in the threat landscape. Therefore, the best practice is to establish a feedback loop where the automation system continuously learns from new incidents, allowing it to refine its detection capabilities and improve overall security posture. This approach aligns with industry best practices for security automation, emphasizing the importance of adaptability and continuous improvement in threat detection and response mechanisms.

EBS encryption uses AES-256 encryption, which is a strong encryption standard, and it is performed on the storage level. This means that data is automatically encrypted when written to the disk and decrypted when read, without requiring any changes to the applications. This approach minimizes the performance impact, as the encryption and decryption processes are handled by the AWS infrastructure, which is optimized for such operations. On the other hand, managing their own encryption keys introduces additional complexity and potential security risks. It requires the company to implement their own key management practices, which may not be as robust as AWS KMS. Furthermore, a custom encryption solution could lead to performance bottlenecks if not designed properly, as the application would need to handle encryption and decryption operations. Disabling AWS KMS while using EBS encryption is not advisable, as it would negate the benefits of using a managed key service and could lead to compliance issues. Lastly, relying on application-level encryption while using unencrypted EBS volumes exposes the data to risks during transit and at rest, as the underlying storage would not be encrypted. In summary, leveraging AWS KMS for key management in conjunction with EBS encryption provides a secure, compliant, and performance-optimized solution for the company’s sensitive customer data. This approach aligns with AWS best practices and ensures that the company can focus on its core business without compromising on security.

On the other hand, implementing advanced technical controls without addressing employee training (option b) neglects the human element of security. Employees are often the first line of defense, and their awareness and understanding of security protocols are vital. A policy that focuses solely on compliance with external regulations (option c) may overlook the importance of internal accountability and ethical behavior, which are critical for a robust security posture. Lastly, limiting communication about security policies to only the IT department (option d) creates silos and can lead to a lack of awareness among non-technical staff, who also play a significant role in maintaining security. In summary, a comprehensive security policy must integrate technical measures with a strong emphasis on professional conduct, ensuring that all employees understand their responsibilities and the importance of reporting any security concerns. This holistic approach not only enhances security but also cultivates an ethical workplace culture, which is essential for long-term success in any organization.

Additionally, utilizing AWS Identity and Access Management (IAM) roles is essential for controlling access to AWS resources. By assigning specific permissions to IAM roles, the company can enforce the principle of least privilege, ensuring that only authorized entities can access sensitive resources. This minimizes the risk of unauthorized access and potential data breaches. On the other hand, relying solely on AWS App Runner’s built-in security features without additional configurations is inadequate. While AWS provides robust security measures, it is the responsibility of the organization to implement additional layers of security tailored to their specific application needs. Using a single IAM user with broad permissions is a poor practice as it increases the attack surface and makes it difficult to track actions taken by different users. This approach violates the principle of least privilege and can lead to significant security risks. Finally, disabling logging to reduce overhead is counterproductive. Logging is vital for monitoring application behavior, detecting anomalies, and conducting forensic analysis in the event of a security incident. Effective logging practices are essential for maintaining compliance with data protection regulations and ensuring accountability. In summary, the company should prioritize implementing HTTPS for secure communications and using IAM roles to manage access effectively, as these measures significantly enhance the security posture of their AWS App Runner deployment while ensuring compliance with relevant regulations.

In contrast, a purely centralized governance model may impose uniform policies that do not account for local nuances, potentially leading to non-compliance or ineffective security practices. A decentralized model, while promoting autonomy, risks fragmentation and inconsistency in security measures, which can create vulnerabilities. Lastly, a compliance-driven governance model, while important for meeting regulatory requirements, may neglect the broader context of risk management, leading to a checkbox mentality rather than fostering a proactive security culture. The hybrid approach encourages stakeholder engagement by involving various departments in the governance process, promoting a culture of security awareness. This model aligns with frameworks such as the NIST Cybersecurity Framework and ISO/IEC 27001, which advocate for a risk-based approach to security governance. By adopting a hybrid model, the organization can effectively navigate the complexities of global security challenges while ensuring that all stakeholders are invested in the security posture of the organization.

Increasing the threshold for flagging transactions may seem like a straightforward solution, but it risks missing genuine fraud cases, as it could lead to a higher tolerance for anomalies. Implementing a manual review process for all flagged transactions can be resource-intensive and may not scale well, especially in high-volume environments. Disabling the machine learning model entirely is not a viable option, as it would leave the organization vulnerable to undetected fraud during the downtime. Therefore, the most effective strategy is to enhance the model’s training data with relevant contextual information, which will improve its predictive capabilities and reduce the likelihood of false positives while maintaining robust fraud detection. This approach aligns with best practices in machine learning and security analytics, emphasizing the importance of continuous improvement and adaptation of detection systems to evolving patterns of behavior.

Moreover, CMKs allow for detailed auditing capabilities through AWS CloudTrail, which logs all key usage, providing visibility into who accessed the keys and when. This level of oversight is vital for compliance audits and for demonstrating adherence to regulatory requirements. In contrast, while AWS Managed Keys simplify key management by automatically handling key rotation and lifecycle management, they do not offer the same level of control over access permissions. This can be a significant drawback for organizations that require stringent access controls and detailed auditing capabilities. Additionally, while cost considerations are important, the primary focus should be on security and compliance needs rather than just cost-effectiveness. AWS Managed Keys may reduce operational overhead, but they may not meet the specific compliance requirements that necessitate the use of Customer Managed Keys. Therefore, in scenarios where compliance and detailed access control are paramount, Customer Managed Keys are the superior choice.

To understand the minimum duration of sustained high CPU utilization that would trigger the alarm, we need to analyze the configuration. The evaluation period is set to 5 minutes, meaning that the alarm will evaluate the last 5 data points (which correspond to the last 5 minutes). The requirement of 3 out of 5 data points means that at least 3 of these 5 data points must be above the threshold of 75% CPU utilization for the alarm to trigger. To achieve this, the CPU utilization must be above 75% for at least 3 consecutive minutes within the 5-minute evaluation period. This means that if the CPU utilization is above 75% for 3 minutes, the alarm will trigger at the end of the 5-minute evaluation period, assuming the other 2 data points can be below the threshold. Therefore, the minimum duration of sustained high CPU utilization that would trigger the alarm is 3 minutes, but since the evaluation period is 5 minutes, the alarm will only trigger if the CPU utilization remains high for at least 3 out of those 5 minutes. Thus, the correct answer is that the minimum duration of sustained high CPU utilization that would trigger the alarm is effectively 15 minutes, as the alarm will only evaluate the last 5 minutes and requires a sustained breach over that time frame. This configuration helps to avoid false positives from transient spikes, ensuring that the company is alerted only when there is a genuine and sustained increase in CPU utilization.