WGU Managing-Cloud-Security - WGU Managing Cloud Security (JY02, GZO1)

The Store phase of the cloud data lifecycle is responsible for maintaining data in cloud storage systems and is where file, block, and object storage architectures are implemented. Managing Cloud documentation explains that once data is created and prepared, it must be stored using appropriate storage technologies that support availability, durability, scalability, and performance requirements.

File storage is commonly used for shared access and hierarchical file systems, block storage supports high-performance workloads such as databases and virtual machines, and object storage is optimized for scalability and unstructured data. All these storage models fall under the Store phase because they represent how data is retained and managed at rest within the cloud environment.

The Archive phase focuses on long-term retention and cost optimization, often using cold or infrequent access storage. The Create phase is concerned with generating data, and the Share phase involves distributing data to other users or systems. None of these phases define the architectural storage models used to hold data. Therefore, the Store phase is the correct answer, as it directly implements the underlying cloud storage architectures required to securely and efficiently manage data.

A dry run disaster recovery plan test requires broad organizational participation in a simulated disaster scenario without executing all production-impacting tasks. Managing Cloud principles explain that dry run testing validates coordination, communication, and procedural readiness while avoiding the risks of full operational disruption.

In a dry run, teams follow documented recovery steps conceptually or in limited execution, verifying that dependencies, responsibilities, and sequencing are correct. This approach provides higher fidelity than tabletop exercises, which are discussion-based, while avoiding the operational risks of full or parallel tests.

Parallel tests involve running recovery systems alongside production, and full tests execute all recovery actions, often causing service disruption. Therefore, a dry run offers a balanced method to test preparedness across the organization without full execution.

Failover should occur prior to the crisis event when an impending disaster is identified. Managing Cloud principles explain that proactive failover allows organizations to maintain service continuity by transitioning operations to alternate systems before disruption occurs.

Early failover reduces downtime, minimizes data loss, and avoids the risks associated with reactive responses during an active crisis. Cloud environments support automated or planned failover mechanisms that can be triggered by warning systems, ensuring seamless continuity.

Failover during or after the crisis increases the likelihood of service interruption. Therefore, initiating failover before the event is the correct approach.

Cloud providers typically manage multi-tenant infrastructure, where physical hardware is shared among customers. Therefore, drives are not destroyed for each customer unless explicitly required in the contract. If the customer’s agreement specifies dedicated hardware disposal, then the provider must comply by physically destroying the drives.

Cryptographic erasure and degaussing are valid sanitization methods, but they may not meet the specific contractual requirement of physical destruction. Insurance clauses are unrelated to disposal.

This question underscores the importance of negotiating contractual terms in cloud agreements. Customers handling highly sensitive or regulated data may require physical destruction, while others may accept logical erasure. Clear agreements ensure both compliance and alignment of security responsibilities.

The software agent management plane must support auto-scaling and elasticity because traditional security tools are not designed for the speed and scale of cloud environments. Managing Cloud guidance explains that cloud workloads can be created, scaled, and terminated rapidly, often within minutes or seconds.

If security management systems cannot scale at the same pace, workloads may operate without protection or monitoring. Elastic security management ensures that agents are deployed, configured, and decommissioned automatically as workloads scale up or down.

The other options do not directly explain the need for elasticity. Network isolation, reduced services, and firewall port usage are not the primary drivers. Therefore, the need to match cloud velocity makes option C correct.

The requirement for a username, password, and security token describes authentication—the process of verifying the identity of a user. By requiring multiple factors (something you know + something you have), the organization is implementing multifactor authentication (MFA).

Authorization defines what resources a user can access after authentication. WAFs protect web applications, and ACLs specify rules for allowed or denied traffic, but neither validate user identity.

Authentication ensures that only legitimate users gain access to cloud resources. In hybrid environments, MFA is a strong safeguard against credential theft and phishing attacks, providing assurance that identities are genuine before authorization decisions are made.

Runtime Application Self-Protection (RASP) prevents environments from being over-controlled with performance-degrading security measures. Managing Cloud guidance explains that RASP operates from within the application, monitoring behavior and responding to threats in real time.

Because RASP provides contextual awareness of application logic, it reduces the need for excessive external security controls such as heavy network filtering or constant scanning. This minimizes performance impact while maintaining effective protection against attacks like injection, unauthorized access, and misuse of application functions.

QoS manages traffic prioritization, DDoS describes an attack type, and IDS detects threats but does not prevent over-control. Therefore, RASP is the correct technology.

Data masking is a privacy-preserving technique that replaces sensitive fields with obfuscated or partial values while retaining usability. For example, displaying only the last four digits of a Social Security Number or credit card number. This allows a representative to verify identity without accessing the full data set.

Hashing and encryption protect data at rest or in transit, but they do not allow selective partial display. Tokenization substitutes sensitive data with unique tokens but is typically used for storage and processing rather than interactive verification. Masking, on the other hand, is specifically designed for scenarios where a user must work with limited but recognizable data.

By using masking, organizations enforce the principle of least privilege, reduce exposure of sensitive information, and align with privacy standards such as PCI DSS and GDPR.

A cloud service partner plays a complementary role by offering products or services that enhance or interact with the primary cloud provider’s offerings. Examples include managed service providers, value-added resellers, or software vendors that integrate their solutions with the core infrastructure or platform of a cloud service provider.

The customer is the end user of cloud services, regulators ensure compliance with laws, and developers create applications but do not represent an independent ecosystem role. Partners, on the other hand, extend the value of the primary offering by providing additional tools, support, or integrations that enhance customer experience.

This ecosystem role is recognized by major cloud frameworks, such as the Cloud Security Alliance, which notes the importance of partners in ensuring interoperability, extending services, and supporting shared responsibility. For customers, this means greater flexibility and choice in tailoring cloud solutions to business needs.

Examining configuration data is the appropriate methodology to determine whether other similar instances were potentially exposed during the same attack. Managing Cloud principles explain that configuration analysis identifies shared settings, permissions, or misconfigurations across cloud resources.

By reviewing configuration data, security teams can identify patterns such as overly permissive access controls, shared credentials, or insecure templates that may affect multiple instances. This helps assess blast radius and identify additional affected systems.

Application logs and network flows help investigate specific events, while generalized log review focuses on activity. Configuration analysis uniquely identifies systemic exposure. Therefore, examining configuration data is the correct answer.