Managing-Cloud-Security Exam Dumps - WGU Courses and Certificates Questions and Answers

Vendor lock-in risk arises when organizations outsource significant investments in data formats, procedures, or processes that are tightly coupled to a specific cloud provider. Managing Cloud principles explain that proprietary technologies, APIs, and workflows can make it difficult or costly to migrate to another provider.

This dependency limits flexibility and bargaining power and can increase long-term costs or operational risk if the provider changes pricing, services, or availability. Lock-in risk is a key consideration during cloud strategy planning.

Compliance risk involves regulatory obligations, overutilization concerns excessive resource usage, and exit risk relates to termination processes rather than dependency. Therefore, lock-in risk is the correct answer.

The correct time for data deletion is after the specified retention period defined by contractual agreements, regulatory frameworks, or internal policies. Retention policies ensure that data is kept for as long as necessary for business, legal, or compliance reasons but not longer than required.

Oversubscription, inactivity, or review cycles are not valid triggers because they may conflict with compliance mandates such as GDPR, HIPAA, or PCI DSS. Deleting data prematurely could result in legal penalties or business risks, while keeping it longer than necessary could increase exposure.

By deleting data only after the retention period, providers demonstrate adherence to data governance principles and protect customer rights while minimizing storage costs and liability.

The cloud data life cycle defines distinct stages that data goes through from its origin until its disposal. The Create phase is the very first stage, and this is where data is generated or captured by systems, applications, or users. At this point, data does not yet have context for storage or use, so it must be appropriately categorized and classified. Activities like labeling, marking, tagging, and assigning metadata are critical because they establish the foundation for enforcing controls throughout the rest of the life cycle.

Classification ensures that data is aligned with sensitivity levels, regulatory requirements, and business value. For example, financial records may be labeled “confidential” while general marketing content may be marked “public.” These distinctions guide how encryption, access controls, and monitoring will be applied in subsequent phases such as storage, sharing, or use.

According to industry frameworks, starting security at the Create phase ensures that controls “follow the data” across environments. Without proper classification at creation, organizations risk mismanaging sensitive data downstream.

The General Data Protection Regulation (GDPR) is the legal framework concerned with the privacy of data belonging to citizens of the European Union and the European Economic Area (EU/EEA). Managing Cloud principles explain that GDPR establishes comprehensive rules governing the collection, processing, storage, and transfer of personal data.

GDPR applies to organizations both within and outside the EU/EEA if they process personal data of EU residents. It enforces strict requirements related to data protection, consent, breach notification, and individual rights. Cloud service providers and consumers must ensure compliance when handling EU personal data.

The other options apply to different jurisdictions or data types. HIPAA governs healthcare data in the United States, COPPA protects children’s online privacy in the U.S., and APPI applies to Japan. Therefore, GDPR is the correct framework.

Architecting for failure is a fundamental business continuity and disaster recovery consideration in cloud application architecture. Managing Cloud principles emphasize that cloud systems must be designed with the assumption that components will fail.

Architecting for failure involves implementing redundancy, fault tolerance, automated recovery, and failover mechanisms. Applications should be resilient to infrastructure outages and capable of continuing operation despite component failures. This approach reduces downtime and ensures service availability during incidents.

Health status pages provide visibility, compliance addresses regulatory needs, and message queues support communication but do not fully address BC/DR requirements. Therefore, architecting for failure is the correct answer.

In Agile development, user stories are the standard way to capture requirements for new features or improvements. A user story describes the functionality from the perspective of the end user, ensuring that development aligns with business needs.

“Cases” might refer to test cases, which validate requirements, but they are not used to describe them. Cookies are technical elements for web sessions, and notes are informal documentation.

User stories typically follow a format such as: “As a [role], I want [goal] so that [benefit].” This provides clarity, fosters communication between developers and stakeholders, and ensures that acceptance criteria can be defined and tested. Using stories as a requirement tool aligns with iterative, customer-focused release cycles.

Object-based storage architecture allows digital rights management (DRM) solutions to associate metadata directly with stored materials. Managing Cloud documentation highlights that object storage is designed to store data as discrete objects, each containing the data itself, a unique identifier, and customizable metadata.

This metadata capability is essential for DRM solutions, as it enables the attachment of usage rights, access restrictions, expiration rules, and ownership information to digital content. Because metadata is stored alongside the object, policies can be enforced consistently regardless of where or how the data is accessed within the cloud environment.

Other storage architectures lack this flexibility. Volume and file storage focus on block-level or hierarchical file systems with limited metadata support, while relational databases require structured schemas not optimized for DRM metadata association. Object-based storage’s native metadata functionality makes it the preferred architecture for enforcing content protection and rights management in the cloud.

A compensating control should be implemented to address the loss of physical control when moving data to the cloud. Managing Cloud guidance explains that compensating controls are alternative safeguards used when direct controls are not feasible.

Since customers cannot physically secure cloud data centers, compensating controls such as strong encryption, key management, access controls, and monitoring are used to mitigate the risk. These controls provide equivalent or greater protection despite the lack of physical access.

The other options are not recognized control types in cloud security governance. Therefore, compensating control is the correct answer.

Platform as a Service (PaaS) provides application development services in cloud environments. Managing Cloud documentation explains that PaaS delivers development frameworks, programming languages, libraries, databases, and testing tools required to build and deploy applications.

This model eliminates the need to manage infrastructure and operating systems, allowing developers to rapidly create, test, and deploy applications. PaaS also supports scalability and integration with other cloud services.

SaaS delivers completed applications, IaaS provides raw infrastructure, and SECaaS focuses on security services. Therefore, PaaS is the correct model for application development services.

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.