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AT-510 Test Centres | AT-510 Exam Tutorial

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AT-510 Test Centres | AT-510 Exam Tutorial

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AI CERTs AI+ NetworkExamination Sample Questions (Q40-Q45):NEW QUESTION # 40
(What is the purpose of VLANs in a network?)
  • A. To logically divide a physical network into isolated segments.
  • B. To enhance physical connectivity between devices.
  • C. To replace the need for network switches and routers.
  • D. To provide internet access to all connected devices.
Answer: A
Explanation:
Virtual Local Area Networks (VLANs) are used to logically divide a single physical network into multiple isolated broadcast domains. According to AI+ Network foundational documentation, VLANs allow network administrators to group devices based on function, department, or security requirements rather than physical location.
By segmenting a network logically, VLANs improve security by limiting broadcast traffic and reducing the scope of potential attacks. Devices in different VLANs cannot communicate directly without routing, which allows administrators to enforce access control policies. VLANs also enhance performance by reducing unnecessary broadcast traffic across the entire network.
VLANs do not enhance physical connectivity, provide internet access by themselves, or replace networking hardware. Instead, they work in conjunction with switches and routers to create scalable, secure, and efficient network architectures. AI+ Network materials consistently identify VLANs as a core technique for network segmentation and traffic management.

NEW QUESTION # 41
(What makes behavioral analysis effective against unknown cyber threats?)
  • A. It detects threats by monitoring deviations from normal activity.
  • B. It focuses on analyzing static features like file metadata.
  • C. It relies on predefined signatures to identify specific malware.
  • D. It uses manual investigation to identify suspicious activities.
Answer: A
Explanation:
Behavioral analysis is effective against unknown cyber threats because it detects anomalies by monitoring deviations from established normal behavior. AI+ Network security documentation explains that instead of relying on known attack signatures, behavioral analysis builds baselines of normal user, device, and network activity.
When behavior deviates significantly-such as unusual login patterns, abnormal data transfers, or unexpected process execution-the system flags the activity as potentially malicious. This allows detection of zero-day attacks and advanced persistent threats that signature-based tools cannot identify.
Static metadata analysis and manual investigation are slower and less adaptive. AI+ Network frameworks emphasize behavioral analysis as a critical AI-driven capability for modern threat detection, enabling proactive defense against evolving cyber risks.

NEW QUESTION # 42
(Scenario: A company needs a network design that maintains high performance while ensuring reliability.
Question: Which combination of strategies would best achieve this?)
  • A. Cloud infrastructure with fault tolerance.
  • B. Load balancing with redundant connections.
  • C. Star topology with failover systems.
  • D. Centralized routing with hybrid topology.
Answer: B
Explanation:
Load balancing combined with redundant connections is the most effective strategy for achieving both high performance and reliability in modern network designs. According to AI+ Networkfoundational principles, load balancingdistributes traffic evenly across multiple network paths, links, or devices, preventing congestion and ensuring optimal resource utilization. This directly improves performance by avoiding single points of saturation.
Redundant connectionscomplement load balancing by providing alternate paths in case of link, device, or circuit failure. If one connection becomes unavailable, traffic is automatically rerouted through another active path, maintaining service continuity without noticeable downtime. AI+ Network documentation emphasizes redundancy as a critical design principle for high-availability architectures, particularly in enterprise and mission-critical environments.
While star topology with failover improves reliability, it can still suffer from central bottlenecks. Centralized routing introduces single points of failure, and cloud fault tolerance alone does not address on-premise or hybrid network performance challenges. In contrast, load balancing with redundancy directly addresses both throughput optimizationandfault toleranceat the network layer.
Therefore, this combination best satisfies the requirement of maintaining high performance while ensuring consistent and reliable network operations.

NEW QUESTION # 43
(Which platform is best for handling traffic surges and maintaining application availability across multi-cloud environments?)
  • A. Kubernetes
  • B. AI Engine
  • C. OpenStack
  • D. Ansible
Answer: A
Explanation:
Kubernetes is the most suitable platform for handling traffic surges and maintaining high application availability across multi-cloud environments. According to AI+ Network architecture principles, Kubernetes is designed as a cloud-native orchestration platform that automates container deployment, scaling, and management across distributed infrastructures. One of its core strengths ishorizontal auto-scaling, which dynamically increases or decreases application pods based on real-time metrics such as CPU utilization, memory usage, or custom telemetry. This makes Kubernetes highly effective during sudden traffic spikes.
In multi-cloud environments, Kubernetes provides a consistent control plane abstraction across different cloud providers, enabling workload portability and resilience. AI+ Network documentation emphasizes Kubernetes' support forself-healing, where failed containers are automatically restarted or rescheduled without manual intervention, ensuring continuous application availability. Additionally, Kubernetes integrates seamlessly with cloud-native load balancers and service meshes, allowing intelligent traffic distribution and failover across regions and providers.
Compared to OpenStack, which focuses on infrastructure provisioning, or Ansible, which is primarily a configuration automation tool, Kubernetes directly manages application runtime behavior at scale. AI Engines, while valuable for analytics, do not provide orchestration capabilities. Therefore, Kubernetes stands out as the optimal platform for maintaining performance, scalability, and availability in modern, AI-driven, multi-cloud network architectures.

NEW QUESTION # 44
(Which feature of Zero Trust Architecture best addresses insider threats by enforcing dynamic and continuous access controls?)
  • A. Static IP-based rules
  • B. Role-Based Access Control (RBAC)
  • C. Firewalls to block unverified internal traffic
  • D. Network perimeter segmentation
Answer: B
Explanation:
Role-Based Access Control (RBAC) is a key Zero Trust Architecture feature that effectively addresses insider threats through dynamic and continuous access enforcement. AI+ Network security documentation explains that RBAC limits user access based on defined roles and responsibilities, ensuring users can only access resources necessary for their job functions.
In a Zero Trust model, RBAC is continuously evaluated alongside contextual factors such as device posture, user behavior, and session risk. This reduces the potential damage from compromised insider accounts and prevents privilege abuse.
Static IP rules and perimeter segmentation rely on outdated trust assumptions, while firewalls alone cannot address insider misuse. AI+ Network materials identify RBAC as a foundational mechanism for enforcing least-privilege access within Zero Trust frameworks.

NEW QUESTION # 45
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