Google Professional Cloud Network Engineer Exam Dumps and Practice Test Questions Set 7 Q91-105

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Question 91

A logistics company wants to establish a private connection between its on-premises warehouse network and Google Cloud. They require predictable bandwidth, low latency, and support for dynamic routing with automatic failover. Which solution is most suitable?

A) Cloud VPN Classic
B) Cloud Interconnect Dedicated with Cloud Router
C) Cloud Interconnect Partner without Cloud Router
D) Manual static routes with VPN

Correct Answer: B) Cloud Interconnect Dedicated with Cloud

Explanation

Logistics companies rely on timely data transfers between on-premises warehouses and cloud systems for inventory management, order processing, and real-time tracking. A network solution must provide high performance, predictable bandwidth, low latency, automatic failover, and dynamic routing to ensure smooth operations across geographically distributed warehouses. Evaluating the options against these requirements clarifies the most suitable approach.

The first approach, Cloud VPN Classic, establishes encrypted tunnels over the public internet. VPNs provide security,, but cannot guarantee consistent bandwidth or low latency due to internet traffic variability. While multiple tunnels can be configured for redundancy, failover is manual or requires additional configuration. Routing is largely static, meaning network updates or new routes require manual intervention. For a logistics operation handling large data volumes, Cloud VPN Classic cannot meet performance or operational efficiency requirements.

The third approach, Cloud Interconnect Partner without Cloud Router, provides a private, high-bandwidth connection through a partner provider. While predictable performance and low latency are achievable, the absence of a Cloud Router means all routes must be manually managed. Failover is not automatic; administrators must configure redundant connections and update routes manually during outages or changes. Scaling to additional warehouses or modifying network paths adds operational complexity, making this approach less ideal for dynamic logistics requirements.

The fourth approach, manual static routes with VPN, requires configuring each network path individually. Each route must be updated manually for changes in topology, and failover is not automatic. Scaling to multiple warehouses increases configuration errors and operational overhead. This method does not support dynamic routing, which is essential for responsive logistics networks where routes may need to adapt to demand or failures.

The second approach, Cloud Interconnect Dedicated with Cloud Router, provides predictable high bandwidth and low latency for on-premises connectivity. Cloud Router enables dynamic route propagation, automatically adjusting to network changes without manual intervention. Redundant connections allow automatic failover, ensuring continuous operations during link or device failure. Adding new warehouses or subnets is straightforward because routes propagate dynamically. Centralized management and monitoring simplify operational oversight, reduce errors, and enhance reliability. This solution fulfills all requirements: predictable bandwidth, low latency, dynamic routing, automatic failover, and simplified operational management, making it the optimal choice for logistics operations requiring private connectivity to Google Cloud.

Question 92

A SaaS provider wants to expose a single global public endpoint for its application with SSL termination, health-based routing, and automatic scaling across multiple regions. Users should be directed to the nearest available backend to reduce latency. Which Google Cloud load balancer is most appropriate?

A) Regional External HTTP(S) Load Balancer
B) Global External HTTP(S) Load Balancer
C) TCP Proxy Load Balancer
D) Internal HTTP(S) Load Balancer

Correct Answer: B) Global External HTTP(S) Load Balancer

Explanation

SaaS applications require global availability, low latency, and high reliability. Users across multiple regions expect fast response times and uninterrupted service. Requirements include a single public IP for simplicity, SSL termination at the edge to offload encryption from backend servers, health-based routing to direct traffic to the nearest available backend, and autoscaling to accommodate variable workloads. Evaluating Google Cloud load balancing solutions clarifies the optimal choice.

The first approach, regional external HTTP(S) load balancing, distributes traffic only within a single region. While SSL termination and autoscaling are supported within that region, users connecting from other locations may experience high latency due to a lack of global routing. Multi-region failover is not automatic, making this solution insufficient for SaaS providers serving a global user base.

The third approach, TCP Proxy Load Balancer, provides global traffic routing at the TCP layer. It supports proximity-based routing to healthy backends but lacks application-layer features such as SSL termination at the edge and content-based routing. SaaS applications typically operate over HTTP(S), and edge SSL termination is essential to reduce backend load and improve performance. TCP-level routing alone cannot provide application-layer optimization, making it suboptimal.

The fourth approach, internal HTTP(S) load balancing, is designed for private internal workloads. It does not provide a public IP and cannot route external traffic. Autoscaling and SSL termination are limited to internal users, making it unsuitable for SaaS applications intended for global public access.

The second approach, global external HTTP(S) load balancing, provides a single public IP address accessible worldwide. Traffic is automatically routed to the nearest healthy backend to minimize latency. SSL termination occurs at the edge, reducing backend processing requirements. Autoscaling adjusts capacity dynamically across regions, ensuring seamless handling of spikes in user activity. Multi-region failover ensures high availability; if a regional backend is unavailable, traffic automatically reroutes to the next closest healthy backend. Centralized monitoring and logging simplify operational management and troubleshooting. This approach fully meets all SaaS requirements: global reach, low latency, edge SSL termination, health-based routing, and dynamic autoscaling.

Given the need for global access, low-latency routing, edge SSL termination, and autoscaling, global external HTTP(S) load balancing is the optimal solution for SaaS providers serving worldwide users.

Question 93

A healthcare organization requires private access for internal applications to multiple Google Cloud managed services, with centralized access control, private IP connectivity, and the ability to connect to multiple service producers efficiently. Which solution meets these requirements?

A) VPC Peering with each service
B) Private Service Connect endpoints
C) Assign external IPs and use firewall rules
D) Configure individual VPN tunnels for each service

Correct Answer: B) Private Service Connect endpoints

Explanation

Healthcare organizations must comply with stringent privacy regulations and protect sensitive patient data. Providing private connectivity to managed Google Cloud services ensures that traffic remains within private networks and is not exposed to the public internet. Requirements include private IP connectivity, centralized access management for consistent policy enforcement, and support for multiple service producers to simplify operational management. Evaluating each connectivity option highlights the most suitable solution.

The first approach, VPC Peering with each service, provides private connectivity between networks. While feasible, it does not scale efficiently for multiple managed services, as each service requires a separate peering connection. Centralized access control is limited because policies must be applied individually for each peering, and overlapping IP ranges are unsupported. As the number of services increases, operational complexity grows significantly, making it impractical for large healthcare organizations.

The third approach, assigning external IPs with firewall rules, exposes APIs to the public internet while attempting to restrict access. While firewall rules can limit connections to authorized users, services remain publicly reachable, increasing the risk of exposure. Centralized access management is difficult to implement, and multiple service producers require separate firewall configurations, increasing administrative overhead. This approach does not fully comply with healthcare privacy requirements.

The fourth approach, configuring individual VPN tunnels for each service, provides encrypted connectivity but introduces high operational overhead. Each VPN tunnel must be separately configured, monitored, and maintained. Scaling to multiple services or teams is cumbersome. Centralized policy management is difficult because each VPN operates independently. This approach increases complexity without providing the scalability or operational efficiency required.

The second approach, Private Service Connect endpoints, enables private IP access to multiple managed services without exposing traffic to the public internet. Multiple service producers can be accessed through a single framework, reducing operational overhead. Centralized access management ensures consistent policy enforcement across teams. Multi-region support allows seamless scaling without redesigning network architecture. Integrated logging and monitoring simplify auditing and operational oversight. Private Service Connect provides secure, scalable, and operationally efficient access to managed services, meeting privacy, compliance, and operational requirements for healthcare organizations.

Given the need for private IP connectivity, centralized access control, and support for multiple service producers, Private Service Connect is the optimal solution for healthcare organizations accessing multiple Google Cloud managed services.

Question 94

A multinational manufacturing company wants to securely connect multiple on-premises production sites to Google Cloud. They require high bandwidth, predictable latency, dynamic route propagation, automatic failover, and centralized network management. Which solution should they choose?

A) Cloud VPN Classic
B) Cloud Interconnect Dedicated without Cloud Router
C) Cloud Interconnect Partner with Cloud Router
D) Manually configured static routes

Correct Answer: C) Cloud Interconnect Partner with Cloud Router

Explanation

Manufacturing companies operate geographically distributed production sites that require fast and reliable communication with cloud-based ERP systems, analytics platforms, and supply chain management tools. Their networking solution must provide high bandwidth for large data transfers, predictable latency for real-time process monitoring, dynamic route propagation to simplify network management, automatic failover to ensure business continuity, and centralized management to reduce operational complexity. Assessing available Google Cloud solutions demonstrates why Cloud Interconnect Partner with Cloud Router is optimal.

The first approach, Cloud VPN Classic, provides encrypted tunnels over the public internet. While VPNs are secure, they cannot guarantee predictable bandwidth or low latency due to variability in public network performance. Routing is largely static, requiring manual configuration for each site, and failover is either manual or requires complex configuration with multiple tunnels. Scaling VPNs across multiple production sites increases operational overhead and is prone to errors. While secure, Cloud VPN Classic does not meet the throughput, latency, and operational efficiency requirements of a manufacturing environment.

The second approach, Cloud Interconnect Dedicated without Cloud Router, provides private, high-bandwidth connectivity to Google Cloud. Dedicated interconnects ensure low latency and predictable performance. However, without a Cloud Router, all network routes must be configured manually. Failover is not automatic, requiring administrators to configure redundant connections and monitor them continuously. Any addition of new sites or subnet changes involves significant manual updates. While throughput and latency are addressed, operational efficiency and dynamic route management remain limited, which is a critical gap for a multinational manufacturing network.

The fourth approach, manually configured static routes, is not scalable. Each site requires manual route updates, and any change in network topology necessitates updates across all sites. Failover is not automated, and traffic cannot dynamically adjust to optimize performance or respond to outages. Operational overhead is extremely high, and the approach is prone to errors. For a network spanning multiple global production sites, this approach is inefficient and risky.

The third approach, Cloud Interconnect Partner with Cloud Router, provides high-bandwidth, low-latency connectivity with dynamic routing and automatic failover. Partner interconnects offer reliable and predictable network performance. Cloud Router dynamically propagates routes, eliminating the need for manual configuration when new sites or subnets are added. Redundant connections automatically provide failover in case of link or device failure. Centralized monitoring, logging, and management simplify operational oversight and reduce configuration errors. This solution satisfies all essential requirements: predictable high bandwidth, low latency, dynamic route propagation, automated failover, and centralized management. It enables the manufacturing company to securely connect multiple global sites to Google Cloud while minimizing operational complexity.

Considering all factors—including bandwidth, latency, scalability, failover automation, and management efficiency—Cloud Interconnect Partner with Cloud Router is the optimal solution for multinational manufacturing connectivity.

Question 95

A global SaaS company needs to expose a single public endpoint for its web application. The solution must provide SSL termination at the edge, health-based routing to the closest healthy backend, and autoscaling across multiple regions. Which load balancer should be used?

A) Regional External HTTP(S) Load Balancer
B) Global External HTTP(S) Load Balancer
C) TCP Proxy Load Balancer
D) Internal HTTP(S) Load Balancer

Correct Answer: B) Global External HTTP(S) Load Balancer

Explanation

SaaS applications demand high availability, low latency, and global reach. Key requirements include a single global IP for simplicity, SSL termination at the edge to offload encryption from backends, health-based routing to direct traffic to the nearest available backend, and autoscaling to handle unpredictable traffic surges. Evaluating Google Cloud load balancers against these requirements demonstrates the most suitable solution.

The first approach, regional external HTTP(S) load balancing, provides SSL termination and autoscaling within a specific region. However, it cannot automatically route traffic to the nearest backend outside its region, which can increase latency for global users. Multi-region failover is not automatic, limiting resilience and performance. While suitable for local traffic, it does not meet global SaaS application needs.

The third approach, TCP Proxy Load Balancer, supports global routing at the TCP layer but lacks application-layer features. It cannot perform SSL termination at the edge or support content-based routing. SaaS applications typically use HTTP(S), and edge SSL termination is critical to reduce backend load, optimize performance, and simplify certificate management. TCP-level routing alone is insufficient for SaaS requirements.

The fourth approach, internal HTTP(S) load balancing, is designed for private traffic within a VPC. It does not provide a public IP, cannot route external traffic, and limits SSL termination and autoscaling to internal workloads. This solution is unsuitable for public SaaS applications.

The second approach, global external HTTP(S) load balancing, provides a single public IP globally. Traffic is automatically routed to the closest healthy backend to minimize latency. SSL termination occurs at the edge, reducing backend load. Autoscaling dynamically adjusts backend capacity across regions to handle variable traffic, ensuring continuous availability. Multi-region failover guarantees high availability; if a regional backend fails, traffic is rerouted to the next closest healthy backend automatically. Centralized monitoring and logging provide operational visibility, enabling performance optimization and troubleshooting. This approach fully meets SaaS requirements: global low-latency access, edge SSL termination, health-based routing, and autoscaling.

Considering global reach, low latency, edge SSL termination, and dynamic scaling, global external HTTP(S) load balancing is the optimal choice for SaaS applications serving worldwide users.

Question 96

A healthcare organization wants internal applications to access multiple Google Cloud managed services privately, without using public IPs. The organization requires centralized access control, support for multiple service producers, and seamless scalability. Which solution is most appropriate?

A) VPC Peering with each service
B) Private Service Connect endpoints
C) Assign external IPs with firewall restrictions
D) Individual VPN tunnels for each service

Correct Answer: B) Private Service Connect endpoints

Explanation

Healthcare organizations must comply with strict privacy regulations and protect sensitive patient data. Internal applications need private connectivity to managed Google Cloud services to prevent data exposure over public networks. Requirements include private IP connectivity, centralized access management for consistent policies, support for multiple service producers, and seamless scalability. Evaluating each solution highlights the most suitable approach.

The first approach, VPC Peering with each service, provides private connectivity between networks. While feasible for a few services, it does not scale efficiently for multiple managed services, as each requires a separate peering connection. Overlapping IP ranges are not supported, and centralized access control is limited because policies must be applied individually. Operational complexity grows rapidly as the number of services increases, making this approach impractical for large healthcare organizations.

The third approach, assigning external IPs with firewall restrictions, leaves APIs exposed to the public internet, even if restricted. Firewall rules can limit access to authorized users, but centralized access management is difficult, and multiple service producers require separate firewall configurations. This method does not fully comply with privacy and regulatory requirements.

The fourth approach, configuring individual VPN tunnels for each service, ensures encrypted connectivity but introduces high operational overhead. Each tunnel requires configuration, monitoring, and maintenance. Scaling to multiple services or teams is cumbersome, and centralized access control is difficult, as each VPN operates independently. This approach increases operational complexity without providing efficient scalability.

The second approach, Private Service Connect endpoints, enables private IP access to multiple managed services without using public IPs. Multiple service producers can be accessed through a single framework, reducing operational overhead. Centralized access management ensures consistent policy enforcement across teams. Multi-region support allows seamless scalability without redesigning network connectivity. Integrated logging and monitoring simplify auditing and operational oversight. Private Service Connect provides secure, scalable, and operationally efficient access to managed services, meeting privacy, compliance, and operational requirements for healthcare organizations.

Considering private IP connectivity, centralized access control, multi-service support, and scalability, Private Service Connect is the optimal solution for securely accessing multiple Google Cloud-managed services in healthcare environments.

Question 97

A financial services company needs to connect multiple on-premises data centers to Google Cloud. They require high throughput, low latency, dynamic routing, automatic failover, and centralized management of network routes. Which solution is most appropriate?

A) Cloud VPN Classic
B) Cloud Interconnect Dedicated with Cloud Router
C) Cloud Interconnect Partner with Cloud Router
D) Manually configured static routes

Correct Answer: C) Cloud Interconnect Partner with Cloud

Explanation

Financial services companies handle highly sensitive and time-critical workloads that require predictable network performance, high availability, and secure connectivity. Connecting multiple on-premises datacenters to Google Cloud involves evaluating bandwidth, latency, dynamic route management, failover capabilities, and operational efficiency to ensure continuous operations and compliance with regulatory requirements.

The first approach, Cloud VPN Classic, provides encrypted connectivity over the public internet. While VPNs ensure security, they do not guarantee predictable bandwidth or low latency due to variability in public networks. Each connection must be configured individually, and dynamic route propagation is limited, requiring manual updates for changes in network topology. Failover is either manual or requires additional configuration with multiple tunnels. Although VPNs can provide secure connectivity, they cannot meet the performance, scalability, or automation requirements of global financial operations.

The second approach, Cloud Interconnect Dedicated with Cloud Router, provides high-bandwidth, low-latency connectivity. Dedicated interconnects ensure predictable performance and reliability. Cloud Router supports dynamic routing, allowing automatic route propagation when network changes occur. Redundant interconnects can provide failover, but configuring partner connectivity and operational management can be more complex and may require additional support. While this solution is viable, it may introduce higher operational effort compared to partner-managed solutions.

The fourth approach, manually configured static routes, is the least scalable. Each data center requires manual route management, and any network change necessitates configuration updates across all endpoints. Failover is not automated, and static routes do not adapt to optimize traffic flows dynamically. Operational complexity grows exponentially as more data centers are added, increasing the risk of errors.

The third approach, Cloud Interconnect Partner with Cloud Router, provides high-bandwidth, low-latency connectivity with dynamic routing and automatic failover. Partner interconnect ensures reliable performance without the organization managing physical infrastructure. Cloud Router enables dynamic route propagation, reducing operational overhead. Redundant connections automatically provide failover, ensuring uninterrupted service. Centralized management simplifies monitoring, logging, and policy enforcement, supporting operational efficiency and compliance. This approach satisfies all critical requirements for a financial services network: predictable high throughput, low latency, dynamic routing, failover automation, and centralized management. It allows the company to securely and efficiently connect multiple data centers to Google Cloud while minimizing operational complexity.

Considering all factors, including performance, scalability, failover, and centralized management, Cloud Interconnect Partner with Cloud Router is the optimal solution for connecting multiple financial services datacenters to Google Cloud.

Question 98

A global SaaS provider wants to deliver its web application to users worldwide with minimal latency. Requirements include a single public IP, SSL termination at the edge, automatic routing to the nearest healthy backend, and autoscaling to handle spikes in traffic. Which load balancer should they implement?

A) Regional External HTTP(S) Load Balancer
B) Global External HTTP(S) Load Balancer
C) TCP Proxy Load Balancer
D) Internal HTTP(S) Load Balancer

Correct Answer: B) Global External HTTP(S) Load Balancer

Explanation

Global SaaS applications need low-latency, reliable access for users in multiple geographic regions. Key requirements include a single public IP for simplicity, SSL termination at the edge to offload encryption processing from backend servers, health-based routing to direct users to the nearest available backend, and autoscaling to handle sudden traffic surges. Evaluating Google Cloud load balancer options highlights the most suitable solution.

The first approach, regional external HTTP(S) load balancing, distributes traffic within a single region. While SSL termination and autoscaling are supported within the region, users outside the region experience higher latency because traffic cannot automatically route to the nearest backend in other regions. Failover across regions is not automatic, limiting availability. This solution is suitable for regional applications but does not meet global requirements.

The third approach, TCP Proxy Load Balancing, provides global routing at the TCP level. Although it can route traffic to the nearest healthy backend, it lacks application-layer features such as SSL termination at the edge, content-based routing, and advanced HTTP(S) features. SaaS applications typically require HTTP(S) protocols, and edge SSL termination is critical to reduce backend load and optimize performance. TCP Proxy alone does not satisfy these application-layer needs.

The fourth approach, internal HTTP(S) load balancing, is designed for private traffic within a VPC. It does not provide a public IP for external users and cannot route global traffic. Autoscaling and SSL termination are confined to internal workloads, making this solution unsuitable for public SaaS applications.

The second approach, global external HTTP(S) load balancing, provides a single public IP address accessible worldwide. Traffic is automatically routed to the closest healthy backend to reduce latency. SSL termination occurs at the edge, minimizing backend processing requirements. Autoscaling dynamically adjusts backend capacity across multiple regions, ensuring seamless handling of traffic spikes. Multi-region failover provides high availability; if a backend in one region fails, traffic automatically redirects to the nearest healthy backend. Centralized monitoring and logging provide operational visibility, enabling performance optimization and troubleshooting. This solution meets all requirements: global reach, low-latency routing, edge SSL termination, health-based routing, and autoscaling for unpredictable workloads.

Given global access, low latency, edge SSL termination, health-based routing, and dynamic scaling requirements, global external HTTP(S) load balancing is the optimal choice for SaaS providers serving worldwide users.

Question 99

A healthcare organization needs internal applications to access multiple Google Cloud managed services privately, without using public IPs. Requirements include private IP connectivity, centralized access management, and support for multiple service producers. Which solution is most appropriate?

A) VPC Peering with each service
B) Private Service Connect endpoints
C) Assign external IPs and restrict access via firewall rules
D) Individual VPN tunnels for each service

Correct Answer: B) Private Service Connect endpoints

Explanation

Healthcare organizations must maintain strict privacy and regulatory compliance when accessing cloud services. Internal applications require private connectivity to Google Cloud managed services to avoid public internet exposure. Requirements include private IP connectivity, centralized access management to enforce consistent policies, and support for multiple service producers to simplify operations. Evaluating available solutions clarifies the most suitable choice.

The first approach, VPC Peering with each service, provides private connectivity but does not scale efficiently for multiple services. Each managed service requires a separate peering connection, and overlapping IP ranges are unsupported. Centralized access management is limited, as policies must be configured individually per peering. Operational complexity grows significantly with more services, making it unsuitable for large healthcare environments.

The third approach, assigning external IPs and restricting access via firewall rules, exposes services to the public internet, even if access is limited by firewall rules. Centralized access management is difficult, and multiple service producers require individual firewall configurations, increasing administrative overhead. This approach does not fully comply with privacy and regulatory requirements.

The fourth approach, individual VPN tunnels for each service, provides encrypted connectivity but introduces high operational overhead. Each VPN tunnel requires separate configuration, monitoring, and maintenance. Scaling to multiple services or teams is cumbersome, and centralized policy management is difficult because each tunnel is independent. Operational complexity and administrative burden are significant.

The second approach, Private Service Connect endpoints, enables private IP access to multiple managed services without using public IPs. Multiple service producers can be accessed through a single centralized framework, reducing administrative effort. Centralized access management ensures consistent policy enforcement across teams. Multi-region support allows seamless scalability without redesigning network architecture. Integrated logging and monitoring facilitate auditing and operational oversight. Private Service Connect is secure, scalable, and operationally efficient, meeting privacy, compliance, and operational requirements for healthcare organizations.

Given private IP connectivity, centralized access control, multi-service support, and regulatory compliance, Private Service Connect is the optimal solution for healthcare organizations accessing multiple Google Cloud managed services securely.

Question 100

A global retail company wants to securely connect multiple on-premises stores to Google Cloud. They require high throughput, low latency, dynamic route updates, automatic failover, and centralized route management. Which solution is most appropriate?

A) Cloud VPN Classic
B) Cloud Interconnect Dedicated without Cloud Router
C) Cloud Interconnect Partner with Cloud Router
D) Manually configured static routes

Correct Answer: C) Cloud Interconnect Partner with Cloud Router

Explanation

Global retail operations require secure, high-performance connectivity between physical store locations and cloud infrastructure. Connectivity must support large data transfers for inventory, point-of-sale, and analytics applications while maintaining low latency for real-time operations. Dynamic route updates, automatic failover, and centralized route management are essential to reduce operational complexity and ensure continuous availability. Evaluating available Google Cloud solutions highlights the optimal approach.

The first approach, Cloud VPN Classic, provides secure connectivity over the public internet using IPsec tunnels. While VPNs ensure encryption, they are limited in bandwidth and throughput, which can impede the performance of retail operations with high data volumes. Routing is primarily static, requiring manual updates for any network topology changes. Failover is either manual or requires multiple tunnel configurations, increasing operational complexity. VPNs are suitable for small-scale or low-bandwidth deployments but do not meet the performance, scalability, or automation requirements of a global retail network.

The second approach, Cloud Interconnect Dedicated without Cloud Router, provides private, high-bandwidth connections with predictable low latency. Dedicated interconnects offer excellent performance; however, without a Cloud Router, all routes must be configured manually. Failover is not automatic, and adding new store locations or updating subnets requires significant manual effort. While throughput and latency are addressed, operational efficiency and dynamic route propagation remain limited.

The fourth approach, manually configured static routes, is the least scalable. Each store location requires individual route updates, and network changes must be manually propagated across all sites. Failover is not automated, and traffic cannot dynamically adjust for optimal routing. Operational complexity increases as the network grows, creating risk for misconfiguration and outages.

The third approach, Cloud Interconnect Partner with Cloud Router, combines high throughput, low latency, dynamic routing, automatic failover, and centralized management. Partner interconnect ensures reliable performance without the organization managing physical infrastructure. Cloud Router enables dynamic route propagation, automatically updating routes as network topology changes. Redundant connections provide automatic failover, ensuring continuous operations during link or device failures. Centralized monitoring and management simplify operational oversight and reduce human error. This solution fulfills all essential requirements for a global retail network: predictable high bandwidth, low latency, dynamic routing, automatic failover, and centralized management. It enables the company to securely connect multiple on-premises stores to Google Cloud while minimizing operational complexity.

Considering bandwidth, latency, failover, scalability, and centralized management, Cloud Interconnect Partner with Cloud Router is the optimal solution for connecting multiple retail locations to Google Cloud.

Question 101

A global SaaS provider wants to expose a single public endpoint for its application. Requirements include SSL termination at the edge, health-based routing to the nearest backend, and autoscaling to accommodate variable traffic. Which Google Cloud load balancer is the best choice?

A) Regional External HTTP(S) Load Balancer
B) Global External HTTP(S) Load Balancer
C) TCP Proxy Load Balancer
D) Internal HTTP(S) Load Balancer

Correct Answer: B

Explanation

Global SaaS applications demand low-latency access, high availability, and scalable performance. Requirements include a single global IP, SSL termination at the edge to offload encryption from backend servers, health-based routing to direct users to the nearest healthy backend, and autoscaling to handle unpredictable traffic spikes. Evaluating Google Cloud load balancing solutions identifies the optimal choice.

The first approach, regional external HTTP(S) load balancing, provides SSL termination and autoscaling within a single region. However, users outside the region may experience higher latency since traffic cannot automatically route to the nearest backend in other regions. Multi-region failover is not automatic, which can reduce availability. This solution is suitable for regional applications but does not satisfy global SaaS requirements.

The third approach, TCP Proxy Load Balancing, supports global routing at the TCP level. It can route traffic to the nearest healthy backend but lacks application-layer features such as edge SSL termination and content-based routing. SaaS applications rely heavily on HTTP(S) protocols, and edge SSL termination is essential to reduce backend load, improve performance, and simplify certificate management. TCP Proxy alone is insufficient for SaaS applications.

The fourth approach, internal HTTP(S) load balancing, is intended for private traffic within a VPC. It does not provide a public IP for external users and cannot route global traffic. SSL termination and autoscaling are limited to internal workloads, making this solution unsuitable for public-facing SaaS applications.

The second approach, global external HTTP(S) load balancing, provides a single public IP address accessible worldwide. Traffic is automatically routed to the nearest healthy backend to minimize latency. SSL termination occurs at the edge, reducing backend load. Autoscaling dynamically adjusts backend capacity across regions, ensuring uninterrupted service during traffic surges. Multi-region failover ensures high availability; if one region fails, traffic automatically reroutes to the closest healthy backend. Centralized monitoring and logging simplify operational oversight and troubleshooting. This solution fully meets global SaaS requirements: low-latency access, edge SSL termination, health-based routing, and autoscaling for variable traffic patterns.

Given global reach, low latency, edge SSL termination, and autoscaling requirements, global external HTTP(S) load balancing is the optimal solution for SaaS providers serving worldwide users.

Question 102

A healthcare organization needs internal applications to access multiple Google Cloud managed services privately, without exposing traffic to the public internet. Requirements include private IP connectivity, centralized access control, and support for multiple service producers. Which solution should be implemented?

A) VPC Peering with each service
B) Private Service Connect endpoints
C) Assign external IPs and use firewall rules
D) Individual VPN tunnels for each service

Correct Answer: B) Private Service Connect endpoints

Explanation

Healthcare organizations must comply with strict privacy and regulatory standards when accessing cloud services. Internal applications need private connectivity to Google Cloud managed services to prevent data exposure on the public internet. Requirements include private IP connectivity to isolate traffic, centralized access management to enforce consistent policies, and support for multiple service producers to simplify operational management. Evaluating solutions clarifies the most appropriate approach.

The first approach, VPC Peering with each service, provides private connectivity but does not scale efficiently for multiple services. Each managed service requires a separate peering connection. Overlapping IP ranges are unsupported, and centralized access management is limited, as policies must be configured individually per peering. Operational complexity increases as the number of services grows, making this approach impractical for large healthcare organizations.

The third approach, assigning external IPs with firewall rules, exposes services to the public internet while attempting to restrict access. Firewall rules can limit access to authorized users, but centralized access management is difficult to implement. Multiple service producers require separate firewall configurations, increasing administrative overhead. This method does not fully comply with privacy and regulatory requirements.

The fourth approach, individual VPN tunnels for each service, provides encrypted connectivity but introduces high operational overhead. Each VPN tunnel must be configured, monitored, and maintained separately. Scaling to multiple services or teams is cumbersome. Centralized access control is difficult, as each VPN operates independently. This approach increases complexity and operational burden without providing efficient scalability.

The second approach, Private Service Connect endpoints, provides private IP access to multiple managed services without exposing traffic to the public internet. Multiple service producers can be accessed through a single framework, reducing administrative effort. Centralized access management ensures consistent policy enforcement across teams. Multi-region support enables seamless scalability without redesigning network architecture. Integrated logging and monitoring facilitate auditing and operational oversight. Private Service Connect provides secure, scalable, and operationally efficient access to managed services, meeting privacy, compliance, and operational requirements for healthcare organizations.

Considering private IP connectivity, centralized access control, multi-service support, and regulatory compliance, Private Service Connect is the optimal solution for healthcare organizations accessing multiple Google Cloud managed services securely.

Question 103

A global logistics company wants to securely connect its on-premises warehouses to Google Cloud. They require high bandwidth, low latency, automatic failover, dynamic route propagation, and centralized route management. Which solution is most appropriate?

A) Cloud VPN Classic
B) Cloud Interconnect Dedicated with Cloud Router
C) Cloud Interconnect Partner with Cloud Router
D) Manually configured static routes

Correct Answer: C) Cloud Interconnect Partner with Cloud Router

Explanation

Global logistics companies depend on real-time connectivity between physical warehouse locations and cloud systems to manage inventory, track shipments, and process orders efficiently. The network must provide high throughput for large data transfers, low latency to support time-sensitive operations, automatic failover to ensure continuity during network failures, dynamic route propagation to minimize manual intervention, and centralized route management for operational efficiency. Evaluating Google Cloud connectivity options highlights why Cloud Interconnect Partner with Cloud Router is the optimal choice.

The first approach, Cloud VPN Classic, establishes encrypted tunnels over the public internet. VPNs provide security, but cannot guarantee consistent bandwidth or low latency due to public network variability. Routing is mostly static, requiring manual configuration for each warehouse. Failover is manual or requires multiple tunnels configured in parallel, increasing operational complexity. While VPNs are suitable for small-scale deployments, they cannot satisfy the performance and reliability requirements of a global logistics network handling high-volume operations.

The second approach, Cloud Interconnect Dedicated with Cloud Router, provides private high-bandwidth connections with predictable low latency. Dedicated interconnects offer excellent performance; however, the enterprise must manage physical infrastructure and route configurations. Although Cloud Router enables dynamic routing, scaling across multiple warehouses in different regions introduces additional operational complexity. Failover is possible with redundancy, but configuring partner connectivity often involves more operational overhead than using a partner-managed solution.

The fourth approach, manually configured static routes, is not scalable. Each warehouse requires individual route updates, and any network topology change necessitates manual updates across all sites. Failover is not automatic, and traffic cannot dynamically optimize to maintain low latency. Operational complexity increases exponentially as the number of locations grows, making this approach unsuitable for a global logistics operation.

The third approach, Cloud Interconnect Partner with Cloud Router, provides high bandwidth, low latency, automatic failover, dynamic route propagation, and centralized route management. Partner interconnect ensures reliable performance without the enterprise managing physical infrastructure. Cloud Router enables automatic route propagation, reducing manual configuration and operational overhead. Redundant connections provide automatic failover to maintain continuous operations. Centralized management simplifies monitoring, logging, and policy enforcement, supporting operational efficiency and reliability. This solution meets all critical requirements for a global logistics network and ensures secure and efficient connectivity between warehouses and Google Cloud.

Question 104

A SaaS company wants to deliver a globally accessible web application. Requirements include a single public IP, SSL termination at the edge, health-based routing to the nearest healthy backend, and automatic scaling during traffic spikes. Which load balancer should they deploy?

A) Regional External HTTP(S) Load Balancer
B) Global External HTTP(S) Load Balancer
C) TCP Proxy Load Balancer
D) Internal HTTP(S) Load Balancer

Correct Answer: B) Global External HTTP(S) Load Balancer

Explanation

SaaS applications with global users require low-latency access, high availability, and scalable performance. Key requirements include a single global IP for simplicity, SSL termination at the edge to reduce backend processing, health-based routing to ensure users reach the nearest healthy backend, and automatic scaling to handle traffic surges. Evaluating Google Cloud load balancing options identifies the best fit.

The first approach, regional external HTTP(S) load balancing, distributes traffic within a single region. While SSL termination and autoscaling are supported regionally, users outside the region may experience higher latency because traffic cannot automatically route to the nearest backend in other regions. Multi-region failover is not automatic, limiting availability. While suitable for regional applications, it does not satisfy global SaaS requirements.

The third approach, TCP Proxy Load Balancing, provides global routing at the TCP layer. Although it can route traffic to the nearest healthy backend, it lacks application-layer features such as SSL termination at the edge and content-based routing. SaaS applications rely on HTTP(S), and edge SSL termination is essential to reduce backend load, improve performance, and simplify certificate management. TCP Proxy alone does not fully satisfy these application-layer requirements.

The fourth approach, internal HTTP(S) load balancing, is designed for private traffic within a VPC. It does not provide a public IP for external users and cannot route traffic globally. Autoscaling and SSL termination are limited to internal workloads, making this solution unsuitable for public-facing SaaS applications.

The second approach, global external HTTP(S) load balancing, provides a single public IP address globally. Traffic is automatically routed to the nearest healthy backend to minimize latency. SSL termination occurs at the edge, reducing backend processing requirements. Autoscaling dynamically adjusts backend capacity across multiple regions, ensuring seamless handling of traffic spikes. Multi-region failover guarantees high availability; if a backend in one region fails, traffic automatically redirects to the nearest healthy backend. Centralized monitoring and logging simplify operational oversight, performance optimization, and troubleshooting. This solution fully satisfies global SaaS requirements: low-latency access, edge SSL termination, health-based routing, and autoscaling for unpredictable traffic patterns.

Considering global reach, low latency, edge SSL termination, health-based routing, and autoscaling, global external HTTP(S) load balancing is the optimal choice for SaaS applications serving worldwide users.

Question 105

A healthcare organization wants internal applications to access multiple Google Cloud managed services privately. Requirements include private IP connectivity, centralized access control, and support for multiple service producers. Which solution should they implement?

A) VPC Peering with each service
B) Private Service Connect endpoints
C) Assign external IPs with firewall rules
D) Individual VPN tunnels for each service

Correct Answer: B) Private Service Connect endpoints

Explanation

Healthcare organizations must maintain strict privacy and regulatory compliance when accessing cloud services. Internal applications require private connectivity to Google Cloud managed services to prevent data exposure over the public internet. Requirements include private IP connectivity, centralized access control to enforce consistent policies, and support for multiple service producers to simplify operational management. Evaluating solutions clarifies the optimal choice.

The first approach, VPC Peering with each service, provides private connectivity but does not scale efficiently. Each managed service requires a separate peering connection, and overlapping IP ranges are unsupported. Centralized access control is limited because policies must be applied individually for each peering. Operational complexity grows significantly as more services are added, making this approach impractical for large healthcare organizations.

The third approach, assigning external IPs with firewall rules, exposes services to the public internet while restricting access. While firewall rules limit connections to authorized users, centralized access management is difficult, and multiple service producers require separate firewall configurations, increasing administrative overhead. This method does not fully comply with healthcare privacy and regulatory requirements.

The fourth approach, individual VPN tunnels for each service, provides encrypted connectivity but introduces high operational overhead. Each VPN tunnel must be configured, monitored, and maintained independently. Scaling to multiple services or teams is cumbersome. Centralized access control is challenging because each tunnel is independent. Operational complexity and administrative burden increase significantly without providing efficient scalability.

The second approach, Private Service Connect endpoints, enables private IP access to multiple managed services without exposing traffic to the public internet. Multiple service producers can be accessed through a single framework, reducing administrative effort. Centralized access management ensures consistent policy enforcement across teams. Multi-region support allows seamless scalability without redesigning network architecture. Integrated logging and monitoring facilitate auditing and operational oversight. Private Service Connect is secure, scalable, and operationally efficient, meeting privacy, compliance, and operational requirements for healthcare organizations.

Google Professional Cloud Network Engineer Exam Dumps and Practice Test Questions Set 7 Q91-105

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