Google Professional Cloud Network Engineer  Exam Dumps and Practice Test Questions Set 6 Q76-90

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Question 79

A global retail company wants to connect multiple on-premises data centerss to Google Cloud. They require high throughput, dynamic route propagation, redundancy, and minimal operational overhead. Which solution is most suitable?

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

Correct Answer: C) Cloud Interconnect Partner with Cloud Router

Explanation

Retail organizations with multiple on-premises datacenters need a network solution that supports high throughput for real-time transaction processing, dynamic route propagation for scalability, redundancy for high availability, and minimal operational overhead to reduce administrative complexity. Selecting the appropriate connectivity method requires evaluating bandwidth, latency, failover mechanisms, centralized route management, and scalability.

The first approach, Cloud VPN Classic, provides secure connectivity over the public internet. While VPNs are secure and relatively easy to deploy, they are limited in bandwidth and throughput, which may be insufficient for large retail workloads. Eadatdata center requires manually configured tunnels, and route propagation is typically static or requires manual updates. Failover can be implemented with redundant tunnels, but it is operationally intensive and error-prone. While VPNs offer a secure connection, they do not provide the performance or operational simplicity needed for a global retail network.

The second approach, Cloud Interconnect Dedicated without Cloud Router, offers high-bandwidth, low-latency connections between on-premises datacenters and Google Cloud. While it addresses throughput requirements, the absence of a dynamic routing engine means all routes must be configured and maintained manually. Redundancy is possible but not automated, requiring extra configuration. Adding new datacenters or updating subnets involves significant operational effort. Though performance is excellent, operational efficiency and scalability are limited.

The fourth approach, manually configuring static routes for each data center, is the least scalable. Each datacenter requires individual route updates, and any network change—such as adding a new subnet or datacenter—requires manual updates across all endpoints. Failover is not automatic, and route optimization is not supported. Operational overhead increases exponentially with network growth. This approach is prone to errors and unsuitable for a distributed retail network requiring high availability and automated management.

The third approach, Cloud Interconnect Partner with Cloud Router, combines high throughput and low latency with automated route propagation and centralized management. Partner-provided interconnects provide predictable performance and high bandwidth for large datasets. Cloud Router dynamically advertises and learns routes between Google Cloud and on-premises networks, eliminating the need for manual route configuration. Redundant interconnects and failover configurations ensure high availability. Adding new datacenters or subnets requires minimal configuration, as dynamic routing automatically propagates changes. Centralized monitoring and logging simplify operational management and compliance. This solution satisfies all critical requirements: high throughput, dynamic routing, redundancy, and minimal operational overhead, making it ideal for global retail networks.

Considering the combination of high bandwidth, automated route propagation, redundancy, and operational efficiency, Cloud Interconnect Partner with Cloud Router is the most suitable solution for connecting multiple on-premises datacenters to Google Cloud in a global retail environment.

Question 80

A media streaming company wants to deliver content to users worldwide with low latency. They require a single global IP, automatic routing to the closest healthy backend, SSL termination at the edge, and autoscaling to handle traffic spikes. Which load balancing solution is optimal?

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

Media streaming platforms require global, high-performance delivery of content to minimize latency and provide a seamless viewing experience. Requirements include a single global IP for simplicity, automatic routing to the nearest backend to reduce latency, SSL termination at the edge to offload encryption from backend servers, and autoscaling to handle unpredictable traffic spikes. Choosing the correct load balancer involves understanding geographic reach, application-layer features, failover capabilities, and operational scalability.

The first approach, regional external HTTP(S) load balancing, distributes traffic only within a single geographic region. Users located far from that region may experience high latency because traffic cannot automatically route to the closest backend elsewhere. Failover across regions is not automatic, SSL termination occurs only within that region, and autoscaling is limited to the regional scope. This approach is effective for regional workloads but does not meet global performance or latency requirements for media streaming.

The third approach, TCP Proxy Load Balancing, provides global TCP-level routing and directs traffic to the closest healthy TCP backend. However, it lacks application-layer HTTP(S) features such as SSL termination, content-based routing, or caching. Media streaming applications typically use HTTP(S) for content delivery, and without edge SSL termination, backend servers must handle encryption, increasing load and latency. While TCP Proxy can provide some global routing, it does not optimize for media streaming at the application layer.

The fourth approach, internal HTTP(S) load balancing, is designed for private traffic within a VPC or internal cloud network. It does not expose a public IP for external users and cannot route traffic globally. SSL termination and autoscaling are limited to internal workloads. For public-facing media delivery, this solution is unsuitable, as it cannot meet latency or availability requirements.

The second approach, global external HTTP(S) load balancing, provides a single public IP address for users worldwide. Traffic is automatically routed to the nearest healthy backend, minimizing latency and optimizing performance. SSL termination occurs at the edge, offloading encryption from backend servers and improving efficiency. Autoscaling dynamically adjusts backend capacity during traffic spikes, ensuring uninterrupted service. Multi-region failover guarantees high availability; if a regional backend becomes unavailable, traffic is automatically rerouted to the next closest healthy region. Centralized monitoring and logging provide operational visibility for performance management and troubleshooting. This solution fully meets all requirements: low-latency global access, edge SSL termination, automatic nearest-backend routing, and autoscaling for peak traffic periods.

Given the need for global reach, low latency, edge SSL termination, and automatic scaling, global external HTTP(S) load balancing is the optimal choice for worldwide media streaming delivery.

Question 81

A healthcare organization wants internal teams to access multiple Google Cloud-managed APIs privately. They require private IP connectivity, centralized access control, 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 using firewall rules
D) Configure individual VPN tunnels for each API

Correct Answer: B)  Private Service Connect endpoints

Explanation

Healthcare organizations must ensure secure, private access to managed cloud APIs due to strict privacy regulations and compliance requirements. Traffic must remain within the private network, avoiding the public internet. Centralized access management is necessary to enforce consistent policies across teams, while support for multiple service producers ensures operational scalability and efficiency. Evaluating the options involves examining scalability, security, operational overhead, and compliance readiness.

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

The third approach exposes APIs via external IP addresses and uses firewall rules to restrict access. While firewall rules can limit traffic to authorized users, the APIs remain publicly reachable, increasing exposure risk. Identity-aware access cannot be enforced centrally, and multiple service producers require individual firewall configurations. This method does not fully isolate sensitive healthcare data and introduces compliance and security concerns.

The fourth approach, creating individual VPN tunnels for each API, provides encrypted connectivity but introduces high operational overhead. Each tunnel requires separate configuration, monitoring, and maintenance. Route propagation is manual, and scaling to multiple APIs or distributed teams is cumbersome. Centralized governance is difficult because each VPN operates independently. This approach increases complexity without providing the same operational efficiency as other native private connectivity solutions.

The second approach, Private Service Connect endpoints, allows internal workloads to access multiple managed services privately using internal IP addresses. Multiple service producers can be accessed through a centralized framework, reducing administrative overhead. Centralized access management ensures consistent policy enforcement, simplifying governance and compliance. Multi-region support allows seamless expansion of services without redesigning network connectivity. Integrated logging and monitoring simplify auditing and operational oversight. Private Service Connect provides secure, scalable, and operationally efficient private access to managed APIs, meeting the strict privacy, security, and operational requirements of healthcare organizations.

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

Question 82

A global bank wants to interconnect multiple on-premises data centers with Google Cloud while ensuring high bandwidth, low latency, dynamic routing, 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

Explanation

Banks operate highly sensitive networks that demand high availability, security, and performance. Connecting multiple on-premises datacenters to Google Cloud requires a solution that ensures high bandwidth for large transaction volumes, low latency for real-time operations, dynamic routing to accommodate network changes, automatic failover to maintain uninterrupted service, and centralized route management to reduce operational complexity. Evaluating these requirements against available Google Cloud networking solutions helps determine the most appropriate approach.

The first approach, Cloud VPN Classic, provides secure connectivity over the public internet using IPsec tunnels. While VPNs offer encryption and basic connectivity, they are limited in bandwidth and latency, which can be insufficient for a bank’s high-volume transactions. VPN configuration for multiple datacenters introduces operational overhead, as each connection must be individually maintained and monitored. Failover is not automatic unless multiple tunnels are configured, and route propagation is largely static, requiring manual intervention. Although secure, VPNs lack the dynamic routing and high throughput needed for enterprise banking operations.

The second approach, Cloud Interconnect Dedicated without Cloud Router, provides high-bandwidth, low-latency connectivity to Google Cloud. Dedicated interconnects offer predictable performance, which is critical for time-sensitive financial operations. However, without a Cloud Router, routes must be manually configured, which increases operational overhead and reduces flexibility. Failover is possible but not automatic, requiring additional manual configuration. Centralized route management is limited, making it cumbersome to scale when new data centers or subnets are added. While it solves throughput concerns, this approach does not fully meet the needs for operational efficiency or automated route management.

The fourth approach, manually configured static routes, introduces significant operational complexity. Each data center requires individual route updates, and any changes in the network topology require manual updates across all endpoints. Failover is not automated, and static routes cannot dynamically adjust to optimize traffic paths. This method is error-prone and does not scale well, making it unsuitable for a banking network with multiple sites, regulatory compliance requirements, and high reliability expectations.

The third approach, Cloud Interconnect Partner with Cloud Router, combines high throughput, low latency, dynamic routing, redundancy, and centralized management. Partner-provided interconnect ensures reliable, high-bandwidth connectivity. Cloud Router enables dynamic route propagation, automatically updating routes when networks change. Redundant connections provide automatic failover in case of link or device failure. Adding new datacenters or subnets requires minimal effort, as routes propagate automatically across the network. Centralized monitoring, logging, and policy enforcement enhance operational visibility and simplify compliance. This solution satisfies all critical requirements: high bandwidth, low latency, dynamic routing, failover automation, and centralized route management, making it ideal for global banking operations.

Considering all factors—performance, scalability, dynamic routing, failover, and operational simplicity—Cloud Interconnect Partner with Cloud Router is the most appropriate solution for interconnecting multiple bank datacenters with Google Cloud.

Question 83

A global e-commerce company wants to provide low-latency access to its web applications worldwide. They require a single public IP, SSL termination at the edge, health-based routing to the nearest backend, and automatic scaling during traffic spikes. Which Whiload-balancing solution should they choose?

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 e-commerce platforms face unique challenges: users connect from diverse locations, traffic patterns fluctuate, and application performance directly impacts revenue. Meeting these challenges requires a load-balancing solution that minimizes latency, optimizes backend utilization, and automatically scales to handle varying loads. Key requirements include a single public IP for user simplicity, SSL termination at the edge to reduce backend encryption overhead, routing traffic to the nearest healthy backend to optimize performance, and autoscaling to handle traffic spikes during promotions or peak hours.

The first approach, regional external HTTP(S) load balancing, distributes traffic only within a specific region. Users outside that region may experience higher latency because traffic cannot automatically route to the closest backend elsewhere. Failover across regions is not automatic, SSL termination is region-specific, and autoscaling is limited to regional capacity. This solution is effective for localized workloads but does not satisfy global performance and low-latency requirements.

The third approach, TCP Proxy Load Balancing, provides global routing at the TCP level. It can direct traffic to the nearest healthy backend but lacks application-layer features. SSL termination and content-based routing are unavailable, forcing backend servers to handle encryption, increasing server load and latency. E-commerce platforms rely on HTTP(S) protocols for transaction processing and dynamic content delivery; therefore, TCP-level routing alone does not meet all requirements.

The fourth approach, internal HTTP(S) load balancing, is intended for private traffic within a cloud VPC. It does not expose a public IP for external users and cannot provide global traffic distribution. SSL termination and autoscaling are confined to internal workloads, making this solution unsuitable for public-facing e-commerce platforms.

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, minimizing latency and optimizing user experience. SSL termination occurs at the edge, reducing backend load and simplifying certificate management. Autoscaling adjusts backend capacity dynamically during traffic spikes, ensuring uninterrupted service. Multi-region failover ensures high availability; if a regional backend becomes unavailable, traffic automatically redirects to the next closest healthy backend. Centralized monitoring and logging provide operational visibility, facilitating troubleshooting and performance optimization. This solution satisfies all requirements: low-latency global access, edge SSL termination, health-based routing, and automatic scaling for unpredictable workloads.

Given the need for global reach, performance optimization, and automated scaling, global external HTTP(S) load balancing is the optimal solution for worldwide e-commerce applications.

Question 84

A healthcare organization wants internal teams to access multiple Google Cloud-managed APIs privately, without exposure to the public internet. They require 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 using firewall rules
D) Configure individual VPN tunnels for each API

Correct Answer: B

Explanation

Healthcare organizations must comply with strict privacy and regulatory requirements. Providing internal teams private access to managed cloud APIs ensures that sensitive patient data does not traverse the public internet. Centralized access management allows consistent policy enforcement, reduces operational overhead, and supports multiple service producers efficiently. Evaluating options involves analyzing scalability, security, operational complexity, and compliance readiness.

The first approach, VPC Peering with each service, provides private connectivity. However, it does not scale efficiently for multiple APIs, as each API 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 increases as the number of services grows, making this approach unsuitable for large healthcare environments.

The third approach, assigning external IPs with firewall restrictions, leaves services publicly reachable, increasing exposure risk. Identity-aware access cannot be enforced centrally, and managing multiple service producers adds administrative overhead. This method does not fully isolate sensitive data, violating regulatory best practices for healthcare workloads.

The fourth approach, configuring VPN tunnels for each API, provides encrypted connectivity but introduces high operational overhead. Each tunnel requires individual setup, monitoring, and maintenance. Route propagation is manual, and scaling to multiple APIs or distributed teams is cumbersome. Centralized governance is difficult, as each VPN operates independently.

The second approach, Private Service Connect endpoints, provides private IP access to multiple managed APIs without exposing traffic to the public internet. It allows centralized access management for consistent policy enforcement. Multiple service producers can be accessed through a single framework, reducing administrative effort. Multi-region support enables seamless expansion without network redesign. Integrated logging and monitoring simplify auditing and operational oversight. Private Service Connect delivers secure, scalable, and operationally efficient private access to managed APIs, meeting regulatory, privacy, 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 securely accessing multiple Google Cloud-managed APIs.

Question 85

A global retail company needs to connect multiple on-premises data centers to Google Cloud. They require high throughput, dynamic routing, redundancy, and minimal operational overhead. Which solution is best suited?

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

Correct Answer: C

Explanation

Retail organizations with multiple data centers need a connectivity solution that can handle high-volume traffic with low latency while maintaining operational efficiency. Requirements include high throughput to support transactional workloads, dynamic routing for flexible network management, redundancy to ensure high availability, and minimal manual configuration to reduce administrative overhead. Selecting the right solution involves evaluating bandwidth, routing capabilities, failover support, and operational simplicity.

The first approach, Cloud VPN Classic, provides encrypted connections over the public internet. VPNs are secure but limited in bandwidth and throughput, making them less suitable for high-volume retail operations. Route management is typically static or requires manual intervention, and failover is not automatic. Scaling VPNs for multiple data centers increases operational complexity significantly. Although VPNs offer basic connectivity, they cannot meet the throughput, scalability, or operational efficiency requirements of a global retail network.

The second approach, Cloud Interconnect Dedicated without Cloud Router, provides high-bandwidth, low-latency connectivity between on-premises datacenters and Google Cloud. Dedicated interconnects ensure predictable performance, which is advantageous for transactional workloads. However, without a Cloud Router, routes must be configured manually, and any network changes require additional effort. Failover is possible but requires manual configuration, and centralized route management is limited. While throughput is addressed, operational efficiency, redundancy, automation, and dynamic routing are lacking.

The fourth approach, manually configuring static routes for each data center, is the least scalable. Each data center requires individual route updates, and any network change necessitates manual updates across all endpoints. Failover is not automated, and route optimization is absent. Operational overhead increases exponentially as the network grows, making this solution error-prone and inefficient for global retail operations.

The third approach, Cloud Interconnect Partner with Cloud Router, combines high throughput, low latency, dynamic routing, redundancy, and centralized management. Partner-provided interconnect ensures reliable, high-bandwidth connections. Cloud Router enables dynamic route propagation, automatically updating routes when networks change. Redundant connections provide automatic failover in case of link or device failure. Adding new datacenters or subnets requires minimal effort, as routes propagate automatically across the network. Centralized monitoring and logging enhance operational visibility and simplify troubleshooting. This solution satisfies all critical requirements, making it ideal for global retail networks.

Given the need for high throughput, dynamic routing, redundancy, and minimal operational overhead, Cloud Interconnect Partner with Cloud Router is the most suitable solution for connecting multiple on-premises datacenters to Google Cloud.

Question 86

A global media company wants to deliver streaming content to users worldwide with minimal latency. They require a single global IP, automatic routing to the nearest healthy backend, SSL termination at the edge, and autoscaling to handle sudden spikes in traffic. Which load balancing solution is optimal?

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

Media streaming platforms need high-performance, low-latency delivery for a global audience. Requirements include a single IP address for simplicity, routing traffic to the nearest healthy backend to minimize latency, SSL termination at the edge to offload encryption, and autoscaling to handle unpredictable traffic spikes. Choosing the correct load balancer requires understanding geographic reach, protocol support, application-layer features, failover capabilities, and operational efficiency.

The first approach, regional external HTTP(S) load balancing, distributes traffic only within a single region. Users connecting from other regions may experience higher latency, as traffic cannot be automatically routed to the nearest backend outside the region. Failover across regions is not automatic, SSL termination occurs only within the region, and autoscaling is confined to regional capacity. While effective for local workloads, it cannot meet global performance and latency requirements for streaming content.

The third approach, TCP Proxy Load Balancing, provides global routing at the TCP layer. While it can direct traffic to the closest healthy backend, it lacks application-layer features such as SSL termination at the edge, content-based routing, and caching. Media streaming services typically use HTTP(S) for delivery, so edge SSL termination is critical for offloading encryption from backends and improving performance. Using TCP Proxy would increase backend load and latency, making it only partially suitable.

The fourth approach, internal HTTP(S) load balancing, is intended for private traffic within a cloud network. It does not provide a public IP for global users and cannot route traffic across regions. SSL termination and autoscaling are limited to internal workloads, making it unsuitable for publicly accessible media streaming services.

The second approach, global external HTTP(S) load balancing, provides a single public IP accessible worldwide. Traffic is automatically routed to the nearest healthy backend, minimizing latency. SSL termination occurs at the edge, reducing backend server load and simplifying certificate management. Autoscaling dynamically adjusts backend capacity to handle spikes in traffic, ensuring uninterrupted streaming. Multi-region failover guarantees high availability; if a regional backend becomes unavailable, requests are automatically redirected to the next closest healthy backend. Centralized monitoring and logging provide operational visibility for performance optimization and troubleshooting. This solution fully meets all requirements: low-latency global access, edge SSL termination, automatic nearest-backend routing, and autoscaling for unpredictable traffic patterns.

Given the need for global low-latency delivery, edge SSL termination, health-based routing, and autoscaling, global external HTTP(S) load balancing is the optimal choice for worldwide media streaming services.

Question 87

A healthcare organization wants its internal teams to access multiple Google Cloud managed APIs privately, without exposure to the public internet. They require private IP connectivity, centralized access control, 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 using firewall rules
D) Configure individual VPN tunnels for each API

Correct Answer: B

Explanation

Healthcare organizations handle sensitive patient data, requiring private, secure access to managed cloud APIs. Data must remain within private networks to comply with regulatory and privacy requirements. Centralized access management simplifies governance, ensures consistent policy enforcement, and supports multiple service producers for operational efficiency. Evaluating connectivity solutions involves considering scalability, security, operational overhead, and compliance.

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

The third approach exposes APIs via external IPs and relies on firewall rules to restrict access. Although firewall rules can control traffic, the APIs remain publicly reachable, increasing potential exposure. Identity-aware access cannot be enforced centrally, and managing multiple service producers requires separate firewall configurations, adding administrative overhead. This method does not fully meet privacy or compliance requirements for healthcare workloads.

The fourth approach, creating individual VPN tunnels for each API, ensures encrypted connectivity but introduces high operational overhead. Each tunnel requires separate configuration, monitoring, and maintenance. Route propagation is manual, and scaling to support multiple APIs or distributed teams is cumbersome. Centralized access control is difficult to implement, as each VPN operates independently. This approach increases complexity without providing the benefits of native private connectivity.

The second approach, Private Service Connect endpoints, allows internal workloads to access multiple managed services privately using internal IP addresses. Multiple service producers can be accessed through a single framework, reducing administrative overhead. Centralized access control ensures consistent policy enforcement across teams, simplifying compliance and governance. Multi-region support enables seamless expansion without network redesign. Integrated logging and monitoring facilitate auditing and operational oversight. Private Service Connect delivers secure, scalable, and operationally efficient access to managed APIs, meeting privacy, security, and compliance requirements for healthcare organizations.

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

Question 88

A multinational enterprise wants to interconnect multiple on-premises data centers with Google Cloud. They require high bandwidth, low latency, dynamic route propagation, automatic failover, and centralized 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

Explanation 

Large enterprises require highly reliable and performant network connectivity between their on-premises data centers and Google Cloud. Their network architecture must support high throughput to accommodate significant data transfer volumes, low latency to maintain responsive applications, dynamic routing to adapt to changing network topologies, automatic failover to ensure uninterrupted service, and centralized route management to reduce operational complexity. Choosing the optimal solution involves evaluating bandwidth capacity, routing flexibility, redundancy, and ease of administration.

The first approach, Cloud VPN Classic, provides secure connectivity over the public internet using IPsec tunnels. While it ensures encryption and basic connectivity, it is limited in bandwidth and throughput, which may be insufficient for enterprise workloads with heavy traffic or latency-sensitive applications. Manual configuration of multiple VPN tunnels is required for each data center, increasing operational overhead. Route propagation is static or requires manual updates, and failover is not automatic unless multiple tunnels are carefully configured. VPNs may work for small deployments, but they do not provide the scalability, redundancy, or centralized route management needed for a multinational enterprise.

The second approach, Cloud Interconnect Dedicated without Cloud Router, offers high-bandwidth, low-latency connectivity to Google Cloud. Dedicated interconnects provide predictable performance, which is beneficial for applications requiring large data transfers and consistent latency. However, without a Cloud Router, routes must be configured and maintained manually. Any network topology changes, such as adding a new data center or subnet, require manual route updates. Failover is possible but not automatic; administrators must configure redundancy and test it continuously. Centralized route management is limited, making operations cumbersome for large-scale environments. While this solution addresses throughput and latency, it does not fully meet the requirements for operational efficiency or automated route propagation.

The fourth approach, manually configuring static routes, is not scalable. Each data center requires individual route updates, and any network changes necessitate manual intervention across all endpoints. Failover is not automatic, and static routes cannot dynamically optimize traffic paths. Operational overhead increases exponentially as the number of data centers grows. This approach is prone to human error and is unsuitable for multinational enterprises requiring high availability, low latency, and efficient management.

The third approach, Cloud Interconnect Partner with Cloud Router, combines high throughput, low latency, dynamic routing, redundancy, and centralized management. Partner-provided interconnects ensure reliable, high-bandwidth connectivity with predictable latency. Cloud Router enables dynamic route propagation, automatically adjusting routes when network topology changes. Redundant interconnects provide automatic failover, ensuring uninterrupted service in case of link or device failures. Adding new datacenters or subnets requires minimal effort because routes propagate automatically. Centralized monitoring, logging, and policy enforcement simplify operational management and compliance auditing. This solution meets all critical requirements for multinational enterprises, including high performance, redundancy, dynamic routing, and operational simplicity.

Considering bandwidth, latency, failover, scalability, and centralized management, Cloud Interconnect Partner with Cloud Router is the optimal solution for interconnecting multiple on-premises datacenters with Google Cloud.

Question 89

A global e-commerce company wants to provide low-latency access to its web applications worldwide. They require a single public IP, SSL termination at the edge, health-based routing to the nearest backend, and automatic scaling during traffic spikes. Which load balancing solution should they use?

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 e-commerce platforms must ensure low-latency access for users worldwide, optimize backend utilization, and maintain high availability during traffic spikes. Key requirements include a single public IP for simplicity, SSL termination at the edge to offload encryption from backend servers, routing traffic to the nearest healthy backend to minimize latency, and autoscaling to handle peak traffic. Evaluating these requirements against Google Cloud load balancing solutions allows the selection of the most suitable option.

The first approach, regional external HTTP(S) load balancing, distributes traffic only within a single region. Users connecting from other geographic regions may experience increased latency because traffic cannot automatically route to the nearest backend in a different region. Failover across regions is not automatic, SSL termination occurs only within the selected region, and autoscaling is limited to that region’s backend capacity. This solution is suitable for regional workloads but does not meet global low-latency, single-IP, or failover requirements.

The third approach, TCP Proxy Load Balancing, provides global routing at the TCP layer. It directs traffic to the nearest healthy backend, but it lacks application-layer features such as SSL termination, content-based routing, and caching. E-commerce platforms typically rely on HTTP(S) protocols, so edge SSL termination is essential to offload encryption from backend servers and improve performance. TCP Proxy alone cannot provide optimal application-layer routing or edge SSL termination, which may degrade user experience and increase backend load.

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 distribute traffic globally. SSL termination and autoscaling are limited to internal workloads. This solution cannot meet global low-latency access or high availability requirements for public-facing e-commerce 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, minimizing latency and optimizing user experience. SSL termination occurs at the edge, reducing backend load and simplifying certificate management. Autoscaling dynamically adjusts backend capacity to handle traffic spikes, ensuring uninterrupted service. Multi-region failover guarantees high availability; if one region becomes unavailable, traffic automatically routes to the next closest healthy backend. Centralized monitoring and logging provide operational visibility and facilitate troubleshooting. This solution fully meets all requirements: low-latency global access, edge SSL termination, health-based routing, and autoscaling for unpredictable workloads.

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

Question 90

A healthcare organization wants its internal teams to access multiple Google Cloud managed APIs privately, without exposure to the public internet. They require 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 using firewall rules
D) Configure individual VPN tunnels for each API

Correct Answer: B

Explanation 

Healthcare organizations manage highly sensitive patient information, including electronic health records, diagnostic data, and personal identifiers. Because of the strict privacy expectations placed on healthcare providers, along with legal requirements such as HIPAA and other global regulatory frameworks, protecting data in transit is as important as securing data at rest. Any traffic flowing over the public internet introduces risk, even when encrypted, because it potentially increases exposure to threats, misconfigurations, and unauthorized access. As healthcare systems expand the use of cloud services and managed APIs, choosing the right connectivity model becomes a critical architectural decision that directly affects security, compliance, scalability, and operational efficiency.

A common requirement for healthcare organizations is to maintain private IP connectivity for all communication between internal workloads and cloud-hosted APIs. This ensures that no traffic leaves the internal network perimeter or traverses unpredictable public routes. Along with this, organizations demand centralized access management so that policies, permissions, and governance can be defined and enforced uniformly. Large healthcare enterprises also frequently work with multiple service producers, including various Google Cloud managed APIs, third-party vendors, and internal development teams. Without a scalable connectivity model, the complexity of managing access to these services grows quickly, increasing the risk of configuration errors. Evaluating the available approaches against these needs helps identify which solution best supports security and compliance objectives.

The first approach, using VPC Peering with each managed API, offers direct private connectivity between networks. On the surface, this appears to satisfy the requirement of keeping data off the public internet. However, VPC Peering introduces multiple limitations that make it unsuitable for healthcare enterprises operating at scale. Each API or service producer requires a separate peering connection, and peering relationships must be managed individually. As the number of managed services increases, the number of required peering connections multiplies, creating a spiderweb of dependencies that is difficult to maintain. VPC Peering also does not support overlapping IP ranges, which is a significant constraint for large organizations with complex network topologies or those that have grown through acquisitions. Centralized access management is limited because policies must be configured for each individual peering relationship, making security enforcement inconsistent across teams. For healthcare organizations that rely on dozens of managed APIs across multiple regions, the operational overhead alone makes this approach impractical.

The third approach involves assigning external IPs to managed APIs and then using firewall rules to restrict access. While firewall rules can filter traffic and limit exposure to authorized users, this strategy still leaves APIs publicly reachable. Even if access is restricted to certain source IPs, the fact that these endpoints exist on the public internet increases the overall attack surface. Healthcare organizations must not only protect data, but also ensure that services are not exposed to any form of public probing or scanning. This makes public IP–based designs inherently risky. Centralized access management is limited because each API endpoint and corresponding firewall rule must be configured and maintained independently. As new APIs are added or existing ones evolve, the number of required firewall rules grows, which increases administrative burden and raises the likelihood of misconfiguration. Additionally, coordinating firewall updates across security, networking, and compliance teams becomes cumbersome, especially in fast-paced environments. This approach, while functional for simple use cases, does not meet the stringent privacy and regulatory requirements faced by healthcare providers.

The fourth approach, configuring individual VPN tunnels for each API, improves security by encrypting traffic and ensuring that communication occurs through secure channels. While VPN tunnels are widely used for hybrid connectivity, they are not efficient for connecting to numerous managed APIs. Each tunnel must be configured separately, monitored continuously, and updated when changes occur on either side of the connection. Routing must be manually managed and propagated, and troubleshooting connectivity issues can quickly become time-consuming. When organizations need to access multiple APIs or when different development teams maintain separate environments, the number of required VPN tunnels can grow dramatically. This fragmented design makes enforcing centralized governance difficult because each tunnel effectively becomes an isolated environment with its own configuration. The risk of human error increases, as does the overall operational burden. For healthcare organizations with limited networking staff or strict audit requirements, the complexity of managing many independent VPN tunnels becomes a significant drawback.

The second approach, Private Service Connect (PSC), directly addresses these challenges and aligns closely with the requirements of healthcare organizations. PSC allows internal workloads to access multiple Google Cloud-managed APIs through private IP addresses, ensuring traffic remains entirely within Google’s internal network backbone without traversing the public internet. This is a crucial advantage for organizations focused on compliance and data security. PSC supports multiple service producers and consolidates access into a single architecture, reducing reliance on numerous peering relationships, firewall rules, or VPN tunnels. By centralizing access through standardized endpoints, PSC simplifies administration and ensures consistent policy enforcement across all teams. This centralized framework allows security administrators to maintain clear visibility and apply uniform governance to all managed API connections.

Another key advantage of Private Service Connect is its multi-region support. Large healthcare systems often operate across multiple geographical areas, requiring resilient architectures that can easily scale. PSC enables organizations to extend connectivity to new regions without redesigning the network or establishing new complex connectivity patterns. Integrated logging and monitoring further enhance audit readiness, allowing compliance teams to track API usage, access patterns, and potential anomalies through a single pane of glass. This greatly simplifies documentation and reporting for regulatory audits.

When evaluating all four connectivity strategies through the lens of private IP connectivity, centralized access control, multi-service scalability, operational efficiency, and regulatory compliance, Private Service Connect emerges as the strongest and most comprehensive solution. It minimizes exposure risk, reduces complexity, and provides a secure and scalable framework that aligns with the needs of healthcare organizations seeking to safely access multiple managed APIs on Google Cloud.