Google Professional Cloud Network Engineer Exam Dumps and Practice Test Questions Set 5 Q61-75
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Question 61
A retail company wants to connect hundreds of branch offices to Google Cloud with minimal operational overhead. They require highly available, secure connectivity with dynamic route updates, automated failover, and bandwidth flexibility. Which solution is best suited for their needs?
A) Cloud VPN Classic tunnels configured per branch
B) Cloud VPN HA with Cloud Router
C) VPC Peering for each branch office
D) Static routes configured manually on every branch router
Answer: B) Cloud VPN HA with Cloud Router
Explanation
Connecting a large number of branch offices to a cloud environment requires a design that balances security, reliability, scalability, and operational simplicity. Retail organizations often have dozens or hundreds of geographically distributed locations, which complicates network management. Each site needs consistent connectivity to cloud-hosted applications, and administrators want dynamic routing and automatic failover to avoid service disruptions. Bandwidth flexibility is also important as data transfer requirements fluctuate during peak periods. Evaluating each available approach highlights the operational and technical advantages or limitations in such a scenario.
The first approach establishes individual encrypted tunnels from each branch to the cloud. While this method ensures secure communication, it lacks dynamic routing capabilities. Each tunnel must be manually configured, and any changes in routing or subnets require updates at both ends. As the number of branches increases, administrative overhead grows exponentially. Additionally, bandwidth allocation is fixed per tunnel, making it difficult to adjust dynamically during peak demand. Tunnel failover is limited unless multiple redundant tunnels are configured manually, which further complicates operations. While functional for small deployments, it does not scale efficiently to hundreds of branches.
The third approach relies on creating direct private connections between each branch network and a VPC using peering. Peering is intended for interconnecting VPCs, not for hybrid connectivity with remote on-premises locations. It does not provide encryption or automated failover, and route propagation for hundreds of branches would require extensive manual management. Overlapping address spaces cannot be handled easily, creating additional operational challenges. This makes it unsuitable for widespread branch connectivity where security, dynamic routing, and high availability are critical.
The fourth approach uses static routes configured manually at each branch router. While traffic can be directed securely, static routing is inflexible. Any change in cloud subnets, branch addresses, or network topology requires manual updates across all devices. This method also does not provide automated failover, dynamic bandwidth scaling, or centralized control. Managing hundreds of branches in this manner would be error-prone and operationally costly. It is not practical for an organization seeking scalable and reliable connectivity.
The second approach pairs high-availability VPN gateways with a dynamic routing engine. This design allows redundant tunnels, automatically handling failover if a primary link goes down. Dynamic route updates propagate to all branches via the routing engine, eliminating the need for manual configuration when networks expand or change. Bandwidth can be distributed across multiple tunnels to handle traffic surges, ensuring predictable performance. Security is maintained through encrypted tunnels while operational overhead is minimized because administrators do not need to manage individual tunnels or static routes for each site. This method is scalable to hundreds of branches and supports both high availability and flexibility in managing network growth. By centralizing control and leveraging dynamic routing, the organization can ensure consistent connectivity, resilience, and operational simplicity while maintaining secure communication to cloud-hosted resources.
Considering the need for high availability, dynamic routing, secure connectivity, and scalability across hundreds of branches, the combination of high-availability VPN with a routing engine represents the most efficient and robust solution.
Question 62
A media streaming company needs to distribute content globally with minimal latency. They require a single public IP address for users, automatic routing to the nearest healthy backend, SSL termination at the edge, and automatic scaling during traffic spikes. Which solution best fits these requirements?
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
Answer: B) Global External HTTP(S) Load Balancer
Explanation
Delivering media streaming services worldwide demands low-latency, highly available load balancing capable of intelligent global routing. Users should connect to the nearest backend automatically, and SSL termination must occur at the edge to reduce backend processing. Scalability during traffic spikes ensures consistent performance and uninterrupted service. Assessing the options involves understanding their scope, protocol support, global reach, failover mechanisms, and scalability features.
The first approach operates only at the regional level. It provides HTTP(S) load balancing within a single region but cannot direct traffic intelligently across multiple regions. Users located far from the regional endpoint may experience higher latency, and automatic failover across regions is not supported. SSL termination occurs only in the specific region, limiting the ability to offload encryption globally. Scaling is confined to a single region, which restricts performance during global traffic spikes. This method is not suitable for a worldwide content distribution network requiring a unified global presence.
The third option is designed for TCP-level traffic distribution across global endpoints. While it can route users to the closest healthy TCP backend, it does not provide application-layer features such as SSL termination for web protocols. Content-based routing, caching, or HTTP(S) header-based logic is not supported. For media streaming applications, which rely on HTTP(S), TCP-level routing alone fails to provide the necessary optimization, leaving backend systems to handle SSL decryption, increasing load and latency.
The fourth approach is intended for internal, private traffic within a cloud environment. It cannot provide public access for worldwide users. SSL termination, global routing, and autoscaling for external user traffic are not supported. While suitable for internal applications, this method is entirely inappropriate for public-facing media streaming services where users are geographically distributed.
The second approach offers a global endpoint with a single public IP address accessible worldwide. Requests are automatically routed to the closest healthy backend, minimizing latency for end users. SSL termination at the edge ensures encryption is handled efficiently, reducing load on backend systems. Autoscaling adjusts backend capacity dynamically based on incoming traffic, maintaining performance during spikes. Multi-region failover ensures service continuity if a regional backend becomes unavailable. This design supports both operational efficiency and a high-quality user experience. Monitoring and logging capabilities provide centralized visibility into traffic patterns and backend health, which is critical for media platforms managing high-volume, latency-sensitive workloads. By leveraging the global edge network, content is distributed efficiently, improving performance and resilience.
Considering the need for a single global IP, automated nearest-backend routing, edge SSL termination, and automatic scaling during traffic surges, the global external HTTP(S) load balancing solution is the most suitable choice for worldwide media streaming.
Question 63
A healthcare organization wants its internal teams to securely access multiple managed Google Cloud APIs without exposing traffic to the public internet. They require private IP connectivity, centralized access management, and support for multiple service producers simultaneously. Which solution best meets these requirements?
A) VPC Peering with each service
B) Private Service Connect endpoints
C) Assign external IPs and enforce firewall rules
D) Configure individual VPN tunnels for each API
Answer: B) Private Service Connect endpoints
Explanation
Healthcare organizations must ensure that access to sensitive services is secure, private, and auditable due to regulatory compliance and data privacy requirements. When teams need to consume managed services without exposing traffic to the public internet, the solution must provide private IP connectivity and centralized access management. Additionally, multiple service producers may exist, requiring a scalable approach that minimizes operational complexity and ensures consistent security policies. Evaluating connectivity options requires understanding private access capabilities, operational simplicity, and multi-service support.
The first approach, VPC Peering with each managed service, enables network-to-network communication. While it ensures private connectivity, this approach does not scale well across multiple managed services because each service requires a unique peering relationship. It also mandates non-overlapping IP ranges, limiting flexibility when multiple teams operate independently. Centralized access control is minimal because each peering connection must be managed individually, and operational complexity increases significantly with scale.
The third approach exposes services using external IP addresses while restricting access with firewall rules. Although firewall rules can limit traffic, the services are still publicly reachable. This increases exposure risk and fails to meet strict privacy and compliance requirements. Centralized management is limited because each service must be configured individually. Multiple service producers add further complexity, making this method operationally cumbersome and insecure for sensitive healthcare workloads.
The fourth approach involves creating VPN tunnels for each API. While this ensures encrypted, private transport, it introduces significant operational overhead. Each service requires a separate tunnel, increasing configuration complexity and management burden. Route propagation is manual, and scaling to multiple services or multiple offices is difficult. Centralized governance is not easily achievable because each VPN is independently managed, making this approach impractical for a large healthcare organization.
The second approach, Private Service Connect, allows internal workloads to access managed services privately using internal IP addresses. This maintains traffic isolation from the public internet, meeting privacy and compliance requirements. Multiple service producers can be accessed through a single endpoint framework, simplifying management and operational overhead. Subnet-level control allows teams to enforce granular access policies while centralizing governance. Additionally, Private Service Connect supports multi-region deployments, ensuring scalability without redesign. This solution provides an integrated and native cloud method for private API consumption, centralizing control and simplifying monitoring, logging, and access enforcement. Teams can access services securely and efficiently, avoiding exposure to the public internet while maintaining operational simplicity and regulatory compliance.
Given the need for private IP access, centralized management, and multi-service support, Private Service Connect is the most effective and scalable solution for securely consuming managed services in a healthcare environment.
Question 64
A logistics company needs to interconnect multiple Google Cloud VPCs and on-premises datacenters. They require centralized routing, high availability, support for overlapping IP ranges, and scalable management as new sites are added. Which architecture best fulfills these requirements?
A) VPC Peering between all VPCs and individual VPNs to datacenters
B) Shared VPC across all projects with static routes
C) Network Connectivity Center hub-and-spoke architecture
D) Cloud VPN Classic with manual route configuration
Answer: C) Network Connectivity Center hub-and-spoke architecture
Explanation
Building a unified network fabric for multiple cloud VPCs and on-premises datacenters requires a solution that balances centralization, scalability, high availability, and routing flexibility. Logistics companies often have numerous geographically distributed sites, each with unique subnets that may overlap with other sites. The challenge is to provide efficient communication between cloud and on-premises environments, manage routes centrally, and support future expansion without introducing operational complexity or single points of failure. Evaluating the available approaches reveals the differences in scalability, manageability, and technical suitability.
The first approach connects each VPC directly to every other VPC using pairwise connections and individual VPNs to datacenters. While this provides secure communication, the number of connections grows exponentially as the network scales. Maintaining hundreds of tunnels and VPC Peering relationships introduces operational overhead and increases the chance of misconfigurations. Overlapping IP ranges cannot be supported without network address translation, complicating the network design. Manual configuration of routes across multiple VPNs and VPCs further increases complexity. This solution becomes unwieldy for a logistics company with many VPCs and datacenters that may expand over time.
The second approach leverages Shared VPC to centralize resource management and policy enforcement. While it allows multiple projects to share a VPC, static routes are required for inter-VPC or on-premises communication. Static routing requires manual updates whenever a subnet is added or a new site is connected, increasing operational burden. Overlapping IP ranges are not supported, limiting flexibility for distributed teams with independent addressing. Regional traffic may also take suboptimal paths because routing is manually configured rather than dynamically optimized. Shared VPC centralizes administrative control but does not provide a scalable or flexible solution for a growing, multi-datacenter logistics network.
The fourth approach uses individually configured VPN tunnels with manual routes. Each branch or datacenter requires separate configuration, and any network change necessitates updates at all affected endpoints. This does not scale efficiently and introduces significant administrative overhead. Automated route propagation is not supported, limiting resilience and flexibility. Traffic between overlapping networks cannot be handled without complex workarounds. For an enterprise with multiple sites, this design is operationally intensive and error-prone.
The third approach employs a hub-and-spoke model using a central connectivity hub. VPCs and datacenters connect as spokes, with the hub managing routing and policy enforcement centrally. Dynamic route propagation ensures that updates to subnets or new site additions are automatically reflected across the network. High availability is supported through redundant connections and fault-tolerant design. Overlapping IP ranges are handled effectively because each spoke can operate independently while the hub controls connectivity. The architecture allows scalable growth with minimal manual intervention, reducing operational complexity. Centralized logging, monitoring, and policy enforcement are simplified because the hub provides a single point of control. Network traffic between cloud and on-premises environments is optimized for latency and efficiency, supporting high-performance operations across distributed sites. This approach is particularly suitable for logistics organizations that need to maintain predictable connectivity, enforce security policies consistently, and scale globally without redesigning the network for each new site.
Considering the requirements for centralized routing, high availability, overlapping IP support, and scalable management, a hub-and-spoke architecture with Network Connectivity Center is the most appropriate solution for a logistics company connecting multiple VPCs and datacenters.
Question 65
A media streaming company needs a global load balancing solution for web services that provides low latency for users worldwide. They want a single public IP address, SSL termination at the edge, health-based routing to the nearest backend, and automatic scaling during traffic spikes. Which solution meets these requirements?
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
Answer: B) Global External HTTP(S) Load Balancer
Explanation
Media streaming platforms require global traffic distribution to ensure users experience low latency and uninterrupted service. The system must intelligently route traffic to the nearest healthy backend, terminate SSL at the edge to offload decryption from backend servers, and scale automatically during spikes in traffic. Selecting the appropriate load balancing solution involves understanding global reach, protocol termination capabilities, dynamic routing, autoscaling features, and failover mechanisms.
The first option is a regional load balancer. While it provides HTTP(S) balancing within a single region, it does not support routing users to the closest backend globally. Users connecting from distant locations may experience high latency, and failover across regions is not automatic. SSL termination occurs only within the region, limiting offload benefits. Scaling is confined to the region, making it unsuitable for handling global traffic spikes. Therefore, regional HTTP(S) load balancing cannot satisfy the requirement for a unified global IP address or worldwide low-latency access.
The third option, TCP Proxy Load Balancing, provides global TCP-level routing. While it can route traffic to the closest healthy TCP backend, it lacks HTTP(S) layer features such as SSL termination, content-based routing, and header-based decisions. Media streaming applications rely on HTTP(S) protocols and require edge SSL termination for efficient performance. TCP-level load balancing offloads neither encryption nor application-layer optimization, increasing backend workload and latency. It is partially functional but does not fulfill all requirements for a web-based media service.
The fourth option, internal HTTP(S) load balancing, is designed for private cloud traffic. It does not expose a public IP address for users and cannot route external traffic globally. While useful for internal applications, it cannot serve geographically distributed streaming users or provide automatic global failover. Autoscaling and edge SSL termination are limited to internal traffic scenarios, making it unsuitable for public-facing media services.
The second option, global external HTTP(S) load balancing, provides a single public IP accessible worldwide. It automatically routes traffic to the closest healthy backend, reducing latency for users everywhere. SSL termination occurs at the edge, offloading encryption/decryption from backend servers, and improving performance. Autoscaling adjusts backend capacity dynamically to handle spikes in traffic, ensuring consistent quality during peak demand. Multi-region failover ensures high availability, automatically redirecting traffic to other healthy regions if a regional backend becomes unavailable. Centralized monitoring and logging provide operational visibility, enabling rapid troubleshooting and performance optimization. This solution meets all requirements for low-latency, globally distributed web services and ensures efficient delivery of media content to users worldwide.
Given the need for a single IP address, edge SSL termination, nearest-backend routing, and automatic scaling during global traffic surges, global external HTTP(S) load balancing is the most suitable solution for media streaming platforms.
Question 66
A healthcare organization wants internal teams to access multiple managed Google Cloud APIs securely, without exposing traffic 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 with firewall rules
D) Configure individual VPN tunnels for each API
Answer: B) Private Service Connect endpoints
Explanation
Healthcare organizations must ensure private, secure access to cloud-managed APIs due to regulatory and compliance requirements. Access must remain internal to the cloud network, avoid exposure to the public internet, and enable centralized governance for auditing and policy enforcement. Multiple service producers may exist, requiring scalable solutions that simplify operations while maintaining strict access control. Evaluating options involves analyzing connectivity, operational complexity, scalability, and security.
The first option uses VPC Peering to connect internal networks with managed services. While this enables private communication, it does not scale efficiently for multiple services because each service requires a separate peering connection. Overlapping IP ranges are unsupported, and central access management is limited because each peering must be configured independently. Operational complexity increases as additional services are introduced, making this approach unsuitable for large healthcare environments.
The third option exposes services using public IPs and restricts access using firewall rules. While this limits traffic to authorized sources, the endpoints remain publicly reachable, creating potential security and compliance risks. Firewall rules do not provide identity-aware access or centralized policy enforcement. Multiple service producers increase administrative overhead because each public endpoint requires individual firewall configuration. This approach does not fully isolate sensitive healthcare traffic and cannot meet strict regulatory requirements.
The fourth option uses VPN tunnels for each API. Although tunnels provide encrypted transport, managing multiple tunnels for multiple services is operationally intensive. Each tunnel must be individually configured and maintained, and route propagation is manual. Scaling to support multiple services or global teams becomes cumbersome, and central access governance is difficult because each tunnel operates independently. This approach introduces unnecessary complexity while still achieving private access.
The second option, Private Service Connect, allows internal workloads to access managed services privately using internal IP addresses. This ensures that traffic never traverses the public internet, maintaining compliance and security. Multiple service producers can be accessed through a single framework, reducing operational overhead. Subnet-level control provides centralized access management, ensuring that policies are enforced consistently across all teams. The solution supports multi-region deployments, allowing seamless expansion without redesign. Centralized monitoring and logging further simplify auditing and governance. Private Service Connect is designed to provide scalable, secure, and efficient private access to managed services, meeting both operational and regulatory requirements.
Considering the requirements for private IP access, centralized access control, multi-service support, and operational simplicity, Private Service Connect is the optimal solution for securely consuming managed APIs in healthcare environments.
Question 67
A global financial organization wants to connect multiple on-premises datacenters to Google Cloud with high availability, dynamic routing, and automatic failover. They require high throughput for large transaction datasets 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) Static routes configured between datacenters and Google Clou
Answer: C) Cloud Interconnect Partner with Cloud Router
Explanation
Financial institutions require highly reliable connectivity between on-premises datacenters and cloud environments due to strict requirements for performance, security, and resilience. Large volumes of transaction data must flow seamlessly, making high throughput essential. Centralized management and automated route propagation reduce operational overhead while ensuring route consistency across multiple sites. Evaluating connectivity options involves considering throughput, redundancy, dynamic routing, failover capabilities, and ease of management.
The first approach relies on individually configured VPN tunnels to provide secure connections. While VPNs ensure encrypted transport, they are limited in bandwidth, which may not meet the high throughput requirements of a financial organization handling large transaction datasets. Redundancy can be achieved by creating multiple tunnels, but configuration remains manual and complex. Dynamic routing is possible when paired with a routing engine, but scaling to multiple datacenters and handling automated failover is cumbersome. VPN-based solutions introduce higher latency compared to dedicated links, making them suboptimal for performance-sensitive financial workloads.
The second approach uses a dedicated interconnect link without a routing engine. Dedicated interconnects provide high bandwidth and low latency, which is beneficial for transferring large datasets. However, without dynamic routing, administrators must manually configure and maintain routes whenever network changes occur. Failover is limited because routing does not adapt automatically to link or device failures. Centralized route management is not supported, resulting in operational overhead and potential misconfigurations, especially when multiple datacenters are involved. While throughput and latency requirements are met, operational complexity and resilience are inadequate for enterprise-scale financial environments.
The fourth approach relies solely on static routes to manage connectivity. Administrators must manually update routes across all datacenters and cloud networks whenever subnets change or new datacenters are added. Static routing does not support dynamic failover or automatic route propagation. Managing multiple datacenters in this way is error-prone and labor-intensive. It is also inflexible, meaning route optimization and recovery from failures are not automated. Although technically secure and functional, this approach cannot handle the scale, dynamic routing, and resilience required for financial workloads.
The third approach combines interconnect connectivity with a routing engine. Partner-provided interconnect links ensure high throughput and low latency, while the routing engine provides dynamic route advertisement between on-premises datacenters and the cloud. Redundant links and high-availability configurations provide automatic failover in case of link or gateway failure, ensuring uninterrupted data flow. Centralized route management reduces administrative overhead, as routes propagate automatically to all connected sites. Adding new datacenters requires minimal configuration, and the dynamic routing engine adapts to network changes automatically. This architecture provides secure, high-performance connectivity while supporting enterprise-level operational efficiency, resilience, and scalability.
Considering the requirements for high availability, dynamic routing, automatic failover, high throughput, and centralized management, the combination of interconnect with a dynamic routing engine provides the most robust solution for financial organizations connecting multiple datacenters to Google Cloud.
Question 68
A gaming company needs to provide low-latency access to multiplayer servers for players worldwide. They require traffic to be routed automatically to the closest healthy backend, SSL termination at the edge, and the ability to scale automatically during spikes in demand. 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
Answer: B) Global External HTTP(S) Load Balancer
Explanation
Real-time multiplayer gaming requires a global load balancing solution that reduces latency, ensures high availability, and provides consistent performance for players located in diverse geographic regions. Players need traffic routed intelligently to the closest backend to minimize lag, and edge SSL termination improves performance by offloading encryption from backend servers. Autoscaling is essential to handle unpredictable spikes in traffic. Evaluating load balancing options involves understanding geographic reach, protocol support, routing intelligence, failover capabilities, and application-layer features.
The first option operates regionally, balancing traffic only within a single geographic location. Users connecting from distant regions may experience higher latency because traffic cannot be routed automatically to the nearest backend outside that region. Failover across regions is not supported, and SSL termination occurs only locally, reducing offload efficiency. Scaling is limited to the region and does not address global traffic surges. Therefore, this solution is inadequate for a worldwide gaming environment.
The third option, TCP Proxy Load Balancing, supports global routing at the TCP layer. While it can direct traffic to the closest healthy backend, it does not provide HTTP(S)-specific features such as SSL termination at the edge, header-based routing, or caching. Multiplayer games using web protocols rely on HTTP(S), making TCP-level load balancing insufficient for performance optimization and efficient encryption offload. Backend servers would need to handle SSL decryption, increasing processing load and potentially introducing latency.
The fourth option, internal HTTP(S) load balancing, is designed for traffic within a private cloud environment. It cannot serve public users worldwide and does not provide global ingress points. Autoscaling and SSL termination are confined to internal traffic. For gaming applications with geographically distributed players, this solution cannot deliver low-latency access or global routing intelligence.
The second option, global external HTTP(S) load balancing, provides a single global IP address for users worldwide. Traffic is automatically routed to the closest healthy backend, minimizing latency. SSL termination occurs at the edge, improving performance and simplifying certificate management. Autoscaling dynamically adjusts backend capacity during traffic spikes, ensuring consistent gameplay experience. Multi-region failover ensures high availability, automatically redirecting traffic if a regional backend becomes unavailable. Centralized monitoring and logging provide visibility into traffic and backend health, enabling rapid troubleshooting. This solution integrates global routing intelligence, application-layer optimization, and autoscaling, making it ideal for latency-sensitive multiplayer gaming environments.
Given the need for low-latency global access, edge SSL termination, autoscaling, and health-based routing, global external HTTP(S) load balancing is the optimal choice for worldwide multiplayer gaming services.
Question 69
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 without exposing services to the public internet. Which approach is most suitable?
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 API
Answer: B) Private Service Connect endpoints
Explanation
Healthcare organizations handle sensitive patient data, making private, secure access to managed cloud APIs critical. Access must remain internal, avoiding exposure to the public internet. Centralized governance and policy enforcement simplify compliance and auditing. Multiple service producers require scalable solutions that minimize operational complexity while ensuring secure, private connectivity. Assessing options involves evaluating scalability, operational efficiency, private connectivity, and centralized access control.
The first option, VPC Peering, enables private network communication. While functional for connecting a network to a managed service, it does not scale well for multiple services. Each service requires a separate peering connection, increasing configuration overhead. Overlapping IP ranges are not supported, limiting flexibility for multiple independent teams. Centralized access control is limited because policies must be applied individually to each peering connection. Operational complexity increases as the number of services grows, making this approach impractical for a large healthcare organization.
The third option exposes APIs through public IPs and relies on firewall rules for access control. While firewall rules can restrict traffic, services are still publicly reachable, increasing the potential attack surface. Identity-aware access cannot be enforced centrally, and multiple service producers require separate firewall configurations, adding administrative burden. Public exposure conflicts with compliance and privacy requirements for healthcare data, making this approach unsuitable.
The fourth option uses individual VPN tunnels for each API. VPNs ensure private transport but introduce significant operational overhead. Each tunnel must be separately configured, maintained, and monitored. Route propagation is manual, and scaling to multiple services or global teams is cumbersome. Centralized governance is difficult because each VPN is independent. This method complicates management without providing significant advantages over native private connectivity options.
The second option, Private Service Connect, provides private IP access to multiple managed services without exposing them to the public internet. It allows a single, centralized access framework for multiple service producers, reducing operational complexity. Subnet-level access control and centralized policy enforcement simplify governance and compliance. Multi-region support allows the organization to scale services without redesigning connectivity. Monitoring and logging are integrated, enabling auditing and operational oversight. Private Service Connect ensures private, secure, and manageable access to cloud-managed services while meeting the regulatory and operational requirements of healthcare organizations. It provides a native, scalable, and secure mechanism for consuming multiple managed APIs efficiently and consistently.
Considering private connectivity, centralized management, multi-service support, and regulatory compliance, Private Service Connect is the optimal solution for healthcare organizations accessing managed Google Cloud APIs.
Question 70
A global e-commerce company wants to connect multiple on-premises datacenters to Google Cloud with high throughput, automatic route propagation, redundancy, and minimal operational overhead. Which solution best meets these requirements?
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 datacenter
Answer: C) Cloud Interconnect Partner with Cloud Router
Explanation
Global e-commerce platforms often require reliable, high-throughput connectivity between multiple datacenters and the cloud to support real-time transaction processing, inventory management, and customer-facing applications. High availability, dynamic route propagation, and operational efficiency are critical because manual management of routes or tunnels across multiple sites can quickly become unmanageable. Evaluating the available connectivity solutions involves analyzing bandwidth, redundancy, automation, routing flexibility, and operational overhead.
The first approach relies on individually configured VPN tunnels for each datacenter. While VPNs provide secure encrypted connections, they are bandwidth-limited compared to dedicated links. Redundancy requires multiple tunnels per site, and route propagation must be manually managed or paired with a routing engine, adding complexity. Scaling to numerous datacenters increases administrative overhead exponentially. VPNs are also subject to higher latency and are less predictable for performance-sensitive applications. While secure, this solution does not meet the high throughput and low operational overhead requirements.
The second approach uses a dedicated interconnect link without a routing engine. Dedicated interconnect provides high bandwidth and predictable low latency, which is advantageous for e-commerce workloads. However, without a dynamic routing engine, any changes in on-premises networks or cloud subnets require manual route configuration. Failover is not automatic, limiting redundancy and resilience. Managing multiple datacenters without dynamic route propagation introduces operational complexity, particularly as the number of sites increases. While throughput requirements are satisfied, the solution lacks flexibility and automation.
The fourth approach relies on manually configured static routes at each datacenter. Static routes do not scale effectively in multi-datacenter environments. Any network change, such as adding new subnets or datacenters, requires manual updates on every device, increasing the risk of misconfiguration. Failover is not automatic, and bandwidth allocation cannot be dynamically managed. Operational overhead becomes significant with multiple sites, making this solution impractical for a global e-commerce organization requiring high reliability and scalable connectivity.
The third approach combines partner-provided interconnect connectivity with a routing engine. This solution provides high throughput and predictable low latency for large data transfers. Dynamic route propagation ensures that any changes in network topology are automatically communicated to all connected sites, reducing administrative effort. Redundant connections and high-availability configurations allow automatic failover in case of link or device failure. Operational overhead is minimized because administrators do not need to manually manage routes for every datacenter. Adding new sites requires minimal configuration, and the routing engine ensures consistency across the entire network fabric. This approach satisfies all critical requirements: high bandwidth, redundancy, automated route propagation, and operational efficiency, making it ideal for a global e-commerce organization with multiple datacenters.
Considering the requirements for high throughput, dynamic routing, redundancy, and minimal operational overhead, using interconnect connectivity with a routing engine provides the most reliable and scalable solution for connecting multiple on-premises datacenters to Google Cloud.
Question 71
A media company wants to deliver video streaming globally with low latency. They require a single public IP address for users worldwide, automatic routing to the closest healthy backend, SSL termination at the edge, and automatic scaling during traffic spikes. Which load balancing solution is best suited for this use case?
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
Answer: B
Explanation
Media streaming platforms serving global audiences require load balancing solutions that minimize latency, provide high availability, and ensure consistent user experience. Users must connect to the nearest backend automatically, SSL termination at the edge is essential to offload encryption from backend servers, and autoscaling handles traffic spikes to maintain uninterrupted service. Selecting the correct load balancer requires understanding global reach, application-layer support, failover, autoscaling, and traffic optimization.
The first option operates regionally. Regional HTTP(S) load balancing distributes traffic only within a single geographic region. Users connecting from distant locations may experience high latency due to suboptimal routing. Failover across regions is not automated, SSL termination occurs only within that region, and autoscaling is confined regionally. This approach cannot provide a single global IP for worldwide access, nor can it guarantee low-latency performance for a globally distributed audience. While functional for local traffic, it does not satisfy global streaming requirements.
The third option, TCP Proxy Load Balancing, provides global TCP-level routing. While capable of directing traffic to the nearest healthy TCP backend, it lacks HTTP(S)-specific features. SSL termination cannot occur at the edge, and application-layer optimizations such as caching or header-based routing are unavailable. For web-based streaming applications, this results in increased backend workload and higher latency. TCP Proxy Load Balancing is therefore only partially suitable, as it does not meet all streaming requirements.
The fourth option, internal HTTP(S) load balancing, is intended for private, internal cloud traffic. It does not expose a public IP for users and cannot route traffic globally. Autoscaling and SSL termination are limited to internal environments, making it unsuitable for public-facing media streaming applications requiring low-latency global delivery.
The second option, global external HTTP(S) load balancing, provides a single public IP accessible worldwide. Traffic is automatically routed to the closest healthy backend, minimizing latency and ensuring optimal performance. SSL termination occurs at the edge, reducing load on backend servers. Autoscaling adjusts backend capacity dynamically in response to traffic spikes, ensuring uninterrupted service. Multi-region failover ensures high availability, automatically redirecting requests if a regional backend is unavailable. Centralized monitoring and logging provide operational visibility, enabling quick troubleshooting and performance optimization. The global edge network ensures efficient content delivery and predictable latency for users anywhere in the world. This solution fully satisfies all requirements: low-latency global access, edge SSL termination, automatic scaling, and high availability for streaming workloads.
Given the need for a single global IP, automatic nearest-backend routing, SSL termination at the edge, and autoscaling during traffic surges, global external HTTP(S) load balancing is the most appropriate solution for worldwide video streaming delivery.l
Question 72
A healthcare organization wants its internal teams to securely access multiple managed Google Cloud APIs without exposing them to the public internet. They require private IP connectivity, centralized access management, and support for multiple service producers. Which solution best meets these requirements?
A) VPC Peering with each service
B) Private Service Connect endpoints
C) Assign external IPs and restrict access with firewall rules
D) Configure individual VPN tunnels for each API
Answer: B) Private Service Connect endpoints
Explanation
Healthcare organizations handle sensitive patient data, requiring private, secure access to managed cloud APIs. Access must remain internal, avoid public internet exposure, and provide centralized governance for compliance and auditing. Multiple service producers may exist, demanding a scalable, operationally efficient solution that supports multiple services simultaneously. Evaluating options requires assessing private connectivity, access control, scalability, and operational complexity.
The first option uses VPC Peering to connect internal networks to each managed service. While VPC Peering ensures private connectivity, it does not scale efficiently across multiple services. Each service requires a separate peering connection, creating significant administrative overhead. Overlapping IP ranges are not supported, limiting flexibility for multiple teams. Centralized access control is limited because policies must be applied individually for each peering connection. As the number of services grows, management complexity increases significantly, making this approach impractical for large healthcare organizations.
The third option exposes APIs with external IPs while restricting access through firewall rules. Although firewall rules can limit access to authorized users, endpoints remain publicly reachable, increasing potential attack surfaces. Identity-aware access cannot be centrally enforced, and supporting multiple service producers adds administrative complexity. This method does not provide fully private connectivity and does not meet compliance or privacy requirements for healthcare workloads.
The fourth option creates VPN tunnels for each API. While VPNs provide encrypted transport, managing multiple tunnels is operationally intensive. Each tunnel requires individual configuration and ongoing maintenance. Route propagation is manual, and scaling to support multiple services or distributed teams is cumbersome. Centralized governance is difficult because each VPN is managed independently. This approach increases complexity without significant advantages over native private access methods.
The second option, Private Service Connect, provides private IP access to managed services without exposing them 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 all teams. Multi-region support enables scalable service expansion without redesign. Logging and monitoring are integrated, simplifying auditing and compliance. This solution provides private, secure, and operationally efficient access to cloud-managed services, aligning perfectly with healthcare requirements for privacy, security, and scalability.
Considering private connectivity, centralized management, multi-service support, and regulatory compliance, Private Service Connect is the optimal solution for healthcare organizations accessing managed Google Cloud APIs securely.
Question 73
A multinational retail company wants to connect its regional datacenters and Google Cloud environments with centralized management, high availability, support for overlapping IP ranges, and scalable routing for future expansions. Which solution is most appropriate?
A) VPC Peering between all VPCs and individual VPNs to datacenters
B) Shared VPC across all projects with static routes
C) Network Connectivity Center hub-and-spoke architecture
D) Cloud VPN Classic with manual route configuration
Correct Answer: C
Explanation
Large retail organizations often operate multiple datacenters and cloud VPCs across different regions, requiring a highly scalable, centralized network architecture. Key requirements include centralized route management, high availability, support for overlapping IP ranges, and ease of scaling as new locations or cloud projects are added. The chosen solution must optimize latency between sites, reduce administrative overhead, and provide operational simplicity for network engineers.
The first approach involves connecting each VPC directly to all other VPCs using pairwise connections and establishing individual VPNs to datacenters. This method is technically feasible but does not scale well. The number of connections increases exponentially as new VPCs or datacenters are added, making the network highly complex and error-prone. Operational overhead becomes significant, as every network change requires updates to multiple peering relationships or VPN configurations. VPC Peering cannot support overlapping IP ranges, requiring renumbering or NAT workarounds. While secure, the architecture is cumbersome and lacks centralized visibility, making it inefficient for global retail operations.
The second approach leverages Shared VPC with static routes. Shared VPC centralizes certain aspects of network management, allowing multiple projects to attach to a common network. While it offers central control, static routes must be manually maintained. Adding new datacenters or subnets requires updating all relevant routes, increasing the likelihood of errors. Shared VPC does not inherently support overlapping IP ranges, and traffic between different regions may not be optimized for latency, as static routes are rigid. While operationally simpler than full mesh peering, it is still not ideal for multi-region, multi-datacenter expansion.
The fourth approach, manually configuring VPN tunnels with static routes, provides encrypted connectivity but requires high operational effort. Each new datacenter or network change requires manual configuration of VPNs and routes at both ends. Failover is limited unless multiple redundant tunnels are manually configured. Overlapping IP ranges require complex NAT configurations. This solution introduces high administrative overhead and is prone to misconfiguration in large-scale environments.
The third approach, a hub-and-spoke design using Network Connectivity Center, centralizes network connectivity and routing. Each VPC and datacenter connects to a central hub, which handles route propagation, policy enforcement, and failover. Dynamic routing reduces manual management, as updates propagate automatically across the network. Overlapping IP ranges are supported by isolating spokes while enabling controlled communication through the hub. Redundant connections provide high availability, ensuring continuity in case of link or site failure. Adding new datacenters or VPCs involves simply attaching them to the hub, without redesigning the entire network. Centralized monitoring, logging, and policy enforcement simplify operations and improve security governance. Latency is minimized because traffic can traverse optimal paths, and the architecture scales easily as the organization grows.
Given the requirements of centralized management, high availability, overlapping IP support, and scalable routing, Network Connectivity Center’s hub-and-spoke architecture is the optimal solution for connecting multiple datacenters and Google Cloud VPCs in a multinational retail environment.
Question 74
A global gaming company wants to provide low-latency access to multiplayer game servers. They require a single IP address for players worldwide, SSL termination at the edge, health-based routing to the nearest server, and automatic scaling to handle spikes in traffic. Which load balancing solution is best suited for this scenario?
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
Multiplayer gaming platforms need globally distributed, highly responsive infrastructure to provide a seamless player experience. Requirements include low latency, global availability, SSL termination at the edge to offload encryption tasks, health-based routing to the nearest server, and the ability to scale automatically to accommodate traffic spikes. Evaluating available load balancing solutions requires understanding their geographic reach, protocol support, routing intelligence, failover mechanisms, and ability to handle high traffic volumes.
The first approach, regional external HTTP(S) load balancing, distributes traffic only within a single region. Users connecting from other parts of the world may experience high latency, as traffic cannot be routed to the nearest backend in a different region. Failover across regions is not automatic. SSL termination occurs only in the region where the load balancer resides, which reduces offloading benefits. Autoscaling is limited to the region, preventing rapid adaptation to global traffic spikes. While suitable for regional applications, this solution cannot meet the global performance and scalability requirements for multiplayer gaming.
The third approach, TCP Proxy Load Balancing, provides global TCP-level routing. While it can direct traffic to the nearest healthy TCP backend, it lacks application-layer HTTP(S) features such as SSL termination, caching, and content-based routing. Multiplayer games using HTTP(S) protocols would require backend servers to handle encryption and routing tasks, increasing latency and load. Although functional, it does not provide the edge-level optimizations necessary for low-latency global gameplay.
The fourth approach, internal HTTP(S) load balancing, is intended for private traffic within a cloud environment. It does not provide a public IP accessible globally. SSL termination and autoscaling are confined to internal traffic, making it unsuitable for public-facing gaming applications with distributed players. This solution cannot meet the requirement of single IP global access or health-based routing for users worldwide.
The second approach, global external HTTP(S) load balancing, provides a single public IP address that players worldwide can use to connect. Traffic is automatically routed to the nearest healthy backend, minimizing latency and optimizing performance. SSL termination occurs at the edge, reducing load on backend servers and simplifying certificate management. Autoscaling dynamically adjusts backend capacity to handle spikes in traffic, ensuring uninterrupted gameplay. Multi-region failover ensures high availability; if a regional server becomes unavailable, requests are automatically redirected to the next closest healthy region. Centralized monitoring and logging provide operational visibility for managing performance and troubleshooting issues. This solution fully satisfies the requirements of low-latency global access, edge SSL termination, health-based routing, and automatic scaling for high-traffic multiplayer environments.
Given the need for global reach, low latency, edge SSL termination, health-based routing, and autoscaling, global external HTTP(S) load balancing is the most appropriate choice for multiplayer gaming platforms.
Question 75
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 optimal?
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 stringent privacy and regulatory requirements, making private, secure access to managed cloud APIs critical. The solution must ensure traffic does not traverse the public internet, enable centralized governance for auditing and policy enforcement, and support multiple service producers to simplify network operations. Evaluating the options involves analyzing scalability, security, operational overhead, and centralized management.
The first approach, VPC Peering with each service, allows private connectivity between networks. However, it does not scale efficiently for multiple services, as each managed service requires a separate peering connection. Overlapping IP ranges are not supported, and centralized access management is limited, requiring individual configuration for each peering connection. As the number of services grows, operational complexity increases significantly, making this unsuitable for large healthcare organizations with many managed APIs.
The third approach exposes APIs through public IPs while restricting access with firewall rules. While firewall rules limit traffic to authorized users, services remain publicly reachable, increasing the potential attack surface. Identity-aware access cannot be enforced centrally. Managing multiple service producers further increases administrative overhead, making this method operationally complex and non-compliant with strict privacy requirements.
The fourth approach involves creating VPN tunnels for each API. Although VPNs provide encrypted transport, managing multiple tunnels is labor-intensive. Each tunnel requires individual configuration, monitoring, and maintenance. Route propagation is manual, and scaling to support multiple services or teams is cumbersome. Centralized governance is difficult because each VPN operates independently. This method introduces unnecessary complexity without providing native private connectivity.
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 centralized framework, reducing operational overhead. Centralized access control ensures consistent policy enforcement across teams. Multi-region support allows seamless expansion without network redesign. Logging and monitoring are integrated, simplifying compliance auditing. Private Service Connect enables secure, scalable, and operationally efficient access to cloud-managed services, meeting the regulatory, privacy, and operational requirements of healthcare organizations.
Considering private IP connectivity, centralized management, multi-service support, and compliance needs, Private Service Connect is the optimal solution for securely accessing multiple managed APIs in healthcare environments.