Google Associate Cloud Engineer Exam Dumps and Practice Test Questions Set 5 Q  81- 100

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Question 81

You need to deploy a highly available, stateless web application that must scale automatically based on HTTP request volume. Which Google Cloud service is most appropriate?

A) Compute Engine with managed instance groups
B) App Engine Standard Environment
C) Cloud Run
D) Kubernetes Engine (GKE)

Answer C) Cloud Run

Explanation

A) Compute Engine with managed instance groups provides horizontal scaling by adding or removing VM instances based on metrics like CPU usage. While this approach can achieve high availability, it introduces significant operational overhead. Each VM instance requires manual OS management, runtime installation, and patching. Scaling is metric-based and not directly tied to HTTP request volume unless custom load metrics are configured. Rolling updates are possible but require careful orchestration to prevent downtime, and managing stateless containers on VMs is more complex than using a serverless platform. For a stateless web application that needs fully automated HTTP request-based scaling, Compute Engine adds unnecessary complexity and operational risk.

B) App Engine Standard Environment is a fully managed, serverless platform that automatically scales based on request volume. It abstracts infrastructure management and allows developers to focus on code. However, it has runtime restrictions and predefined environments, which can limit flexibility for custom containerized applications or non-standard dependencies. While it handles scaling and routing efficiently, the lack of container flexibility may make App Engine less ideal for complex modern applications that rely on containerization.

C) Cloud Run is a fully managed, serverless container platform optimized for stateless HTTP workloads. It automatically scales based on the number of incoming requests, including scaling down to zero when no traffic is present, minimizing cost. Cloud Run supports containerized applications, custom runtimes, and stateless services. Deployment is simplified, and it integrates with Cloud IAM for secure access and with Cloud Monitoring for observability. Rolling updates can be performed seamlessly with traffic splitting, ensuring zero downtime. This makes Cloud Run the most suitable service for highly available, stateless web applications requiring automatic scaling tied directly to HTTP traffic volume.

D) Kubernetes Engine (GKE) provides powerful container orchestration, including horizontal pod autoscaling and rolling updates. While highly flexible and robust, GKE introduces operational complexity for stateless applications that do not require advanced multi-service orchestration. Managing clusters, nodes, and networking adds overhead compared to fully serverless platforms like Cloud Run. GKE is better suited for multi-container or microservice architectures with complex dependencies rather than simple stateless web applications.

The correct solution is Cloud Run because it provides serverless, fully managed scaling based directly on HTTP request volume. It reduces operational complexity, supports containerized workloads, ensures high availability, and allows zero-downtime updates. Cloud Run balances simplicity, flexibility, security, and cost efficiency, making it ideal for stateless web applications in production environments. By using Cloud Run, organizations can focus on development rather than infrastructure management, improve deployment speed, and maintain resilient and scalable applications.

Question 82

You need to implement a real-time streaming analytics pipeline to process IoT sensor data, transform it, and store results for business reporting. Which combination of services is most appropriate?

A) Cloud Functions and Cloud Storage
B) Cloud Pub/Sub, Cloud Dataflow, and BigQuery
C) Cloud Run and Cloud SQL
D) Compute Engine and Cloud Bigtable

Answer B) Cloud Pub/Sub, Cloud Dataflow, and BigQuery

Explanation

A) Cloud Functions combined with Cloud Storage is suitable for event-driven workloads triggered by file uploads. While serverless and scalable, it is not designed for high-throughput, real-time streaming from multiple IoT sources. Complex transformations, aggregations, and windowing are difficult to implement with Cloud Functions. Additionally, Cloud Functions may experience cold starts, adding latency, and cannot natively handle continuous ingestion from multiple distributed IoT devices at scale.

B) Cloud Pub/Sub, Cloud Dataflow, and BigQuery provide a fully managed, serverless streaming analytics solution. Pub/Sub ensures reliable, scalable ingestion of events with at-least-once delivery guarantees. Dataflow enables complex transformations, filtering, enrichment, aggregation, and windowing in real time. BigQuery serves as the analytical data warehouse to store and query processed data. This combination supports near real-time analytics, fault tolerance, automatic scaling, and high-throughput ingestion, making it ideal for enterprise IoT scenarios. It also integrates with monitoring, logging, and IAM for operational visibility, security, and compliance. Cloud-native features like automated retries, checkpointing, and stateful processing make this architecture resilient and robust for mission-critical IoT data pipelines.

C) Cloud Run and Cloud SQL provide serverless container execution and relational storage. While Cloud Run scales automatically, Cloud SQL is not optimized for high-throughput streaming analytics. Using this combination for IoT streaming may introduce latency, bottlenecks, and operational complexity. It is suitable for small-scale or batch processing, but it does not support complex real-time streaming requirements effectively.

D) Compute Engine and Cloud Bigtable offer flexibility and high throughput, but Compute Engine requires manual orchestration, scaling, and error handling. Cloud Bigtable is optimized for NoSQL workloads and lacks analytical querying features for business reporting. Maintaining this architecture would require significant operational effort to ensure fault tolerance, scalability, and real-time processing.

The correct solution is Cloud Pub/Sub, Cloud Dataflow, and BigQuery because it provides a fully managed, scalable, and fault-tolerant architecture for real-time streaming analytics. It ensures continuous data ingestion, transformation, and storage while reducing operational complexity. This combination aligns with cloud-native best practices for IoT data processing, providing enterprise-grade resilience, near real-time insights, and seamless integration with monitoring and security services.

Question 83

You need to provide a third-party contractor temporary access to a Cloud Storage bucket to upload files securely. Which method is most appropriate?

A) Share personal credentials
B) Create a service account with long-lived key
C) Use signed URLs
D) Grant Owner permissions

Answer C) Use signed URLs

Explanation

A) Sharing personal credentials is insecure and violates the principle of least privilege. It exposes all project resources to the contractor, increasing the risk of misuse. Auditing, revocation, and compliance become challenging, making this approach unsuitable for enterprise environments.

B) Creating a service account with a long-lived key provides programmatic access but is unsuitable for temporary access. Long-lived keys require secure storage, careful rotation, and monitoring. Sharing keys introduces risk, and manual management increases operational overhead. It is not aligned with best practices for temporary, least-privilege access.

C) Signed URLs provide temporary, secure access to specific objects in Cloud Storage without creating IAM accounts. Permissions and expiration times can be defined to ensure contractors can only perform intended actions for a limited time. Signed URLs are auditable, scalable, and operationally efficient, reducing management overhead while maintaining security. They support least-privilege principles and align with cloud-native security best practices. Contractors can upload files without gaining access to unrelated resources or requiring long-term credentials.

D) Granting Owner permissions is excessive and insecure. Owners have full control over all project resources, which is unnecessary for temporary file uploads. This approach increases operational risk and violates security best practices.

The correct solution is signed URLs because they provide temporary, auditable, and secure access, reduce operational complexity, and align with enterprise cloud security principles. This method ensures contractors can perform necessary tasks without exposing sensitive credentials or resources.

Question 84

You need to monitor Compute Engine instances for CPU, memory, and disk usage and alert your operations team when thresholds are exceeded. Which service is most appropriate?

A) Cloud Logging
B) Cloud Monitoring with alerting policies
C) Cloud Trace
D) Cloud Storage notifications

Answer B) Cloud Monitoring with alerting policies

Explanation

A) Cloud Logging collects logs for auditing and troubleshooting. While valuable for historical analysis, it does not provide real-time monitoring of system-level metrics or automated threshold-based alerts. Building a monitoring solution using logs alone requires complex pipelines, adding latency and operational overhead.

B) Cloud Monitoring provides real-time metrics collection from Compute Engine instances, including CPU, memory, and disk usage. Alerting policies allow thresholds to be defined, and notifications can be sent via email, Slack, PagerDuty, or other channels. Dashboards provide visualization of trends, supporting proactive incident response, capacity planning, and operational efficiency. Cloud Monitoring integrates with IAM, logging, and other services for centralized observability, making it ideal for enterprise monitoring of production workloads. Automated alerts ensure operations teams can respond promptly to anomalies, maintain high availability, and reduce risk. It supports scaling, reliability, and performance analysis while minimizing downtime.

C) Cloud Trace monitors application latency and request performance. It is valuable for debugging and optimizing distributed applications but cannot monitor infrastructure-level metrics like CPU or disk usage, making it unsuitable for Compute Engine instance monitoring.

D) Cloud Storage notifications alert users about object changes in storage. They are unrelated to system metrics and cannot trigger alerts based on thresholds for Compute Engine instances.

The correct solution is Cloud Monitoring with alerting policies because it provides real-time metrics, automated notifications, dashboards, and operational insights. This enables proactive incident response, maintains high availability, and aligns with enterprise monitoring best practices.

Question 85

You need to design a disaster recovery solution for a mission-critical application that must remain available during a regional outage. Which architecture is most appropriate?

A) Single-region deployment with automated backups
B) Multi-region deployment with active-active instances
C) Single-region deployment with snapshots
D) Deploy all resources in a private VPC

Answer B) Multi-region deployment with active-active instances

Explanation

A) Single-region deployment with automated backups provides protection against accidental deletion or corruption but does not address regional failures. If the region becomes unavailable, downtime occurs until resources are restored elsewhere, which does not meet near-zero recovery time objectives (RTO) or recovery point objectives (RPO).

B) Multi-region deployment with active-active instances ensures continuous availability across multiple regions. Traffic is distributed using a global load balancer, and healthy instances in unaffected regions automatically handle requests during a regional failure. This architecture provides automated failover, high availability, fault tolerance, and scalability. Active-active deployments also support load balancing, operational continuity, and business resilience. They meet strict enterprise RTO and RPO requirements, ensuring near-zero downtime and operational continuity for mission-critical applications. This solution aligns with cloud-native disaster recovery best practices.

C) Single-region deployment with snapshots allows recovery from failure but requires manual restoration in another region, introducing downtime. Snapshots alone do not ensure high availability or automated failover for critical workloads.

D) Deploying resources in a private VPC enhances security but does not provide cross-region redundancy. Regional failure would render all resources unavailable, making this approach insufficient for disaster recovery.

The correct solution is multi-region deployment with active-active instances. It ensures redundancy, automated failover, near-zero downtime, and operational continuity, aligning with enterprise disaster recovery best practices for critical applications. This architecture provides resilience, scalability, and reliability for mission-critical workloads while meeting business continuity objectives.

Question 86

You need to deploy a containerized microservices application that requires automatic scaling, rolling updates, and secure inter-service communication. Which Google Cloud solution is most appropriate?

A) Compute Engine with managed instance groups
B) App Engine Standard Environment
C) Kubernetes Engine (GKE) with Istio
D) Cloud Run

Answer C) Kubernetes Engine (GKE) with Istio

Explanation

A) Compute Engine with managed instance groups provides scalable VM instances that can respond to load changes. While horizontal scaling is supported, deploying containerized microservices on VMs introduces operational complexity. Each service requires manual deployment, orchestration, network configuration, and secure communication setup. Rolling updates are not automated, and achieving zero-downtime deployment would require custom scripts and careful planning. Additionally, ensuring secure service-to-service communication would require firewall and networking configurations, which are difficult to maintain across multiple services. This approach is feasible but inefficient for microservices architectures.

B) App Engine Standard Environment is a fully managed serverless platform that abstracts infrastructure management and automatically scales based on HTTP requests. It is suitable for simple web applications or single services. However, it is limited in flexibility for multi-service containerized applications, as it does not support custom container orchestration or advanced service mesh capabilities. Rolling updates are possible via traffic splitting, but secure inter-service communication, advanced routing, and traffic policies are not supported at the same level as Kubernetes with Istio.

C) Kubernetes Engine (GKE) with Istio is the ideal solution for containerized microservices requiring automatic scaling, rolling updates, and secure inter-service communication. GKE provides fully managed Kubernetes orchestration, including horizontal pod autoscaling, self-healing, and automated rolling updates. Istio, as a service mesh, enables secure mTLS communication between services, fine-grained traffic management, retries, circuit breaking, and observability. Together, GKE and Istio simplify deployment, improve security, and provide enterprise-grade operational capabilities. This combination allows microservices to scale independently, perform zero-downtime updates, and communicate securely, minimizing operational risk and complexity.

D) Cloud Run is a fully managed serverless container platform that automatically scales stateless services based on HTTP traffic. While suitable for individual microservices, Cloud Run lacks native support for complex orchestration, multi-service deployment, and secure inter-service communication. Implementing these features across multiple Cloud Run services requires additional configuration and external solutions, making it less efficient than GKE with Istio for large-scale microservices architectures.

The correct solution is Kubernetes Engine with Istio because it provides advanced orchestration, automated scaling, rolling updates, secure communication, and operational visibility. This architecture aligns with best practices for deploying enterprise-grade microservices, reducing operational complexity, improving security, and ensuring resilience. GKE with Istio supports declarative deployment, traffic control, and robust monitoring, making it the ideal choice for mission-critical multi-service applications.

Question 87

You need to migrate an on-premises PostgreSQL database to Cloud SQL with minimal downtime while ensuring continuous replication. Which method should you choose?

A) Export to SQL dump and import
B) Use Database Migration Service (DMS) with continuous replication
C) Manual schema creation and data copy
D) Cloud Storage Transfer Service

Answer B) Use Database Migration Service (DMS) with continuous replication

Explanation

A) Exporting a PostgreSQL database to a SQL dump and importing it into Cloud SQL is a simple approach for small datasets or testing. However, this method introduces downtime because the source database must stop accepting writes during export to maintain consistency. Large datasets can take hours or even days to migrate, increasing downtime risk. Any transactions made after the export are not captured, making this unsuitable for production workloads requiring minimal disruption.

B) Database Migration Service (DMS) with continuous replication is designed for production database migrations with minimal downtime. DMS automates initial data migration, schema conversion, and continuous replication of ongoing changes. This ensures the Cloud SQL target remains synchronized with the source database while the application continues to operate. DMS provides monitoring, logging, error handling, and automated cutover support, reducing operational risk. Continuous replication ensures data consistency, allowing a seamless transition with near-zero downtime. This method is suitable for enterprise-grade migrations where uptime, data integrity, and operational efficiency are critical.

C) Manual schema creation and data copy is time-consuming, error-prone, and operationally complex. It requires scripts to copy data and keep it synchronized, which is impractical for minimal downtime scenarios. Manual intervention increases risk of inconsistencies and prolonged downtime, making it unsuitable for production migrations.

D) Cloud Storage Transfer Service is designed for moving files and objects between storage systems. It does not provide relational database migration, schema conversion, or continuous replication, making it inappropriate for database migration use cases.

The correct solution is DMS with continuous replication because it enables minimal downtime, continuous synchronization, automated schema migration, and operational reliability. This approach ensures production continuity, reduces risk, and supports enterprise-level migration best practices. Using DMS, organizations can migrate critical databases efficiently while maintaining operational stability and data integrity.

Question 88

You need to provide temporary secure access for a third-party contractor to upload files to a Cloud Storage bucket. Which approach is most appropriate?

A) Share personal credentials
B) Create a service account with long-lived keys
C) Use signed URLs
D) Grant Owner permissions

Answer C) Use signed URLs

Explanation

A) Sharing personal credentials is highly insecure and violates least-privilege principles. It exposes all project resources, increasing the risk of accidental or malicious misuse. Auditing, revocation, and monitoring are difficult, making this approach unsuitable for enterprise scenarios.

B) Creating a service account with long-lived keys provides programmatic access but is not suitable for temporary access. Long-lived keys require secure management, rotation, and monitoring. Sharing them increases the risk of compromise and introduces operational complexity. It does not align with cloud-native security best practices for temporary access.

C) Signed URLs provide temporary, secure access to specific objects in Cloud Storage without creating IAM accounts. Permissions and expiration times are configurable, ensuring contractors can perform only intended actions for a limited period. Signed URLs are auditable, scalable, and operationally efficient, reducing overhead while maintaining security. They support least-privilege principles and align with enterprise cloud security standards. Contractors can upload files without accessing unrelated resources, making this the most secure and efficient solution.

D) Granting Owner permissions is excessive and insecure. Owners have full control over all project resources, which is unnecessary for temporary uploads. This increases risk, violates least-privilege principles, and is unsuitable for third-party access.

The correct solution is signed URLs because they provide temporary, secure, auditable access, reduce operational overhead, and align with best practices. This approach ensures contractors can perform necessary tasks without compromising other resources or credentials.

Question 89

You need to monitor Compute Engine instances for CPU, memory, and disk usage and alert your operations team when thresholds are exceeded. Which service is most appropriate?

A) Cloud Logging
B) Cloud Monitoring with alerting policies
C) Cloud Trace
D) Cloud Storage notifications

Answer B) Cloud Monitoring with alerting policies

Explanation

A) Cloud Logging collects logs for troubleshooting and auditing. While valuable for historical analysis, it does not provide real-time system-level metrics or automated alerts. Using logs alone for monitoring requires complex pipelines, delays alerts, and increases operational overhead.

B) Cloud Monitoring collects real-time metrics from Compute Engine instances, including CPU utilization, memory usage, and disk I/O. Alerting policies allow thresholds to be defined, with notifications sent via email, Slack, PagerDuty, or other channels. Dashboards provide trend visualization, enabling proactive incident response, capacity planning, and operational efficiency. Integration with IAM and logging allows centralized observability. Cloud Monitoring ensures operations teams can detect anomalies promptly, maintain high availability, and optimize performance. It supports automated scaling, operational alerts, and trend analysis, making it an enterprise-grade monitoring solution.

C) Cloud Trace focuses on application-level latency and request performance. It is valuable for distributed application debugging but cannot monitor infrastructure-level metrics like CPU, memory, or disk usage, making it unsuitable for system monitoring.

D) Cloud Storage notifications alert users to object changes within storage buckets. They are unrelated to Compute Engine metrics and cannot provide threshold-based alerts.

The correct solution is Cloud Monitoring with alerting policies because it provides real-time metrics, automated notifications, dashboards, and operational insights. This allows proactive response, minimizes downtime, and ensures high availability for Compute Engine workloads, aligning with enterprise monitoring best practices.

Question 90

You need to design a disaster recovery plan for a mission-critical application that must remain available during a regional outage. Which architecture is most appropriate?

A) Single-region deployment with automated backups
B) Multi-region deployment with active-active instances
C) Single-region deployment with snapshots
D) Deploy all resources in a private VPC

Answer B) Multi-region deployment with active-active instances

Explanation

A) Single-region deployment with automated backups protects against accidental deletion or corruption but does not address regional failures. If the region fails, downtime occurs until resources are restored elsewhere, which does not meet near-zero recovery time objectives (RTO) or recovery point objectives (RPO).

B) Multi-region deployment with active-active instances ensures continuous availability across multiple regions. Traffic is distributed using a global load balancer, and healthy instances in unaffected regions automatically handle requests during a regional outage. This architecture provides automated failover, high availability, fault tolerance, and scalability. Active-active deployments meet enterprise RTO and RPO requirements, ensuring near-zero downtime and operational continuity. They support load balancing, resiliency, and operational efficiency, making them ideal for mission-critical applications. Cloud-native features such as health checks, global routing, and automated failover enhance resilience and reliability.

C) Single-region deployment with snapshots allows recovery but requires manual restoration in another region, introducing downtime. Snapshots alone do not provide high availability or automated failover for critical workloads.

D) Deploying resources in a private VPC improves security but does not provide cross-region redundancy. A regional failure would render all resources unavailable, making this approach insufficient for disaster recovery.

The correct solution is multi-region deployment with active-active instances because it ensures redundancy, automated failover, near-zero downtime, and operational continuity. This architecture aligns with enterprise disaster recovery best practices, ensuring resilience, high availability, and operational continuity for mission-critical workloads while meeting business continuity requirements.

Question 91

You need to deploy a multi-service containerized application that requires automatic scaling, rolling updates, and secure service-to-service communication across services. Which solution is most appropriate?

A) Compute Engine with managed instance groups
B) App Engine Standard Environment
C) Kubernetes Engine (GKE) with Istio
D) Cloud Run

Answer C) Kubernetes Engine (GKE) with Istio

Explanation

A) Compute Engine with managed instance groups provides the ability to horizontally scale virtual machine instances. While this allows scaling based on CPU or load metrics, it does not provide native container orchestration. Each service requires manual deployment, networking configuration, and load balancing. Rolling updates and zero-downtime deployments must be manually scripted, which increases operational complexity. Security between services also requires manual firewall rules or network policies. While technically feasible, this approach is not efficient for a modern multi-service containerized application.

B) App Engine Standard Environment is a fully managed, serverless platform that scales automatically. It abstracts infrastructure management and simplifies deployment. However, it is less flexible for complex multi-service containerized applications. Traffic splitting allows rolling updates, but secure inter-service communication, advanced routing, and service-to-service policies are limited. It is suitable for single-service web applications but not for complex multi-service microservice architectures requiring fine-grained control.

C) Kubernetes Engine (GKE) with Istio provides full container orchestration, automatic scaling, rolling updates, and secure service-to-service communication. GKE manages the lifecycle of containers, including deployment, scaling, and self-healing. Istio adds a service mesh layer that provides mutual TLS encryption between services, traffic routing, retries, fault tolerance, and observability. This combination ensures zero-downtime deployments, secure communication, and operational efficiency. It is ideal for enterprise-grade multi-service applications, allowing teams to manage microservices at scale while maintaining security and reliability. Advanced monitoring, logging, and policy enforcement are built-in, reducing operational risk and complexity.

D) Cloud Run is a fully managed, serverless platform for stateless containers. It automatically scales based on HTTP traffic and allows zero-downtime deployment for individual services. However, Cloud Run lacks native support for multi-service orchestration, secure inter-service communication, and traffic policies. Implementing these features across multiple Cloud Run services requires additional configuration or external tools, which increases complexity compared to GKE with Istio.

The correct solution is Kubernetes Engine with Istio because it provides automated orchestration, secure service communication, rolling updates, and enterprise-grade operational capabilities. This combination minimizes manual management, ensures resilience, enhances security, and aligns with best practices for containerized multi-service applications in production.

Question 92

You need to migrate a PostgreSQL database from on-premises to Cloud SQL with minimal downtime and continuous replication. Which approach should you choose?

A) Export to SQL dump and import
B) Database Migration Service (DMS) with continuous replication
C) Manual schema creation and data copy
D) Cloud Storage Transfer Service

Answer B) Database Migration Service (DMS) with continuous replication

Explanation

A) Exporting a PostgreSQL database to a SQL dump and importing it into Cloud SQL is a simple approach but introduces significant downtime. The source database must stop accepting writes to ensure consistency during export, which is unacceptable for production workloads. For large databases, the export and import process may take hours or days. Any transactions made after the export will not be captured, risking data inconsistency.

B) Database Migration Service (DMS) with continuous replication is designed for production database migrations with minimal downtime. It automates schema migration, initial data seeding, and real-time replication of ongoing changes. This ensures the Cloud SQL target remains synchronized while the source database continues to operate. DMS provides monitoring, logging, and error handling, reducing operational risk. Continuous replication captures ongoing transactions, allowing a seamless cutover with near-zero downtime. This solution is ideal for enterprise-grade migrations requiring uptime, data integrity, and operational reliability.

C) Manual schema creation and data copy is time-consuming and error-prone. Synchronizing ongoing changes requires custom scripts and monitoring, making it impractical for minimal downtime migrations. Operational complexity and risk of data inconsistencies are high.

D) Cloud Storage Transfer Service is designed for moving files between storage systems. It does not provide relational database migration, schema conversion, or continuous replication, making it unsuitable for PostgreSQL migration to Cloud SQL.

The correct solution is DMS with continuous replication because it enables minimal downtime, maintains data consistency, automates schema migration, and provides enterprise-grade operational reliability. It supports seamless transitions and ensures business continuity during migration.

Question 93

You need to provide temporary secure access for a contractor to upload files to a Cloud Storage bucket. Which method is most appropriate?

A) Share personal credentials
B) Create a service account with long-lived keys
C) Use signed URLs
D) Grant Owner permissions

Answer C) Use signed URLs

Explanation

A) Sharing personal credentials is highly insecure and violates the principle of least privilege. It exposes all project resources, increases risk, and complicates auditing, revocation, and monitoring. This method is unsuitable for enterprise security standards.

B) Creating a service account with long-lived keys provides programmatic access but is not ideal for temporary access. Long-lived keys must be securely stored, rotated, and monitored. Sharing these keys increases risk and operational overhead, making it inefficient and insecure for temporary tasks.

C) Signed URLs provide temporary, secure access to specific objects in Cloud Storage without creating IAM accounts. Permissions and expiration times can be defined, ensuring contractors can perform uploads without accessing other resources. Signed URLs are auditable, scalable, and operationally efficient. They enforce least-privilege access and align with cloud-native security best practices. Contractors can perform the required tasks safely and securely, with automatic expiration reducing the risk of unauthorized access.

D) Granting Owner permissions is excessive and insecure. Owners have full control over all project resources, which is unnecessary for temporary uploads. This approach increases risk and violates security principles.

The correct solution is signed URLs because they provide temporary, secure, auditable, and least-privilege access. This method balances security, operational efficiency, and usability for third-party collaboration, ensuring compliance with enterprise security policies.

Question 94

You need to monitor Compute Engine instances for CPU, memory, and disk usage and alert your operations team when thresholds are exceeded. Which service is most appropriate?

A) Cloud Logging
B) Cloud Monitoring with alerting policies
C) Cloud Trace
D) Cloud Storage notifications

Answer B) Cloud Monitoring with alerting policies

Explanation

A) Cloud Logging captures logs for auditing and troubleshooting but does not provide real-time system-level metrics or automated threshold-based alerts. Using logs for monitoring requires complex pipelines, adding latency and operational overhead, which makes it unsuitable for proactive incident response.

B) Cloud Monitoring provides real-time metrics collection from Compute Engine instances, including CPU utilization, memory usage, and disk I/O. Alerting policies enable threshold-based notifications, which can be sent via email, Slack, PagerDuty, or other channels. Dashboards visualize trends and anomalies, supporting proactive incident response, capacity planning, and operational efficiency. Integration with IAM, logging, and other services ensures centralized observability. Cloud Monitoring enables operations teams to detect anomalies promptly, maintain high availability, and optimize performance. It supports automated scaling, operational alerts, and trend analysis, making it an enterprise-grade monitoring solution.

C) Cloud Trace is focused on application latency and distributed request performance. It cannot monitor infrastructure-level metrics like CPU, memory, or disk usage, making it unsuitable for system monitoring.

D) Cloud Storage notifications alert users about object changes in storage buckets. They are unrelated to Compute Engine metrics and cannot trigger threshold-based operational alerts.

The correct solution is Cloud Monitoring with alerting policies because it provides real-time metrics, automated notifications, dashboards, and operational insights. This enables proactive incident response, minimizes downtime, and ensures high availability for Compute Engine workloads.

Question 95

You need to design a disaster recovery solution for a mission-critical application that must remain available during a regional outage. Which architecture is most appropriate?

A) Single-region deployment with automated backups
B) Multi-region deployment with active-active instances
C) Single-region deployment with snapshots
D) Deploy all resources in a private VPC

Answer B) Multi-region deployment with active-active instances

Explanation

A) Single-region deployment with automated backups protects against accidental deletion or corruption but does not provide resilience against regional outages. If the region fails, downtime occurs until resources are restored in another region, which does not meet near-zero recovery time objectives (RTO) or recovery point objectives (RPO).

B) Multi-region deployment with active-active instances ensures continuous availability across multiple regions. Traffic is distributed using a global load balancer, and healthy instances in unaffected regions automatically handle requests during a regional outage. This architecture provides automated failover, high availability, fault tolerance, and scalability. Active-active deployments meet enterprise RTO and RPO requirements, ensuring near-zero downtime and operational continuity. It supports load balancing, resiliency, and operational efficiency. Cloud-native features such as health checks, global routing, and automated failover enhance resilience and reliability. This approach is ideal for mission-critical applications that require high availability and operational continuity in production environments.

C) Single-region deployment with snapshots allows recovery but requires manual restoration in another region, introducing downtime. Snapshots alone do not provide high availability or automated failover.

D) Deploying resources in a private VPC enhances security but does not provide cross-region redundancy. A regional failure would render all resources unavailable, making this approach insufficient for disaster recovery.

The correct solution is multi-region deployment with active-active instances because it ensures redundancy, automated failover, near-zero downtime, and operational continuity. This architecture aligns with cloud-native disaster recovery best practices, ensuring resilience, high availability, and business continuity for mission-critical workloads.

Question 96

You need to deploy a highly available, stateless web application that must automatically scale based on HTTP request volume while minimizing operational overhead. Which Google Cloud service is most appropriate?

A) Compute Engine with managed instance groups
B) App Engine Standard Environment
C) Cloud Run
D) Kubernetes Engine (GKE)

Answer C) Cloud Run

Explanation

A) Compute Engine with managed instance groups allows horizontal scaling of VM instances based on metrics such as CPU utilization or load. While this approach provides high availability, it introduces significant operational overhead. Each instance must be maintained with OS updates, security patches, runtime environments, and application deployment. Scaling is metric-based and may not align directly with HTTP request volume without additional configuration. Rolling updates require manual orchestration to avoid downtime. Stateless containerized applications can run on Compute Engine, but managing scaling, monitoring, and updates introduces complexity that is unnecessary for serverless workloads.

B) App Engine Standard Environment is a fully managed, serverless platform with automatic scaling and traffic-based routing. It abstracts infrastructure management and simplifies deployment, but it is less flexible for custom containers or non-standard runtimes. App Engine Standard is optimized for web applications in predefined environments, limiting support for containerized microservices with specific dependencies. It does handle HTTP request-based scaling, but the developer has limited control over runtime configuration compared to Cloud Run.

C) Cloud Run is a fully managed, serverless container platform optimized for stateless applications. It scales automatically based on HTTP request volume, including scaling down to zero when no traffic is present. Cloud Run supports custom container images and provides zero-downtime deployments via traffic splitting. Security is enforced via IAM, and integration with Cloud Monitoring allows operational visibility. This platform minimizes operational overhead while supporting rapid deployment, automatic scaling, and high availability. It is ideal for modern web applications that require elastic scaling without managing underlying infrastructure.

D) Kubernetes Engine (GKE) provides robust orchestration for containerized applications, including autoscaling and rolling updates. While GKE is highly flexible, managing clusters, nodes, and networking introduces operational overhead. For a simple stateless web application that scales automatically based on HTTP traffic, GKE is overkill and less efficient than Cloud Run.

The correct solution is Cloud Run because it delivers serverless scaling, minimal operational overhead, support for containerized workloads, and high availability. Cloud Run balances simplicity, flexibility, and enterprise-grade reliability, making it ideal for stateless web applications that must scale automatically with demand. By leveraging Cloud Run, organizations reduce management complexity, ensure zero-downtime deployments, and improve cost efficiency through pay-per-use scaling.

Question 97

You need to implement a real-time analytics pipeline for IoT sensor data, including ingestion, transformation, and storage for reporting. Which combination of services is most appropriate?

A) Cloud Functions and Cloud Storage
B) Cloud Pub/Sub, Cloud Dataflow, and BigQuery
C) Cloud Run and Cloud SQL
D) Compute Engine and Cloud Bigtable

Answer B) Cloud Pub/Sub, Cloud Dataflow, and BigQuery

Explanation

A) Cloud Functions combined with Cloud Storage is suitable for event-driven workloads triggered by file uploads. While serverless and scalable, it cannot handle high-throughput, real-time IoT data streams efficiently. Complex transformations, aggregations, or windowed computations are difficult to implement with Cloud Functions. Cold starts introduce latency, and scaling is not optimized for continuous, high-frequency IoT data streams.

B) Cloud Pub/Sub, Cloud Dataflow, and BigQuery provide a fully managed, serverless real-time streaming analytics solution. Pub/Sub handles scalable, reliable ingestion of events from distributed IoT devices with at-least-once delivery guarantees. Dataflow performs transformations, filtering, aggregations, and windowed computations in real time. BigQuery stores and queries processed data for reporting and analysis. This architecture is fault-tolerant, scalable, and provides near real-time insights. Built-in monitoring, logging, and IAM integration ensure operational visibility and security. Checkpointing and automatic retries ensure data integrity. This combination is optimized for enterprise IoT pipelines and reduces operational overhead compared to custom-managed solutions.

C) Cloud Run and Cloud SQL can handle containerized workloads and relational storage. However, Cloud SQL is not optimized for high-throughput, real-time analytics. This combination may introduce bottlenecks and latency, making it unsuitable for real-time IoT pipelines requiring continuous ingestion and processing.

D) Compute Engine and Cloud Bigtable offer flexibility and high throughput for NoSQL workloads. While feasible, Compute Engine requires manual orchestration, scaling, and error handling. Cloud Bigtable is excellent for time-series data but lacks native support for analytics and reporting, making this architecture operationally complex and less efficient than the fully managed Pub/Sub, Dataflow, and BigQuery combination.

The correct solution is Pub/Sub, Dataflow, and BigQuery because it enables real-time ingestion, transformation, and storage with minimal operational overhead. This architecture ensures scalability, fault tolerance, and near real-time insights while supporting enterprise-grade IoT workloads. It reduces manual management, enhances reliability, and integrates seamlessly with other Google Cloud services.

Question 98

You need to provide temporary secure access to a third-party contractor to upload files to Cloud Storage. Which approach is most appropriate?

A) Share personal credentials
B) Create a service account with long-lived keys
C) Use signed URLs
D) Grant Owner permissions

Answer C) Use signed URLs

Explanation

A) Sharing personal credentials is highly insecure and violates the principle of least privilege. It exposes all project resources and complicates auditing, revocation, and monitoring. This approach is unsuitable for enterprise environments.

B) Creating a service account with long-lived keys provides programmatic access but is not suitable for temporary access. Long-lived keys require secure storage, rotation, and monitoring. Sharing these keys introduces operational risk and complexity.

C) Signed URLs allow temporary, secure access to specific objects in Cloud Storage without creating IAM accounts. Permissions and expiration times are configurable, ensuring contractors can upload files without accessing other resources. Signed URLs are auditable, scalable, and operationally efficient, reducing administrative overhead. They enforce least-privilege access and align with enterprise security best practices. Contractors can perform required tasks safely, with access automatically expiring to minimize security risk.

D) Granting Owner permissions is excessive and insecure. Owners have full control over all project resources, which is unnecessary for temporary uploads. This increases risk and violates least-privilege principles.

The correct solution is signed URLs because they provide temporary, secure, auditable access, minimize operational overhead, and align with cloud-native security practices. This approach ensures contractors can perform necessary tasks safely without compromising other resources.

Question 99

You need to monitor Compute Engine instances for CPU, memory, and disk usage and alert your operations team when thresholds are exceeded. Which service is most appropriate?

A) Cloud Logging
B) Cloud Monitoring with alerting policies
C) Cloud Trace
D) Cloud Storage notifications

Answer B) Cloud Monitoring with alerting policies

Explanation

A) Cloud Logging captures logs for auditing and troubleshooting, but it does not provide real-time metrics or threshold-based alerts. Using logs alone for monitoring requires complex pipelines and delays alerts, making it unsuitable for proactive operational monitoring.

B) Cloud Monitoring collects real-time metrics from Compute Engine instances, including CPU utilization, memory, and disk I/O. Alerting policies allow thresholds to be defined and notifications to be sent via email, Slack, PagerDuty, or other channels. Dashboards visualize trends, enabling proactive incident response, capacity planning, and operational efficiency. Integration with IAM and logging ensures centralized observability. Cloud Monitoring allows operations teams to detect anomalies, maintain high availability, and optimize performance. Automated alerts, operational dashboards, and trend analysis provide enterprise-grade monitoring for infrastructure.

C) Cloud Trace monitors application latency and distributed request performance. While valuable for debugging and performance optimization, it cannot monitor CPU, memory, or disk metrics, making it unsuitable for system monitoring.

D) Cloud Storage notifications alert users to object changes in storage buckets. They are unrelated to Compute Engine instance metrics and cannot trigger operational alerts based on thresholds.

The correct solution is Cloud Monitoring with alerting policies because it provides real-time metrics, automated alerts, dashboards, and operational insights. This ensures proactive incident response, minimal downtime, and high availability for Compute Engine instances, aligning with enterprise monitoring best practices.

Question 100

You need to design a disaster recovery solution for a mission-critical application that must remain available during a regional outage. Which architecture is most appropriate?

A) Single-region deployment with automated backups
B) Multi-region deployment with active-active instances
C) Single-region deployment with snapshots
D) Deploy all resources in a private VPC

Answer B) Multi-region deployment with active-active instances

Explanation

A) Single-region deployment with automated backups protects against accidental deletion or corruption but does not provide resilience against regional failures. If the region fails, downtime occurs until resources are restored elsewhere, which does not meet near-zero recovery time objectives (RTO) or recovery point objectives (RPO).

B) Multi-region deployment with active-active instances ensures continuous availability across multiple regions. Traffic is distributed using a global load balancer, and healthy instances in unaffected regions automatically handle requests during a regional outage. This architecture provides automated failover, high availability, fault tolerance, and scalability. Active-active deployments meet enterprise RTO and RPO requirements, ensuring near-zero downtime and operational continuity. Cloud-native features such as health checks, global routing, and automated failover enhance resilience, reliability, and business continuity. This solution is ideal for mission-critical applications requiring continuous availability and operational resilience.

C) Single-region deployment with snapshots allows recovery but requires manual restoration in another region, introducing downtime. Snapshots alone do not ensure high availability or automated failover.

D) Deploying resources in a private VPC enhances security but does not provide cross-region redundancy. A regional failure would render all resources unavailable, making this approach insufficient for disaster recovery.

The correct solution is multi-region deployment with active-active instances because it ensures redundancy, automated failover, near-zero downtime, and operational continuity. This architecture aligns with cloud-native disaster recovery best practices, ensuring resilience, high availability, and operational continuity for mission-critical workloads while meeting enterprise business continuity objectives.