Google Associate Cloud Engineer Exam Dumps and Practice Test Questions Set 6 Q 101- 120 

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Question 101

You need to deploy a containerized stateless application that must scale automatically in response to HTTP requests and minimize 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 virtual machines based on metrics such as CPU utilization. While it can provide high availability, it introduces significant operational overhead. Each VM requires OS management, security patching, and deployment of the container runtime. Scaling is based on metrics rather than HTTP requests directly unless custom configurations are added. Rolling updates must be carefully orchestrated to avoid downtime. For stateless containerized applications, this approach adds unnecessary complexity compared to fully managed serverless solutions.

B) App Engine Standard Environment is a fully managed platform that scales automatically based on HTTP requests. It abstracts infrastructure management, reducing operational overhead. However, it has runtime restrictions and limited support for custom containerized applications. For applications requiring custom runtimes or specialized dependencies, App Engine Standard may be less flexible than Cloud Run.

C) Cloud Run is a fully managed, serverless platform for containerized workloads. It automatically scales based on incoming HTTP request volume, including scaling to zero when no traffic is present, minimizing cost. Cloud Run supports custom container images, provides zero-downtime deployments with traffic splitting, and integrates seamlessly with IAM for secure access. Operational overhead is minimal because the platform abstracts infrastructure, patching, scaling, and load balancing. Cloud Run is ideal for stateless applications requiring fast deployment, scalability, and high availability.

D) Kubernetes Engine (GKE) is a powerful container orchestration platform offering scaling, rolling updates, and self-healing. While highly flexible, GKE introduces operational complexity, requiring cluster management, node maintenance, and network configuration. For simple stateless applications that need request-driven scaling, GKE is more complex and less cost-efficient than Cloud Run.

The correct solution is Cloud Run because it provides fully managed scaling, minimal operational overhead, support for containerized workloads, high availability, and secure deployment. It balances flexibility, simplicity, and enterprise-grade reliability, making it ideal for stateless web applications with variable traffic patterns.

Question 102

You need to implement a real-time streaming analytics pipeline to process IoT sensor data, transform it, and store it for reporting. Which combination of Google Cloud 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 and Cloud Storage can handle event-driven workloads triggered by file uploads. However, Cloud Functions are not designed for high-throughput real-time data streams. Complex transformations, aggregations, and windowed computations are difficult to implement. Cold starts can introduce latency, and continuous scaling for high-frequency IoT data is challenging.

B) Cloud Pub/Sub, Cloud Dataflow, and BigQuery provide a fully managed, serverless streaming analytics solution. Pub/Sub allows scalable, reliable ingestion of events with at-least-once delivery guarantees. Dataflow performs transformations, aggregations, filtering, and windowed computations in real time. BigQuery serves as a data warehouse for storage and analytical queries. This architecture supports high-throughput ingestion, near real-time analytics, fault tolerance, and automatic scaling. Built-in monitoring, logging, and IAM integration ensure operational visibility and security. Checkpointing and retries guarantee data integrity, making this combination ideal for enterprise IoT pipelines with minimal operational overhead.

C) Cloud Run and Cloud SQL can manage containerized workloads and relational storage. However, Cloud SQL is not optimized for high-throughput streaming analytics. This approach may create performance bottlenecks and is less suitable for continuous IoT data streams.

D) Compute Engine and Cloud Bigtable can support high-throughput workloads. Compute Engine requires manual orchestration and scaling, while Cloud Bigtable is optimized for time-series or key-value data but lacks native analytics and reporting capabilities. Operational complexity and cost are higher compared to the fully managed Pub/Sub, Dataflow, and BigQuery solution.

The correct solution is Pub/Sub, Dataflow, and BigQuery because it enables scalable ingestion, transformation, and storage with near real-time analytics. It ensures high availability, fault tolerance, and minimal operational overhead, making it ideal for enterprise-grade IoT solutions.

Question 103

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 and complicates auditing, revocation, and monitoring. This method is unsuitable for enterprise environments.

B) Creating a service account with long-lived keys provides programmatic access but is unsuitable for temporary access. Long-lived keys require secure storage, rotation, and monitoring. Sharing keys increases operational risk and administrative overhead.

C) Signed URLs allow temporary, secure access to specific objects in Cloud Storage without creating IAM accounts. Permissions and expiration times are configurable, ensuring the contractor can upload files without accessing unrelated resources. Signed URLs are auditable, scalable, and operationally efficient. They enforce least-privilege access and align with enterprise security best practices. Contractors can complete their tasks safely with automatic expiration minimizing 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 access, reduce operational overhead, and enforce least-privilege access. This method aligns with cloud-native security best practices and ensures contractors can safely perform their required tasks.

Question 104

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 troubleshooting and auditing but does not provide real-time system metrics or automated alerts. Using logs for monitoring requires complex pipelines, adding latency and operational overhead, making it unsuitable for proactive incident response.

B) Cloud Monitoring collects real-time metrics from Compute Engine instances, including CPU, memory, and disk I/O. Alerting policies allow thresholds to be defined and 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 ensures centralized observability. Cloud Monitoring allows operations teams to detect anomalies promptly, maintain high availability, and optimize performance. Automated alerts and dashboards provide enterprise-grade monitoring for infrastructure workloads.

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

D) Cloud Storage notifications alert users to object changes in storage buckets. They are unrelated to Compute Engine instance metrics and cannot trigger 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 ensures proactive incident response, reduces downtime, and maintains high availability for Compute Engine workloads.

Question 105

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 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 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 and reliability. This solution is ideal for mission-critical applications requiring continuous availability, operational continuity, and enterprise-grade disaster recovery.

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

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 cloud-native disaster recovery best practices, ensuring resilience, high availability, and business continuity for mission-critical workloads.

Question 106

You need to deploy a containerized web application that must scale automatically in response to HTTP traffic and minimize 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 like CPU or load. While this provides high availability, each VM requires OS patching, security updates, and container runtime management. Rolling updates and scaling based on HTTP requests require additional setup, making operational overhead significant. For stateless containerized web applications, this solution is less efficient compared to serverless platforms.

B) App Engine Standard Environment automatically scales based on HTTP request volume and abstracts infrastructure management. It is fully managed, reducing operational burden. However, it has runtime constraints and limited support for custom containerized applications. For applications needing custom dependencies or container images, App Engine Standard is less flexible.

C) Cloud Run is a fully managed, serverless platform designed for stateless containers. It scales automatically based on HTTP traffic, including scaling down to zero when no requests are present, which minimizes cost. Cloud Run supports custom container images, zero-downtime deployments, and integrates with IAM for secure access. Operational overhead is minimal because the platform abstracts underlying infrastructure, load balancing, and patching. Cloud Run is ideal for applications that require fast deployment, elastic scaling, and high availability without the complexity of cluster management.

D) Kubernetes Engine (GKE) is a robust container orchestration platform with autoscaling, rolling updates, and self-healing capabilities. While highly flexible, GKE introduces operational complexity, requiring cluster management, node maintenance, networking setup, and monitoring. For simple stateless web applications needing automatic HTTP-based scaling, GKE is overkill and less cost-effective than Cloud Run.

The correct solution is Cloud Run because it delivers fully managed scaling, minimal operational overhead, support for containerized workloads, and high availability. Cloud Run provides a balance between simplicity, flexibility, and enterprise-grade reliability, making it ideal for stateless web applications with variable traffic patterns.

Question 107

You need to implement a real-time analytics pipeline for streaming IoT sensor data, including ingestion, transformation, and storage for reporting. Which combination of Google Cloud 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 and Cloud Storage can handle event-driven workloads triggered by file uploads. While serverless and scalable, Cloud Functions are not optimized for high-throughput streaming data. Complex transformations, aggregations, and windowed computations are difficult to implement. Cold starts introduce latency, and continuous scaling for high-frequency IoT data is challenging.

B) Cloud Pub/Sub, Cloud Dataflow, and BigQuery provide a fully managed, serverless real-time streaming analytics solution. Pub/Sub handles scalable ingestion of events from distributed IoT devices, offering at-least-once delivery guarantees. Dataflow performs transformations, aggregations, filtering, and windowed computations in real time. BigQuery serves as the data warehouse for storing and querying processed data. This architecture is fault-tolerant, highly scalable, and allows near real-time analytics. Built-in monitoring, logging, and IAM integration ensures operational visibility and security. Checkpointing, retries, and fault tolerance maintain data integrity. This combination reduces operational overhead while supporting enterprise-grade IoT pipelines.

C) Cloud Run and Cloud SQL can manage containerized workloads and relational storage. However, Cloud SQL is not optimized for high-throughput, real-time analytics, making this combination less suitable for IoT pipelines that require continuous ingestion and low latency processing.

D) Compute Engine and Cloud Bigtable can handle high-throughput workloads. Compute Engine requires manual orchestration, scaling, and monitoring. Cloud Bigtable is optimized for time-series and key-value data but lacks built-in analytics capabilities. Operational complexity and cost are higher compared to Pub/Sub, Dataflow, and BigQuery, which are fully managed and serverless.

The correct solution is Pub/Sub, Dataflow, and BigQuery because it enables real-time ingestion, transformation, and storage with near real-time analytics. It supports scalability, fault tolerance, and enterprise-grade reliability while minimizing operational overhead.

Question 108

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, making auditing, revocation, and monitoring difficult. This is unacceptable in an enterprise environment.

B) Creating a service account with long-lived keys provides programmatic access but is unsuitable for temporary access. Long-lived keys require secure management, rotation, and monitoring. Sharing keys increases 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 can be set to limit access to the required scope. This approach is auditable, scalable, and reduces operational overhead. It enforces least-privilege access and ensures contractors can safely upload files. Automatic expiration reduces the risk of unauthorized access, aligning with enterprise security best practices.

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 security risk and violates least-privilege principles.

The correct solution is signed URLs because they provide temporary, secure, auditable access with minimal operational overhead. They allow contractors to perform their tasks safely without compromising other resources.

Question 109

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 but does not provide real-time system metrics or threshold-based alerts. Using logs alone for monitoring requires complex pipelines and adds latency, making proactive incident response difficult.

B) Cloud Monitoring collects real-time metrics from Compute Engine instances, including CPU, memory, and disk I/O. Alerting policies allow thresholds to be defined, and notifications can be sent via email, Slack, PagerDuty, or other channels. Dashboards provide trend visualization and operational insights, enabling proactive incident response, capacity planning, and performance optimization. Integration with IAM and logging ensures centralized observability. Cloud Monitoring supports automated alerting, reducing downtime and improving operational efficiency for enterprise workloads.

C) Cloud Trace focuses on application latency and distributed request performance. It is valuable for debugging and optimizing applications but cannot monitor infrastructure-level metrics such as CPU, memory, or disk usage.

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

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

 

Question 110

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 that require 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 provide automated failover or high availability.

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 cloud-native disaster recovery best practices, ensuring resilience, high availability, and business continuity for mission-critical workloads.

Question 111

You need to deploy a multi-service containerized application that requires automatic scaling, rolling updates, and secure service-to-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 horizontal scaling of virtual machines. While this enables scaling based on metrics such as CPU utilization, it does not provide native container orchestration. Each service must be deployed, managed, and connected manually, requiring custom scripts for network configuration, security, and load balancing. Rolling updates are not automated and require careful orchestration to avoid downtime. Service-to-service communication security must be configured manually using firewall rules, VPNs, or custom networking policies, which introduces operational complexity. This approach can work for microservices but is inefficient and error-prone compared to managed container orchestration solutions.

B) App Engine Standard Environment is a fully managed serverless platform that automatically scales applications based on incoming HTTP traffic. It simplifies deployment and abstracts infrastructure management. While App Engine handles scaling and routing automatically, it has limited support for multi-service containerized applications and custom runtimes. Secure service-to-service communication and advanced routing rules are not as configurable as in Kubernetes with Istio. App Engine is suitable for simple web services but lacks the enterprise-grade orchestration, traffic management, and service mesh features required for complex multi-service applications.

C) Kubernetes Engine (GKE) with Istio is designed for containerized microservices requiring automatic scaling, rolling updates, and secure service-to-service communication. GKE provides Kubernetes orchestration with horizontal pod autoscaling, automated rolling updates, self-healing, and declarative deployments. Istio, a service mesh, provides mutual TLS encryption between services, fine-grained traffic routing, retries, fault tolerance, observability, and monitoring. This combination ensures zero-downtime deployments, secure inter-service communication, and operational efficiency. GKE with Istio is ideal for enterprise-grade microservices architectures, simplifying operational management while enhancing security, scalability, and reliability. Monitoring, logging, and policy enforcement are built into the platform, further reducing operational risk.

D) Cloud Run is a fully managed serverless container platform optimized for stateless workloads. It scales automatically based on HTTP requests but lacks native support for complex multi-service orchestration, service-to-service communication, and advanced traffic management. Implementing secure communication and orchestration across multiple Cloud Run services requires additional configuration and external tools, making it less efficient than GKE with Istio for enterprise microservices.

The correct solution is Kubernetes Engine with Istio because it provides automated orchestration, secure service-to-service communication, rolling updates, and enterprise-grade operational features. This combination minimizes manual management, ensures resilience, and supports microservices architectures in production environments.

Question 112

You need to migrate an on-premises PostgreSQL database to Cloud SQL with minimal downtime while ensuring continuous replication. Which approach is most appropriate?

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 for small datasets. However, this method introduces downtime because the source database must stop accepting writes during export to maintain consistency. For large databases, the export/import process can take hours or days. Any changes made after the export are not captured, leading to potential data inconsistencies. This approach is unsuitable for production environments requiring minimal downtime and continuous replication.

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, and automated cutover support, reducing operational risk. Continuous replication ensures data consistency, allowing a seamless transition with near-zero downtime. This solution is ideal for enterprise migrations where uptime, data integrity, and operational reliability are critical.

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 scenarios. 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 ensures minimal downtime, maintains data consistency, automates schema migration, and provides enterprise-grade operational reliability. This approach supports seamless migration while maintaining business continuity and reducing risk.

Question 113

You need to provide temporary secure access for a third-party 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 least-privilege principles. It exposes all project resources, complicates auditing, and increases the risk of misuse. This method is not recommended 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 them increases operational risk and administrative overhead.

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 intended actions for a limited time. Signed URLs are auditable, scalable, and operationally efficient. They enforce least-privilege access and reduce security risks by limiting access scope and duration. Contractors can complete their tasks safely, and access automatically expires, preventing unauthorized use.

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

The correct solution is signed URLs because they provide temporary, secure, auditable access with minimal operational overhead. This ensures contractors can safely perform uploads without compromising other resources.

Question 114

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, but it does not provide real-time metrics or threshold-based alerts. Using logs alone for monitoring requires complex pipelines, adding latency and operational overhead. This makes it unsuitable for proactive incident response.

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, and notifications can be sent via email, Slack, PagerDuty, or other channels. Dashboards provide trend visualization and operational insights, enabling proactive incident response, capacity planning, and performance optimization. Integration with IAM and logging ensures centralized observability. Automated alerts reduce downtime, improve operational efficiency, and allow teams to take corrective actions before issues impact users. Cloud Monitoring supports enterprise-grade monitoring for infrastructure workloads.

C) Cloud Trace focuses on application latency and distributed request performance. While useful for debugging and optimization, it cannot monitor infrastructure metrics such as CPU, memory, or disk usage, making it unsuitable for system monitoring.

D) Cloud Storage notifications alert users to object changes in storage buckets. They are unrelated to Compute Engine metrics and cannot trigger 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 enables proactive response, minimizes downtime, and ensures high availability for Compute Engine workloads.

Question 115

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 address regional failures. If the region fails, downtime occurs until resources are restored elsewhere. This approach does not meet near-zero RTO or RPO requirements for mission-critical workloads.

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 and reliability. This solution is ideal for mission-critical applications requiring continuous availability and operational continuity.

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

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 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 116

You need to deploy a stateless web application that can automatically scale based on HTTP request traffic 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 provides horizontal scaling of virtual machines based on metrics such as CPU utilization. While this ensures high availability, each instance requires OS management, security updates, and runtime environment configuration. Scaling based on HTTP traffic is indirect and requires additional configuration. Rolling updates must be carefully orchestrated to avoid downtime, and operational overhead remains significant for stateless containerized applications. This approach is less efficient than fully managed serverless solutions.

B) App Engine Standard Environment automatically scales based on HTTP request traffic and abstracts infrastructure management. It reduces operational burden, but runtime restrictions limit flexibility for containerized applications or specialized dependencies. It is more suitable for predefined runtimes and simpler applications rather than fully containerized microservices.

C) Cloud Run is a fully managed, serverless container platform optimized for stateless applications. It automatically scales based on HTTP requests, including scaling to zero when no traffic is present, minimizing cost. Cloud Run supports custom container images, provides zero-downtime deployments with traffic splitting, and integrates with IAM for secure access. Operational overhead is minimal because infrastructure management, patching, and load balancing are abstracted. Cloud Run is ideal for stateless web applications that require rapid deployment, elastic scaling, and high availability with minimal management effort.

D) Kubernetes Engine (GKE) provides powerful orchestration for containerized applications, including autoscaling, rolling updates, and self-healing. While highly flexible, it introduces operational complexity because clusters, nodes, and networking must be managed. For simple stateless applications requiring HTTP-driven scaling, GKE is overkill and less cost-effective than Cloud Run.

The correct solution is Cloud Run because it delivers fully managed scaling, minimal operational overhead, high availability, and support for containerized workloads. It provides an optimal balance between simplicity, flexibility, and enterprise-grade reliability.

Question 117

You need to implement a real-time streaming analytics pipeline to process IoT sensor data, perform transformations, and store results for reporting. Which combination of Google Cloud 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 with Cloud Storage can handle event-driven workloads triggered by file uploads. However, this combination is not optimized for high-throughput streaming analytics. Complex transformations, aggregations, and windowed computations are difficult to implement. Cold starts may introduce latency, and continuous scaling for high-frequency IoT data streams is challenging.

B) Cloud Pub/Sub, Cloud Dataflow, and BigQuery provide a fully managed, serverless solution for real-time streaming analytics. Pub/Sub ensures scalable, reliable ingestion of IoT events with at-least-once delivery. Dataflow performs real-time transformations, filtering, aggregations, and windowed computations. BigQuery stores and queries processed data for analytics and reporting. This architecture is fault-tolerant, scalable, and provides near real-time insights. Built-in monitoring, logging, IAM integration, checkpointing, and retries ensure operational visibility and data consistency. This combination minimizes operational overhead while supporting enterprise-grade IoT pipelines.

C) Cloud Run and Cloud SQL can handle containerized workloads and relational storage. However, Cloud SQL is not optimized for high-throughput streaming analytics, and using it in real-time pipelines may introduce latency and bottlenecks.

D) Compute Engine with Cloud Bigtable offers flexibility and high throughput for NoSQL workloads. Compute Engine requires manual orchestration, scaling, and monitoring. Cloud Bigtable excels at time-series and key-value data but lacks built-in analytical capabilities, making this combination operationally complex and less suitable for real-time streaming analytics compared to Pub/Sub, Dataflow, and BigQuery.

The correct solution is Pub/Sub, Dataflow, and BigQuery because it enables real-time ingestion, transformation, and storage with minimal operational overhead. It ensures scalability, fault tolerance, and enterprise-grade reliability for IoT pipelines.

Question 118

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 least-privilege principles. It exposes all project resources and complicates auditing, revocation, and monitoring. This approach is unacceptable in enterprise environments.

B) Creating a service account with long-lived keys provides programmatic access but is unsuitable for temporary access. Long-lived keys require secure management, rotation, and monitoring. Sharing keys increases operational risk and complexity.

C) Signed URLs provide temporary, secure access to specific Cloud Storage objects without creating IAM accounts. Permissions and expiration times can be set to restrict access scope and duration. Signed URLs are auditable, scalable, and operationally efficient. They enforce least-privilege access, reduce risk, and ensure contractors can safely upload files. Automatic expiration ensures security even if the link is exposed.

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

The correct solution is signed URLs because they provide temporary, secure, auditable access with minimal operational overhead. This allows contractors to perform their tasks safely without compromising other resources.

Question 119

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 metrics or automated alerts. Using logs alone for monitoring requires additional pipelines, increasing latency and operational complexity, which is not suitable for proactive incident response.

B) Cloud Monitoring collects real-time metrics from Compute Engine instances, including CPU, memory, and disk I/O. Alerting policies allow thresholds to be defined, and notifications can be sent via email, Slack, PagerDuty, or other channels. Dashboards provide trend visualization and operational insights, enabling proactive incident response, capacity planning, and performance optimization. Integration with IAM and logging ensures centralized observability. Automated alerts reduce downtime, improve operational efficiency, and allow teams to take corrective actions before issues impact users. This service is enterprise-grade and ensures consistent monitoring across infrastructure.

C) Cloud Trace monitors application latency and distributed request performance. While valuable for debugging and optimization, it does not capture infrastructure-level metrics like CPU, memory, or disk usage, 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 threshold-based alerts.

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

Question 120

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. This does not meet near-zero recovery time objectives (RTO) or recovery point objectives (RPO) required for mission-critical workloads.

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 like health checks, global routing, and automated failover enhance resilience, reliability, and business continuity. This architecture is ideal for mission-critical applications requiring continuous availability and enterprise-grade disaster recovery.

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

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 design aligns with cloud-native disaster recovery best practices, ensuring resilience, high availability, and business continuity for mission-critical workloads.