Google Associate Cloud Engineer Exam Dumps and Practice Test Questions Set 8 Q 141- 160

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Question 141

You need to deploy a web application that automatically scales based on user traffic and supports custom container images with minimal operational management. 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. While it can handle traffic spikes, each VM requires ongoing patching, container runtime setup, monitoring, and operational management. Scaling based on HTTP traffic is not direct and requires additional configuration. Rolling updates must be carefully managed to avoid downtime. For a stateless web application, this introduces unnecessary operational overhead compared to serverless solutions.

B) App Engine Standard Environment automatically scales based on HTTP traffic and abstracts infrastructure management. However, it has limitations for custom container images and non-standard runtimes. While it reduces operational burden, it is less flexible for modern containerized web applications requiring full control over the runtime environment.

C) Cloud Run is a fully managed, serverless container platform designed for stateless workloads. It automatically scales based on HTTP requests, including scaling down to zero when idle, which reduces cost. Cloud Run supports custom container images, zero-downtime deployments with traffic splitting, and integrates with IAM for secure access. Operational overhead is minimal because infrastructure, patching, and load balancing are handled automatically. This makes it ideal for web applications requiring fast deployment, elastic scaling, and high availability without heavy operational management.

D) Kubernetes Engine (GKE) provides container orchestration with features such as rolling updates, horizontal pod autoscaling, and self-healing. While suitable for complex microservices, it introduces operational complexity because clusters, nodes, networking, and monitoring must be managed. For a simple web application requiring HTTP-driven scaling, GKE is more complex and resource-intensive than Cloud Run.

The correct solution is Cloud Run because it provides automatic scaling, supports custom container images, and minimizes operational overhead. It balances simplicity, flexibility, and reliability for web applications.

Question 142

You need to implement a streaming analytics pipeline to process IoT sensor data in real time, transform it, 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 handles event-driven workloads triggered by file uploads. However, it is not optimized for high-throughput, real-time streaming analytics. Performing transformations, aggregations, and windowed computations requires complex workarounds. Cold starts can introduce latency, and scaling for high-frequency IoT events can be challenging.

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

C) Cloud Run and Cloud SQL can process containerized workloads and store relational data. However, Cloud SQL is not optimized for high-throughput streaming analytics. Using it for continuous streams may introduce latency and bottlenecks.

D) Compute Engine with Cloud Bigtable offers flexibility and high throughput. Compute Engine requires manual orchestration, scaling, and monitoring. Cloud Bigtable excels at time-series and key-value workloads but lacks built-in analytics capabilities. Operational complexity is higher compared to the fully managed Pub/Sub, Dataflow, and BigQuery solution.

The correct solution is Pub/Sub, Dataflow, and BigQuery because it ensures scalable ingestion, real-time transformation, and analytics with minimal operational overhead, high reliability, and enterprise-grade performance.

Question 143

You need to provide temporary secure access to a contractor for uploading 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, complicates auditing, revocation, and monitoring. This is unacceptable in 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 management, increasing operational risk, especially for short-term contractor access.

C) Signed URLs provide temporary, secure access to specific objects in Cloud Storage without creating IAM accounts. Permissions and expiration times can be configured to restrict access scope and duration. Signed URLs are auditable, scalable, and operationally efficient. They enforce least-privilege access, reduce risk, and automatically expire to prevent unauthorized access. Contractors can safely complete tasks without compromising security or other resources.

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

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

Question 144

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 metrics or threshold-based alerts. Using logs alone requires additional pipelines, increasing operational complexity and latency. This makes 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 set, 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 address issues before they impact users. Cloud Monitoring is enterprise-grade and ensures consistent observability across infrastructure workloads.

C) Cloud Trace monitors application latency and distributed request performance. While useful for debugging and optimization, it does not capture infrastructure 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 metrics and cannot trigger threshold-based alerts.

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

 

Question 145

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. 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 routed via 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 design 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 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 146

You need to deploy a multi-service containerized application that requires automatic scaling, rolling updates, and secure inter-service communication with minimal operational management. Which Google Cloud service 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 for virtual machines based on metrics such as CPU or memory utilization. While it can manage multiple VMs, deploying a multi-service containerized application requires manual orchestration of the containers, networking, and updates. Rolling updates must be orchestrated manually, and inter-service communication must be configured for security, typically using VPNs or firewall rules. Each service must be deployed and managed individually, introducing operational overhead. Compute Engine is more suited for monolithic applications or workloads that require direct control over the VM environment rather than microservices with complex interdependencies.

B) App Engine Standard Environment provides automatic scaling for applications based on HTTP traffic and abstracts the underlying infrastructure. While it reduces operational management, it is not suitable for multi-service containerized applications that require custom runtime environments, inter-service security, and advanced routing capabilities. App Engine Standard Environment is ideal for simple web applications rather than complex microservices that need fine-grained control over service communication and deployment orchestration.

C) Kubernetes Engine (GKE) with Istio is the optimal solution for multi-service containerized applications. GKE provides enterprise-grade orchestration with horizontal pod autoscaling, rolling updates, self-healing, and declarative deployment management. Istio, as a service mesh, adds secure inter-service communication using mutual TLS, traffic management, retries, circuit breaking, and observability. This combination enables secure and reliable communication between services without manual intervention, while providing automated scaling and high availability. Operational management is simplified through built-in logging, monitoring, policy enforcement, and automated resource management. For production-grade microservices, GKE with Istio ensures both operational efficiency and enterprise security.

D) Cloud Run is a fully managed, serverless container platform designed for stateless workloads. While it supports containerized applications and automatically scales based on HTTP requests, it lacks native orchestration for multi-service applications and does not provide a service mesh for secure inter-service communication. Implementing security, routing, and communication across multiple Cloud Run services requires additional external tools, increasing complexity. Cloud Run is ideal for simple stateless APIs but not for complex multi-service architectures with strict inter-service security requirements.

The correct solution is Kubernetes Engine with Istio because it provides automated orchestration, secure inter-service communication, rolling updates, observability, and minimal operational overhead. This combination makes it ideal for enterprise microservices that require high availability, security, and operational efficiency.

Question 147

You need to migrate a production PostgreSQL database to Cloud SQL with minimal downtime while maintaining continuous replication of ongoing changes. 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 but unsuitable for production environments requiring minimal downtime. The SQL dump process captures a snapshot at a single point in time, and any changes made after the export are not included. Large databases can take hours or even days to export and import, resulting in significant downtime and potential data inconsistency. This approach does not support continuous replication and is only feasible for non-critical or offline databases.

B) Database Migration Service (DMS) with continuous replication is specifically designed for enterprise-grade database migrations with minimal downtime. DMS automates the initial schema and data migration, as well as continuous replication of ongoing changes. This ensures the Cloud SQL target instance remains synchronized with the source database while the application continues to operate without interruption. Monitoring, logging, and automated cutover further reduce operational risk. Continuous replication guarantees data consistency and near-zero downtime, making this approach ideal for production databases that require high availability during migration. DMS also provides automated validation and rollback options, ensuring a reliable migration path.

C) Manual schema creation and data copy is error-prone, operationally complex, and time-consuming. Maintaining continuous replication manually requires custom scripts, complex monitoring, and intervention in case of failures. This approach increases the risk of data loss and inconsistency and is not recommended for production databases requiring high availability.

D) Cloud Storage Transfer Service is designed for transferring files or objects between storage systems. It does not provide database migration, schema conversion, or replication capabilities. Using it for PostgreSQL migration would require extensive manual intervention and additional tooling, making it inefficient and risky for production environments.

The correct solution is Database Migration Service with continuous replication because it ensures minimal downtime, maintains data integrity, automates operational tasks, and provides enterprise-grade reliability. This approach allows seamless migration while maintaining business continuity for production PostgreSQL workloads.

Question 148

You need to provide temporary, secure access to a third-party contractor for uploading 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, complicates auditing, revocation, and monitoring. This approach is unacceptable in enterprise environments and violates security best practices.

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 revocation management, increasing operational complexity and security risk, particularly for short-term contractor access.

C) Signed URLs provide temporary, secure access to specific objects in Cloud Storage 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 security risk, and automatically expire to prevent unauthorized use. Contractors can safely complete uploads without compromising other resources. Signed URLs are the industry-standard approach for granting temporary file access to external users while maintaining operational security and compliance.

D) Granting Owner permissions is excessive and insecure. Owners have full control over all project resources, which is unnecessary for temporary uploads and violates security principles. This could lead to accidental or malicious modification of critical resources.

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

Question 149

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 infrastructure metrics or threshold-based alerts. Using logs alone requires additional pipelines and processing, which introduces latency and increases operational complexity. This makes proactive incident response difficult.

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 set, 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 and security. Automated alerts reduce downtime, improve operational efficiency, and allow teams to address issues before users are impacted. Cloud Monitoring is enterprise-grade, scalable, and ensures consistent monitoring across infrastructure workloads.

C) Cloud Trace monitors application latency and distributed request performance. While useful for debugging and performance optimization, it does not provide 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, dashboards, automated notifications, and operational insights. This enables proactive response, minimizes downtime, and ensures high availability for Compute Engine workloads.

Question 150

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. This design 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 routed via 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 solution 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, making it insufficient for mission-critical workloads.

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 unsuitable 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 151

You need to deploy a stateless API service that automatically scales based on HTTP requests and requires minimal operational management. 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 you to scale virtual machines horizontally based on metrics such as CPU utilization or load. However, deploying a stateless API service using Compute Engine requires managing the underlying operating system, patching, container runtime, networking, load balancing, and scaling policies manually. While managed instance groups provide automatic VM scaling, HTTP-based scaling requires additional setup with load balancers or external metrics. Rolling updates must be carefully orchestrated to prevent downtime, and managing stateless APIs across multiple VMs introduces operational complexity. Compute Engine is more suitable for monolithic applications or workloads requiring complete control over the OS environment rather than lightweight stateless APIs.

B) App Engine Standard Environment provides automatic scaling based on HTTP requests and abstracts the underlying infrastructure, including patching, monitoring, and load balancing. It is serverless in nature, which reduces operational overhead. However, App Engine Standard has runtime limitations and restrictions on container images, which reduces flexibility for modern containerized applications. It is well-suited for simple web applications or microservices but may not accommodate specific dependencies or custom container requirements for advanced API services.

C) Cloud Run is a fully managed, serverless container platform optimized for stateless workloads. It automatically scales based on incoming HTTP requests, including scaling down to zero when no traffic is present, minimizing cost. Cloud Run supports custom container images, zero-downtime deployments, traffic splitting, and integrates with IAM for secure access. Operational management is minimal because infrastructure management, patching, scaling, and load balancing are fully handled by the platform. This makes Cloud Run ideal for stateless API services requiring rapid deployment, elastic scaling, high availability, and minimal operational overhead. It supports modern containerized workloads and aligns well with microservices architectures.

D) Kubernetes Engine (GKE) provides robust container orchestration with features like rolling updates, horizontal pod autoscaling, self-healing, and networking. While it is flexible and suitable for complex microservices architectures, it introduces significant operational overhead because clusters, nodes, and networking components must be managed. Scaling based on HTTP requests requires setup of ingress controllers and autoscalers. For simple stateless APIs requiring HTTP-driven scaling, GKE is more complex and cost-inefficient compared to Cloud Run.

The correct solution is Cloud Run because it combines serverless simplicity, container flexibility, automatic HTTP-driven scaling, minimal operational overhead, and enterprise-grade reliability, making it ideal for stateless API services.

Question 152

You need to implement a streaming analytics pipeline to process IoT sensor data in real-time, transform it, and store the 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 is an event-driven serverless solution suitable for reacting to file uploads or triggers. While it can handle simple streaming tasks, it is not optimized for high-throughput real-time streaming analytics. Performing transformations, aggregations, and windowed computations is complex and requires significant custom implementation. Cold starts may introduce latency, and high-frequency IoT data ingestion may overwhelm Cloud Functions, leading to inconsistent performance.

B) Cloud Pub/Sub, Cloud Dataflow, and BigQuery provide a fully managed, scalable, serverless architecture for real-time streaming analytics. Pub/Sub handles high-throughput, reliable ingestion of IoT events with at-least-once delivery guarantees. Cloud Dataflow enables real-time transformations, filtering, aggregations, and windowed computations. BigQuery provides scalable storage and querying capabilities for analytics and reporting. This architecture is fault-tolerant, scalable, and supports near real-time processing. Built-in monitoring, logging, IAM integration, checkpointing, and retries ensure operational visibility and data integrity. Using this combination, you can implement a robust streaming pipeline with minimal operational overhead, automated scaling, and enterprise-grade performance. It supports IoT workloads effectively and ensures that analytic results are continuously updated and available for downstream applications and dashboards.

C) Cloud Run and Cloud SQL provide serverless container deployment and relational data storage. However, Cloud SQL is not optimized for high-throughput streaming data ingestion or real-time analytics. Using Cloud SQL for continuous streams may introduce performance bottlenecks and high latency, making it unsuitable for enterprise-scale streaming analytics.

D) Compute Engine with Cloud Bigtable provides flexibility and high throughput. However, Compute Engine requires manual orchestration, scaling, and monitoring. Cloud Bigtable is ideal for time-series data but lacks built-in analytics capabilities. This approach introduces operational complexity, making it less efficient compared to the fully managed Pub/Sub, Dataflow, and BigQuery pipeline.

The correct solution is Pub/Sub, Dataflow, and BigQuery because it enables scalable ingestion, real-time transformation, analytics, fault tolerance, and operational efficiency. This solution is ideal for IoT streaming pipelines requiring high reliability and enterprise-grade performance.

Question 153

You need to provide temporary, secure access to a contractor for uploading 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, complicates auditing, revocation, and monitoring. Personal credentials are intended for individual use, and sharing them is considered a severe security risk in 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 management. Granting access to contractors using service accounts increases operational overhead and introduces unnecessary security risk, particularly for short-term access.

C) Signed URLs provide temporary, secure access to specific objects in Cloud Storage without creating IAM accounts. Permissions and expiration times can be configured to restrict access scope and duration. Signed URLs are auditable, scalable, and operationally efficient. They enforce least-privilege access, reduce security risk, and automatically expire to prevent unauthorized use. Contractors can safely complete their uploads without compromising other resources. This approach is widely used in enterprise scenarios where temporary external access is needed.

D) Granting Owner permissions is excessive and insecure. Owners have full control over all project resources, which is unnecessary for temporary uploads and violates security best practices. This can result in accidental or malicious modification or deletion of resources.

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

Question 154

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 infrastructure metrics or threshold-based alerts. Using logs alone for monitoring requires building custom pipelines and additional tooling, which introduces latency and operational complexity. Proactive monitoring is therefore difficult with Cloud Logging alone.

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 ensures centralized observability and secure access. Automated alerts reduce downtime, improve operational efficiency, and enable teams to address issues before end users are impacted. Cloud Monitoring is enterprise-grade, scalable, and ensures consistent monitoring across infrastructure workloads.

C) Cloud Trace monitors application latency and distributed request performance. While useful for debugging and performance analysis, it does not capture 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, dashboards, automated notifications, and operational insights. This enables proactive response, minimizes downtime, and ensures high availability for Compute Engine workloads.

Question 155

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. 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 routed via 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 design 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 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 156

You need to deploy a highly available web application that serves global traffic and automatically scales based on demand. Which Google Cloud service or architecture is most appropriate?

A) Single Compute Engine instance with autoscaling
B) App Engine Standard Environment with regional deployment
C) Global Load Balancer with multi-region backend instances
D) Cloud Run deployed in a single region

Answer C) Global Load Balancer with multi-region backend instances

Explanation

A) A single Compute Engine instance with autoscaling provides vertical or horizontal scaling, but it is limited to a single region. While managed instance groups can scale based on metrics like CPU or memory utilization, a single regional deployment does not provide global load balancing or high availability across multiple regions. In the event of a regional outage, all traffic is affected, making this architecture unsuitable for a global audience or highly available applications. Furthermore, manual configuration of load balancing, SSL termination, and failover adds operational complexity.

B) App Engine Standard Environment with regional deployment provides automatic scaling and abstracts infrastructure management. It can scale based on HTTP request load and is suitable for web applications. However, a regional deployment does not distribute traffic globally. Users far from the deployed region may experience higher latency. While App Engine reduces operational burden, it does not inherently provide multi-region high availability or automated global failover. Additional configuration and cross-region replication would be required for global resiliency, making this less ideal for truly global, highly available workloads.

C) A Global Load Balancer with multi-region backend instances is the most suitable solution for serving global traffic with high availability. The Global Load Balancer can route user requests to the nearest healthy backend instance, providing low latency and improved user experience. Multi-region deployment ensures that traffic continues to be served in the event of a regional outage. Health checks automatically remove unhealthy instances from serving traffic, ensuring reliability. Auto-scaling across multiple regions allows the system to dynamically adjust capacity based on demand. This architecture provides fault tolerance, global distribution, and operational efficiency while minimizing downtime for end users. Integrating with Cloud CDN further enhances performance for global users by caching content at edge locations.

D) Cloud Run deployed in a single region offers serverless deployment with automatic scaling and container support. However, deploying only in a single region does not provide resilience against regional outages. While Cloud Run can scale elastically based on traffic within the region, global distribution, redundancy, and failover require multi-region deployments. A single-region Cloud Run deployment is therefore insufficient for highly available, global applications.

The correct solution is a Global Load Balancer with multi-region backend instances because it provides global traffic distribution, fault tolerance, automatic scaling, and high availability. This ensures users experience minimal latency, near-zero downtime, and consistent service availability across regions.

Question 157

You need to migrate a large on-premises Oracle database to Cloud SQL with minimal downtime and zero data loss. 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 ETL data migration
D) Cloud Storage Transfer Service

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

Explanation

A) Exporting a database to SQL dump and importing it into Cloud SQL is a straightforward method for small, non-critical databases. However, it is not suitable for large databases or production workloads because the migration process introduces significant downtime. Changes made to the source database after export will not be captured, leading to potential data inconsistency. For enterprise environments requiring zero data loss and minimal downtime, this approach is impractical.

B) Database Migration Service (DMS) with continuous replication is specifically designed to migrate production databases with minimal downtime while ensuring data integrity. DMS handles the initial schema migration and data load, followed by continuous replication of changes from the source database to the Cloud SQL target. This ensures the target remains synchronized with the source, enabling near-zero downtime migration. Built-in validation, monitoring, and automated failover reduce operational risk. DMS supports enterprise requirements for large-scale database migration and maintains transactional consistency, which is critical for applications requiring zero data loss. Additionally, DMS simplifies cutover procedures and allows rollback if necessary.

C) Manual schema creation and ETL data migration is operationally complex and error-prone. It requires scripting, scheduling, and constant monitoring to ensure consistency, especially for high-volume transactional databases. Continuous replication is difficult to implement manually, making this approach unsuitable for production systems where downtime must be minimized.

D) Cloud Storage Transfer Service is designed for transferring objects between storage systems and does not provide database migration capabilities. Using it for Oracle-to-Cloud SQL migration would require extensive custom development, making it inefficient, risky, and error-prone.

The correct solution is Database Migration Service with continuous replication because it provides automated, enterprise-grade migration with minimal downtime, data integrity, and operational reliability. This ensures mission-critical applications experience no data loss and continue running during the migration.

Question 158

You need to provide temporary, secure access to an external consultant 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, complicates auditing, revocation, and monitoring. Personal credentials should never be shared externally in enterprise environments, as this introduces severe security risk and operational liability.

B) Creating a service account with long-lived keys provides programmatic access but is unsuitable for temporary access. Managing key rotation, secure storage, and revocation introduces operational complexity and increases security risk, especially for short-term access.

C) Signed URLs provide temporary, secure access to specific objects in Cloud Storage without requiring the creation of new IAM accounts. Permissions and expiration times can be configured to restrict access to specific operations, such as uploads or downloads, and automatically expire to prevent misuse. Signed URLs are auditable and scalable, enforce least-privilege access, and allow secure collaboration with external contractors without exposing other project resources. This approach is widely adopted in enterprise environments for temporary external access.

D) Granting Owner permissions is excessive and insecure. Owners have full control over all project resources, which is unnecessary for uploading files and violates security principles. This can lead to accidental or malicious modifications of critical resources, creating unnecessary risk.

The correct solution is signed URLs because they provide secure, temporary access with minimal operational overhead while maintaining auditability and compliance. This ensures that external collaborators can complete their tasks safely without compromising other resources.

Question 159

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 metrics or threshold-based alerts. Using logs alone for monitoring requires additional processing pipelines, which introduces latency and complexity. This approach does not allow proactive alerting for infrastructure metrics such as CPU or memory utilization.

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 to be sent to 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 ensures secure, centralized observability. Automated alerts reduce downtime, improve operational efficiency, and allow teams to address issues before end users are impacted. Cloud Monitoring provides enterprise-grade observability, fault detection, and scalable monitoring across infrastructure workloads.

C) Cloud Trace monitors application latency and distributed request performance. While useful for debugging and application optimization, it does not capture infrastructure 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 metrics and cannot trigger threshold-based alerts.

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

Question 160

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 in another region. This design 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 routed via 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 design 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, making this approach insufficient for mission-critical workloads.

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 unsuitable 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.