Google Associate Cloud Engineer Exam Dumps and Practice Test Questions Set 1  Q 1 – 20 

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Question 1

You have a Google Cloud project and want to give a new user the ability to deploy applications to App Engine but not manage the underlying resources. Which IAM role should you assign?

A) App Engine Admin
B) App Engine Deployer
C) Owner
D) Editor

Answer B) App Engine Deployer

Explanation

A) App Engine Admin grants full control over App Engine applications, including managing app settings, deleting apps, and configuring scaling and traffic splitting. While this role allows deployment, it also provides permissions that are unnecessary if the user only needs to deploy. Assigning this role could inadvertently give too much access, potentially violating the principle of least privilege. Therefore, App Engine Admin is more permissive than needed in this scenario.

B) App Engine Deployer is specifically designed for deployment tasks. It allows a user to deploy new versions of applications and update existing ones, but it does not provide permissions to manage App Engine app settings, delete services, or manipulate infrastructure resources. This aligns perfectly with the requirement of allowing deployment without full administrative control. This role embodies the principle of least privilege by providing exactly the needed permissions and nothing more.

C) Owner has full control over all resources in the project, including billing, IAM policies, and deletion of resources. Assigning Owner for deployment purposes is highly excessive and risky because the user would gain access to sensitive operations unrelated to application deployment. Using Owner violates security best practices in most scenarios, especially for operational tasks like deploying apps.

D) Editor grants broad permissions to modify almost all resources within a project, including Compute Engine instances, Cloud Storage, and networking resources. It does not restrict access to just App Engine deployment, so a user could unintentionally modify unrelated resources. This role is more general and lacks the specificity needed for deployment-only tasks, making it unsuitable here.

The correct answer is App Engine Deployer because it provides deployment capability while limiting administrative privileges. By assigning this role, the user can deploy apps safely without accessing sensitive project configurations or underlying resources, ensuring adherence to security best practices. It balances operational necessity with access control.

Question 2

You are tasked with designing a solution to allow your on-premises data center to securely connect to Google Cloud with minimal latency. Which service is the most suitable?

A) Cloud VPN
B) Cloud Interconnect
C) Cloud NAT
D) Cloud CDN

Answer B) Cloud Interconnect

Explanation

A) Cloud VPN provides encrypted connections over the public internet to Google Cloud. While it is secure and relatively easy to set up, the connection depends on internet performance, which can introduce higher latency and potential variability in throughput. For scenarios requiring minimal latency and consistent bandwidth, Cloud VPN may not provide the level of performance needed.

B) Cloud Interconnect offers direct physical or dedicated connections from an on-premises environment to Google Cloud, bypassing the public internet. This provides low latency, high throughput, and predictable network performance. There are different types such as Dedicated Interconnect and Partner Interconnect, allowing enterprises to choose the best fit based on their location, bandwidth requirements, and redundancy needs. Cloud Interconnect is ideal for high-performance workloads, real-time applications, and situations where predictable latency is critical.

C) Cloud NAT (Network Address Translation) allows instances in private subnets to access the internet without exposing their IP addresses. It does not create a direct connection between on-premises infrastructure and Google Cloud, so it does not address the requirement for minimal latency or secure connectivity between data centers. Its purpose is different, mainly for outbound internet access for private resources.

D) Cloud CDN (Content Delivery Network) caches content at the edge locations closer to users to reduce latency for global access. It is designed for delivering web content and static assets efficiently but does not provide direct connectivity between on-premises infrastructure and Google Cloud. Using Cloud CDN in this scenario would not meet the requirement for a secure, low-latency connection between data centers.

Cloud Interconnect is the correct choice because it provides a dedicated, high-bandwidth, and low-latency connection suitable for enterprise-grade hybrid environments. It ensures performance predictability and security while enabling consistent communication between on-premises systems and cloud resources.

Question 3

You deployed a Compute Engine instance and want to allow incoming traffic only from a specific IP address on TCP port 8080. Which method should you use?

A) Firewall rules
B) IAM roles
C) VPC Peering
D) Cloud NAT

Answer A) Firewall rules

Explanation

A) Firewall rules are used to control ingress and egress traffic to and from virtual machine instances within a VPC. You can create a rule that allows traffic from a specific source IP address and port, which directly matches the requirement. Firewall rules can be stateful, meaning they track established connections, and they integrate seamlessly with VPC networks to enforce network security policies efficiently. This method provides precise control over network access and is the standard practice for managing traffic to Compute Engine instances.

B) IAM roles are used to control access to Google Cloud resources at the management level. They do not regulate network traffic or port-level access to instances. Assigning an IAM role cannot restrict TCP port 8080 access from a specific IP. IAM governs who can perform administrative actions or access APIs, but it is unrelated to firewall-level traffic management.

C) VPC Peering allows connectivity between two VPC networks without using external IP addresses. While it enables instances in different VPCs to communicate, it does not provide a mechanism for controlling traffic based on IP addresses and port numbers. It is primarily a network connectivity solution rather than a security access control tool for inbound traffic.

D) Cloud NAT allows instances without external IP addresses to access the internet for outbound connections. It does not filter incoming traffic, and it cannot be used to restrict access to TCP port 8080 from a specific IP address. Its purpose is network address translation for outbound connectivity, making it irrelevant for this requirement.

Firewall rules are the correct method because they provide fine-grained control over ingress traffic, enabling the restriction of TCP ports and source IP addresses. This ensures that only authorized clients can reach the instance, enhancing security while maintaining proper access for the intended use case.

Question 4

You need to store a large amount of unstructured data in Google Cloud and require low-cost storage with high durability, but infrequent access. Which storage class should you use?

A) Standard
B) Nearline
C) Coldline
D) Archive

Answer C) Coldline

Explanation

A) Standard storage is designed for frequently accessed data and provides low latency and high throughput. While it offers high durability, it is more expensive than storage classes meant for infrequent access. Using Standard storage for data that is rarely accessed is not cost-effective because the per-GB pricing is optimized for hot data rather than archival or cold workloads.

B) Nearline storage is intended for data accessed roughly once a month. It offers lower storage costs compared to Standard and slightly higher retrieval costs. Nearline is suitable for backup and disaster recovery data that may be accessed occasionally but is not optimal for long-term infrequent access due to higher costs compared to Coldline for less frequent retrieval.

C) Coldline storage is designed for infrequently accessed data, roughly once a quarter. It provides low-cost storage and high durability, making it ideal for data that must be preserved but not regularly accessed. Retrieval costs exist but are lower than Archive in scenarios where occasional access may be required. This storage class is perfectly suited for large volumes of unstructured data that need to be retained for compliance or backup purposes but accessed rarely.

D) Archive storage is the lowest-cost storage class designed for data accessed less than once a year. While it is very cost-effective for long-term storage, the retrieval process is slower and more expensive when occasional access is needed. For data that might be accessed periodically, Coldline provides a better balance between storage cost and retrieval flexibility.

Coldline is correct because it provides the ideal balance for storing large volumes of unstructured, infrequently accessed data with high durability and moderate retrieval costs. It is specifically designed for use cases like backups, archival storage, and disaster recovery data.

Question 5

You want to analyze log data from multiple Compute Engine instances in real-time and visualize patterns for troubleshooting. Which Google Cloud service should you use?

A) Stackdriver Logging (Cloud Logging) with BigQuery
B) Cloud Monitoring
C) Cloud Trace
D) Cloud Deployment Manager

Answer A) Stackdriver Logging (Cloud Logging) with BigQuery

Explanation

A) Stackdriver Logging (Cloud Logging) allows centralized collection of logs from Compute Engine instances. By exporting logs to BigQuery, you can run real-time queries and perform detailed analytics, enabling pattern detection and troubleshooting. Visualization tools such as Looker Studio can connect to BigQuery for dashboards. This combination provides a scalable, flexible, and real-time approach to log analysis, giving operational insight into system behavior, error rates, and performance trends.

B) Cloud Monitoring is used for monitoring metrics, uptime, and health of resources. It collects metrics and can generate alerts based on thresholds but does not provide log-level analytics or the ability to query log content in detail. For troubleshooting based on log data, Cloud Monitoring alone is insufficient because it focuses on metrics rather than textual log information.

C) Cloud Trace provides distributed tracing to analyze latency and performance bottlenecks in applications. While it helps identify slow requests or performance issues, it is not designed for analyzing log content across multiple instances or generating detailed textual pattern analytics. Its scope is primarily application tracing, not log aggregation.

D) Cloud Deployment Manager is an infrastructure-as-code tool for deploying and managing Google Cloud resources. It does not provide any logging or analytics capabilities. It is irrelevant to the requirement of analyzing log data or visualizing patterns.

The correct solution is using Cloud Logging with BigQuery because it allows centralized log collection, powerful query capabilities, and visualization for troubleshooting and operational insights. This combination meets the requirement for real-time analysis and pattern detection across multiple instances.

Question 6

You need to deploy a containerized application on Google Cloud and want the service to automatically scale based on HTTP traffic. Which Google Cloud service is most suitable?

A) Compute Engine
B) App Engine Standard Environment
C) Cloud Run
D) Kubernetes Engine (GKE)

Answer C) Cloud Run

Explanation

A) Compute Engine provides virtual machines that give full control over the environment. While you can deploy containers on Compute Engine, it requires manual scaling configuration and infrastructure management. It does not automatically scale based on HTTP traffic out-of-the-box, making it unsuitable for applications that require automatic, serverless scaling.

B) App Engine Standard Environment supports auto-scaling for applications, but it requires the application to fit certain runtime restrictions and scaling patterns. It is ideal for fully managed serverless apps, but Cloud Run provides greater flexibility for containerized workloads and can run any stateless container, not limited to App Engine runtime environments.

C) Cloud Run is designed for serverless containerized applications. It automatically scales based on incoming HTTP requests and scales down to zero when there is no traffic. Cloud Run supports any stateless container, making it highly flexible for modern containerized applications. This behavior directly matches the requirement for automatic scaling based on HTTP traffic without manual intervention.

D) Kubernetes Engine (GKE) provides a managed Kubernetes environment where you can deploy containers. While it offers auto-scaling features, setting up HTTP-based scaling requires configuration of Horizontal Pod Autoscalers and additional Kubernetes resources. It provides more control but also more complexity compared to Cloud Run for this specific requirement.

Cloud Run is correct because it is a fully managed serverless platform that automatically scales containerized applications based on HTTP traffic, offering simplicity and flexibility without requiring infrastructure management.

 

Question 7

You want to enable secure communication between two VPC networks in Google Cloud without using public IP addresses. Which solution should you implement?

A) VPC Peering
B) Cloud VPN
C) Cloud NAT
D) Shared VPC

Answer A) VPC Peering

Explanation

A) VPC Peering allows direct private connectivity between two VPC networks using internal IP addresses. It enables resources in different VPCs to communicate securely without exposing traffic to the public internet. Peering provides low-latency, high-bandwidth connectivity while maintaining isolation of each VPC. This aligns perfectly with the requirement of private communication without public IPs.

B) Cloud VPN provides encrypted communication over the public internet. While it is secure, it relies on the internet for connectivity, which may introduce latency or performance variability. It is suitable for hybrid connections but not ideal for private intra-cloud connectivity that requires internal IPs only.

C) Cloud NAT enables instances in private subnets to access the internet while hiding their internal IP addresses. It does not provide connectivity between two VPCs, so it does not meet the requirement of private communication between networks.

D) Shared VPC allows multiple projects to connect to a common VPC managed by a host project. While it enables centralized networking and resource sharing, it does not establish private connectivity between two separate VPCs that are in different host projects. It is more about resource management than private network connectivity.

VPC Peering is correct because it establishes private, internal IP-based connectivity between two VPC networks without relying on the public internet, fulfilling the requirement for secure intra-cloud communication.

Question 8

You need to monitor CPU utilization, memory usage, and disk I/O of Compute Engine instances and receive alerts when thresholds are exceeded. Which Google Cloud service should you use?

A) Cloud Logging
B) Cloud Monitoring
C) Cloud Trace
D) Cloud Audit Logs

Answer B) Cloud Monitoring

Explanation

A) Cloud Logging collects and stores logs from Google Cloud resources. While logs may contain metrics, it is not a monitoring solution and does not provide automated alerts based on threshold metrics. Using only Cloud Logging would require manual log analysis, which is inefficient for real-time monitoring.

B) Cloud Monitoring is specifically designed to collect metrics from Compute Engine instances, including CPU utilization, memory, and disk I/O. It allows users to set up alerting policies for specific thresholds, providing notifications when usage exceeds defined limits. This enables proactive monitoring and rapid response to performance issues. It also supports dashboards for visualizing trends over time, making it the correct tool for this requirement.

C) Cloud Trace is designed to provide distributed tracing for analyzing application latency and performance bottlenecks. It is not meant for infrastructure monitoring or generating alerts based on system metrics like CPU or disk usage.

D) Cloud Audit Logs track administrative and data access events for compliance and auditing purposes. They do not provide real-time system metrics or alerting capabilities, so they are unsuitable for monitoring CPU, memory, or disk I/O.

Cloud Monitoring is correct because it provides real-time collection of system metrics, threshold-based alerting, and visualization dashboards, making it ideal for monitoring Compute Engine performance.

Question 9

You need to move a large dataset from an on-premises data center to Google Cloud Storage with minimal network impact. Which tool is most appropriate?

A) gsutil cp
B) Cloud Storage Transfer Service
C) Storage Gateway
D) Cloud Pub/Sub

Answer B) Cloud Storage Transfer Service

Explanation

A) gsutil cp allows copying files from on-premises systems to Cloud Storage using the command line. While it works for small datasets, it is inefficient for large-scale transfers and does not provide scheduling, bandwidth throttling, or retry mechanisms for large datasets, which may impact network performance.

B) Cloud Storage Transfer Service is designed for large-scale data transfers into Cloud Storage. It supports scheduled and recurring transfers, bandwidth throttling, and automatic retries, minimizing network impact while ensuring reliable and efficient migration. It is the best choice for moving large datasets with minimal disruption.

C) Storage Gateway is not a Google Cloud service. This option is generally associated with hybrid storage solutions on other platforms and does not apply directly to Google Cloud for large-scale bulk transfer.

D) Cloud Pub/Sub is an event messaging service and not intended for bulk data transfer. It is used for streaming data pipelines and message distribution, not moving large datasets efficiently.

Cloud Storage Transfer Service is correct because it is built to handle large-scale, reliable, and efficient data transfers from on-premises to Cloud Storage, minimizing network impact while providing features like scheduling, throttling, and automatic retries.

Question 10

You want to allow multiple teams to use a single Google Cloud project while isolating resources and permissions between teams. Which Google Cloud feature should you use?

A) Shared VPC
B) VPC Peering
C) Project IAM roles
D) Service Accounts

Answer A) Shared VPC

Explanation

A) Shared VPC allows multiple projects to connect to a centrally managed VPC in a host project. Teams can deploy resources in their own service projects while sharing network resources like subnets, firewall rules, and VPNs from the host project. This allows resource isolation per team while maintaining centralized control over networking and security, matching the requirement perfectly.

B) VPC Peering allows private connectivity between two VPCs but does not provide a mechanism for resource or permission isolation between multiple teams using a single project. It is purely a networking solution.

C) Project IAM roles control access to Google Cloud resources at the project level. While IAM roles are necessary for permission management, they do not inherently provide resource isolation between teams within the same project. Without additional projects or Shared VPC, teams may inadvertently access each other’s resources.

D) Service Accounts provide identity for applications or workloads but do not manage resource isolation between multiple teams. They are used for authentication and permission assignment, not for segregating resources across teams.

Shared VPC is correct because it allows teams to deploy resources in their own service projects while sharing the host project’s network infrastructure, enabling both resource isolation and centralized control.

Question 11

You want to configure a Google Cloud SQL instance for a production application that requires high availability and automatic failover. Which configuration should you choose?

A) Single-zone primary instance
B) Regional high-availability (HA) instance
C) Read replica in a different region
D) Standalone instance with backups

Answer  B) Regional high-availability (HA) instance

Explanation

A) A single-zone primary instance runs entirely in one zone within a region. While it provides standard availability and performance, it does not offer automatic failover if the zone goes down. In production environments where uptime is critical, relying solely on a single-zone instance can lead to service interruptions during planned maintenance or unexpected outages. Although backups may protect data, the lack of automated failover makes this choice insufficient for high-availability requirements.

B) A regional high-availability (HA) instance provides automatic failover between two zones within a region. It uses synchronous replication to maintain a standby instance in a different zone. If the primary zone becomes unavailable, the system automatically fails over to the standby instance with minimal disruption. This ensures both high availability and durability of data for production workloads. Additionally, HA instances support automated backups and maintenance updates, allowing operations teams to maintain the instance without significant downtime. This configuration directly meets the requirement for production environments that demand minimal service interruptions.

C) A read replica in a different region is primarily intended for scaling read operations rather than ensuring high availability. While cross-region read replicas can improve read performance and provide disaster recovery options, they do not automatically handle failover for the primary instance. In case of a primary instance failure, manual intervention is required to promote a replica, which may not satisfy strict uptime requirements. Therefore, using read replicas alone is not sufficient for production-level high availability.

D) A standalone instance with backups ensures that data can be restored in case of failure, but recovery is manual and can take time depending on the size of the database. It does not provide automatic failover or high-availability guarantees. While backups are essential for data protection, relying solely on a standalone instance with backups is inadequate for production environments where continuous availability is a priority.

The correct choice is a regional high-availability instance because it provides automatic failover, synchronous replication, and redundancy across zones within the same region. This configuration ensures that production applications continue running even if a zone fails, minimizing downtime and adhering to best practices for critical workloads. Using HA instances also simplifies management since Google Cloud handles the replication, failover, and updates, allowing teams to focus on application development rather than infrastructure reliability.

Question 12

Your team needs to deploy multiple microservices that require independent scaling, automatic HTTPS, and stateless execution. Which Google Cloud service is most appropriate?

A) Compute Engine
B) App Engine Standard Environment
C) Cloud Run
D) Kubernetes Engine (GKE)

Answer  C) Cloud Run

Explanation

A) Compute Engine provides virtual machines for deploying applications. While it allows full control over scaling and deployment, automatic scaling and HTTPS management are not provided out-of-the-box. Each microservice would require manual configuration for load balancing, SSL certificates, and scaling policies. This introduces complexity and operational overhead, making Compute Engine less ideal for stateless, microservice-based workloads requiring independent scaling.

B) App Engine Standard Environment is fully managed and provides automatic scaling and HTTPS. However, it supports only certain runtime environments and has limitations in container flexibility. If microservices rely on custom containerized workloads or non-standard libraries, App Engine Standard may impose restrictions, making it less flexible than Cloud Run for fully containerized microservices.

C) Cloud Run is a fully managed platform for containerized applications. It automatically scales each container instance independently based on incoming requests and scales down to zero when idle. Cloud Run also provides built-in HTTPS, serverless execution, and stateless behavior, making it ideal for microservices architecture. Each microservice can be deployed as a separate container, allowing independent scaling and management without affecting other services. Additionally, Cloud Run integrates with CI/CD pipelines, monitoring, and logging tools, which facilitates operational efficiency and observability across microservices.

D) Kubernetes Engine (GKE) allows orchestration of containerized applications and provides flexibility in scaling, networking, and deployments. While GKE can support microservices with automatic scaling and HTTPS via ingress controllers, it requires significant operational management, including cluster provisioning, node management, scaling policies, and monitoring setup. For teams looking for simplicity and fully managed scaling per service, Cloud Run provides the required functionality with less operational overhead.

Cloud Run is correct because it combines container flexibility with serverless management. It ensures independent scaling, automatic HTTPS, stateless execution, and minimal operational complexity. This service allows teams to deploy microservices efficiently while focusing on application logic rather than infrastructure management.

Question 13

You are designing a logging and monitoring solution for a Google Cloud application. You need to collect logs, metrics, and traces to troubleshoot performance issues and generate alerts. Which combination of services should you use?

A) Cloud Logging, Cloud Monitoring, Cloud Trace
B) Cloud Monitoring and Cloud IAM
C) Cloud Logging only
D) Cloud Storage and Cloud Pub/Sub

Answer  A) Cloud Logging, Cloud Monitoring, Cloud Trace

Explanation

A) Cloud Logging provides centralized log collection from Google Cloud resources and applications. It allows you to analyze logs, filter by specific attributes, and export logs to external storage or BigQuery for advanced analytics. Cloud Monitoring collects and visualizes metrics, including CPU, memory, disk, and network usage. It enables alerting based on thresholds, providing proactive monitoring capabilities. Cloud Trace collects distributed traces across application requests, helping identify latency bottlenecks and performance issues. Using all three together gives a comprehensive observability solution: logs provide detailed event information, metrics quantify system performance, and traces highlight request-level performance problems. This combination allows teams to troubleshoot effectively, detect anomalies, and respond proactively to incidents.

B) Cloud Monitoring and Cloud IAM alone are insufficient. Cloud Monitoring collects metrics and supports alerts, but without Cloud Logging, you cannot analyze detailed log events. Cloud IAM provides access control but does not contribute to performance observability or troubleshooting. This combination lacks the depth required for comprehensive analysis.

C) Cloud Logging alone captures logs but does not provide metrics visualization, automated alerts, or tracing capabilities. Without Cloud Monitoring and Cloud Trace, teams cannot identify performance trends or latency issues effectively. Logs alone may provide raw data but not actionable insight in real time.

D) Cloud Storage and Cloud Pub/Sub do not meet the requirements. Cloud Storage stores data but is not an analytics or monitoring tool. Cloud Pub/Sub is a messaging service that enables event-driven communication but does not provide metrics, logs, or trace analysis for troubleshooting application performance.

The correct choice is the combination of Cloud Logging, Cloud Monitoring, and Cloud Trace. Together, they provide a full-stack observability solution, offering logs for detailed events, metrics for system performance, and traces for latency and bottleneck analysis. This integrated approach ensures teams can proactively manage performance, generate alerts, and quickly troubleshoot production issues. It also aligns with Google Cloud best practices for building reliable, observable systems.

Question 14

Your company wants to implement a data retention policy that keeps infrequently accessed logs for seven years while minimizing storage costs. Which Cloud Storage class should you use?

A) Standard
B) Nearline
C) Coldline
D) Archive

Answer  D) Archive

Explanation

A) Standard storage is intended for frequently accessed data and provides low-latency, high-throughput access. While it ensures high durability, the cost is significantly higher than cold storage classes. Using Standard for long-term retention of rarely accessed logs is not cost-effective.

B) Nearline storage is for data accessed roughly once a month. While cheaper than Standard, Nearline is better suited for backup and disaster recovery with occasional access. Seven-year retention of logs would result in higher costs than using deeper cold storage classes.

C) Coldline storage is optimized for infrequently accessed data, approximately once a quarter. It provides lower storage costs than Nearline and Standard, making it more suitable for long-term retention. However, for a seven-year retention period, Archive storage is even more cost-effective while providing high durability and long-term access options.

D) Archive storage is designed for long-term retention of data accessed less than once a year. It offers the lowest storage cost among all Cloud Storage classes while maintaining high durability and availability. Retrieval is slightly slower and incurs minimal costs, which is acceptable for infrequently accessed logs. Archive is ideal for compliance, regulatory retention, and cost-optimized long-term storage of logs over multiple years.

Archive is correct because it provides a cost-efficient, durable solution for storing logs for seven years with minimal access requirements. This aligns with compliance standards, reduces operational costs, and ensures that logs are available if needed for audits or analysis.

Question 15

You need to provide temporary access to a third-party contractor for deploying applications to a Google Cloud project without sharing your credentials. What is the best approach?

A) Share your user credentials
B) Create a new IAM user with minimal privileges
C) Use a service account with temporary keys
D) Use Cloud Identity and Access Management with IAM roles

Answer D) Use Cloud Identity and Access Management with IAM roles

Explanation

A) Sharing your user credentials is highly insecure and violates the principle of least privilege. It exposes the project to potential misuse or accidental changes by the contractor. This practice is not recommended for any environment, particularly production workloads.

B) Creating a new IAM user with minimal privileges provides some isolation but does not handle temporary access effectively. Google Cloud IAM is not designed to create individual user accounts for short-term external contractors without additional management overhead.

C) Using a service account with temporary keys can allow programmatic access, but sharing keys requires careful handling, and key rotation must be managed. While feasible for automation, service accounts are not ideal for granting controlled temporary interactive access to a contractor.

D) Cloud Identity and Access Management with IAM roles allows you to assign granular roles to users or groups, defining exactly what actions they can perform. You can grant temporary access using IAM policies and remove it once the contractor’s work is complete. This ensures security, adheres to the principle of least privilege, and provides centralized auditing and monitoring of all actions. IAM roles provide flexibility, enforce security best practices, and prevent accidental exposure of credentials.

Using IAM roles is correct because it provides secure, temporary, and auditable access for contractors without sharing credentials. It ensures proper privilege management and aligns with Google Cloud’s best practices for secure access control.

Question 16

You want to set up a serverless data processing pipeline that ingests events in real time from multiple sources, transforms them, and loads them into BigQuery for analytics. Which combination of Google Cloud services is best suited for this purpose?

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 serverless workloads, such as processing individual events or files uploaded to Cloud Storage. Cloud Functions can trigger on Cloud Storage events, run lightweight code, and store results back in Cloud Storage or other services. However, this combination is not ideal for high-volume, continuous data streams from multiple sources. It lacks efficient handling of streaming pipelines, scaling capabilities for complex transformations, and direct integration with BigQuery for real-time analytics. Using Cloud Functions alone may result in higher operational complexity, as it would require orchestrating multiple functions, handling event ordering, and scaling logic manually.

B) Cloud Pub/Sub is a messaging service that ingests and buffers events from multiple sources reliably and asynchronously. It ensures that messages are delivered to downstream services with at-least-once delivery semantics. Cloud Dataflow is a fully managed stream and batch data processing service that integrates seamlessly with Pub/Sub. It can perform complex transformations, aggregations, and enrichments in real-time, using the Apache Beam programming model. Dataflow automatically scales based on workload, handling high-throughput streams efficiently. Finally, BigQuery serves as a highly scalable analytical data warehouse for storing transformed data, supporting fast SQL queries and business intelligence workflows. This combination provides an end-to-end serverless solution that handles ingestion, transformation, and analytics at scale, with minimal operational overhead.

C) Cloud Run and Cloud SQL provide a containerized, serverless execution environment and relational storage, respectively. While Cloud Run can handle stateless workloads and scale automatically, Cloud SQL is not optimized for high-throughput, real-time analytical workloads. Using Cloud Run to process streaming data would require additional orchestration for message ingestion and batching, which adds complexity. Cloud SQL does not support efficient streaming ingestion at scale, making it less suitable for this use case.

D) Compute Engine and Cloud Bigtable provide customizable infrastructure and a NoSQL database. Compute Engine offers flexibility but requires manual management of scaling, load balancing, and orchestration for event processing. Cloud Bigtable is suitable for high-throughput NoSQL workloads but is not ideal for SQL-style analytics or complex data transformations that BigQuery can handle efficiently. This combination would involve significant operational overhead for a serverless, real-time pipeline.

The correct combination is Cloud Pub/Sub, Cloud Dataflow, and BigQuery. Pub/Sub ensures reliable event ingestion from multiple sources, Dataflow provides scalable and automated stream processing with real-time transformations, and BigQuery enables fast analytics and visualization. Together, they form a serverless, end-to-end pipeline that minimizes operational complexity while supporting high-volume, real-time data processing. This architecture adheres to cloud-native best practices, reduces maintenance overhead, and provides scalability, reliability, and observability for enterprise-grade pipelines.

Question 17

You need to provide secure access to a Cloud Storage bucket for multiple teams with different access requirements: some need read-only, some read-write, and some temporary access. Which approach is most appropriate?

A) Share bucket credentials directly
B) Use IAM roles and signed URLs
C) Enable public access to the bucket
D) Use Cloud Storage Transfer Service

Answer B) Use IAM roles and signed URLs

Explanation

A) Sharing bucket credentials directly, such as service account keys or personal access keys, is insecure and violates the principle of least privilege. It exposes sensitive credentials to multiple users, risking unauthorized access or accidental data deletion. This method is not recommended for enterprise or production environments, especially when different teams require different levels of access or temporary permissions.

B) Using IAM roles and signed URLs provides granular access control and secure temporary access. IAM roles allow assigning specific permissions such as Storage Object Viewer for read-only access or Storage Object Admin for read-write access. Teams receive exactly the permissions they need, adhering to least-privilege principles. Signed URLs provide temporary access to objects in a bucket without creating a permanent user or exposing credentials. They can have expiration times ranging from minutes to days, allowing contractors or external partners to perform tasks securely. This combination ensures both security and flexibility, allowing multiple teams to interact with the same bucket according to their specific access requirements.

C) Enabling public access to the bucket allows anyone with the link to access the data, which is highly insecure. It does not provide the ability to differentiate access levels between teams, nor does it allow for temporary access control. Public buckets are generally reserved for content intended for public consumption, such as hosting static website assets, and are unsuitable for internal team collaboration or sensitive data.

D) Cloud Storage Transfer Service is designed for moving large volumes of data from one location to another, such as migrating on-premises storage to Cloud Storage. It is not intended to manage access control for multiple users or teams. While it can move data securely, it does not address the requirement of providing different types of access to different users.

The correct choice is using IAM roles and signed URLs. IAM roles enable precise permission assignment for each team, ensuring that read-only users cannot modify data and read-write users can perform necessary operations. Signed URLs complement IAM by providing secure, temporary access for external collaborators without sharing permanent credentials. This approach ensures security, flexibility, and compliance while reducing operational complexity and risk of accidental exposure. By leveraging Google Cloud’s IAM and signed URL capabilities, organizations can enforce consistent access policies, maintain auditability, and accommodate different workflows seamlessly.

 

Question 18

You need to migrate an on-premises MySQL database to Cloud SQL with minimal downtime. Which approach should you use?

A) Export to SQL dump and import
B) Use Database Migration Service (DMS)
C) Recreate the schema manually and copy data
D) Use Cloud Storage Transfer Service

Answer B) Use Database Migration Service (DMS)

Explanation

A) Exporting the database to a SQL dump and importing it into Cloud SQL works for small datasets or non-production migrations. However, this approach requires downtime during the export and import processes, as changes made to the source database after the export are not captured. For production workloads requiring minimal downtime, this method is insufficient because it does not support continuous replication or incremental updates.

B) Database Migration Service (DMS) is a fully managed tool designed to migrate relational databases to Cloud SQL with minimal downtime. It supports continuous data replication from the source database while keeping it operational. DMS can handle schema migration, initial data seeding, and ongoing replication until the final cutover, allowing a near-zero downtime migration. It also provides monitoring and logging, helping teams track migration progress and detect issues. This approach ensures a smooth transition from on-premises MySQL to Cloud SQL while maintaining business continuity.

C) Recreating the schema manually and copying data is time-consuming and error-prone. It requires manual effort to ensure the schema matches exactly, and any mistakes can lead to application failures. Additionally, this method cannot handle continuous replication, making it unsuitable for minimal downtime migrations. It also requires careful validation of data integrity, adding operational risk.

D) Cloud Storage Transfer Service is designed for bulk data transfers between storage systems. It is not intended for database migrations, as it cannot maintain transactional integrity, handle schema conversions, or replicate ongoing changes. Using it for database migration would be impractical and would likely result in inconsistent or incomplete data.

The correct choice is Database Migration Service because it provides a fully managed, near-zero downtime migration path. DMS ensures continuous replication, handles schema conversion, and integrates with Cloud SQL monitoring and logging. By using DMS, organizations can migrate critical production databases to Cloud SQL safely, reliably, and efficiently without disrupting operations. It reduces risk, saves operational time, and adheres to best practices for cloud migrations.

Question 19

You need to configure a VPC network where certain subnets should have public internet access and others should remain private. Which combination of services is most appropriate?

A) Cloud NAT and firewall rules
B) VPC Peering and Cloud Interconnect
C) Cloud CDN and Cloud Load Balancing
D) Shared VPC only

Answer A) Cloud NAT and firewall rules

Explanation

A) Cloud NAT (Network Address Translation) allows instances in private subnets to access the internet for outbound connections without exposing their internal IP addresses. Firewall rules control ingress and egress traffic for subnets and instances, providing security and access control. By combining Cloud NAT and firewall rules, you can configure some subnets to remain private while allowing controlled internet access for others. This setup ensures network security while enabling necessary connectivity. Cloud NAT handles outbound traffic for private subnets, while firewall rules allow administrators to specify allowed IPs, protocols, and ports, meeting both privacy and connectivity requirements.

B) VPC Peering enables private connectivity between two VPCs but does not provide internet access. It is primarily used for secure, internal network communication, not for controlling public versus private subnet access. This solution does not satisfy the requirement of managing internet access.

C) Cloud CDN and Cloud Load Balancing optimize content delivery and distribute traffic for web applications. While useful for performance and high availability, they do not provide mechanisms to make certain subnets public or private. They are application-level solutions rather than network access control mechanisms.

D) Shared VPC allows multiple projects to connect to a centrally managed VPC. While it provides centralized network management and shared resources, it does not inherently manage private versus public subnet access. Additional services, such as Cloud NAT and firewall rules, are required to meet this requirement.

The correct choice is Cloud NAT and firewall rules because they provide control over outbound and inbound traffic. Private subnets can remain hidden from the internet while still allowing secure outbound connections via NAT. Firewall rules enforce security policies, specifying which traffic is allowed or denied. This combination ensures that network segmentation and access control are implemented effectively, aligning with security best practices and operational needs.

Question 20

You are designing a disaster recovery plan for a mission-critical application deployed in Google Cloud. You need to ensure that the application can be restored quickly in case of a region-wide outage. Which architecture best meets this requirement?

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

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

Explanation

A) Single-region deployment with automated backups ensures data durability and recovery from accidental deletion or instance failure. However, it does not protect against region-wide outages. In case the entire region becomes unavailable due to a disaster, the application will experience downtime until resources can be restored in another region. Backups help recover data but do not provide high availability or rapid failover across regions.

B) Multi-region deployment with active-active instances involves running instances of the application simultaneously in multiple regions. Traffic can be distributed across regions using global load balancers. In case one region becomes unavailable, traffic automatically routes to healthy instances in other regions. This setup ensures high availability, near-zero downtime, and fast recovery. Active-active architecture also provides resilience against region-level failures while maintaining operational continuity and performance. It aligns with disaster recovery best practices, meeting RTO (Recovery Time Objective) and RPO (Recovery Point Objective) requirements for mission-critical applications.

C) Single-region deployment with snapshots provides backup points to restore the system if needed. Snapshots capture the state of storage volumes or databases but cannot provide real-time failover. Recovery requires manually restoring instances in a different region, which increases downtime and may violate recovery objectives. This approach does not meet the rapid disaster recovery requirement.

D) Deploying only in a private zone with VPC Peering ensures internal connectivity but does not provide regional redundancy or disaster recovery. If the region hosting the private zone fails, the application will be unavailable. VPC Peering facilitates secure network communication but does not inherently offer recovery capabilities or high availability across regions.

The correct approach is multi-region deployment with active-active instances. This architecture ensures continuous availability by distributing workloads across regions and using load balancing to route traffic to healthy instances. It provides resilience against regional outages, fast recovery, and operational continuity. By implementing active-active deployment, organizations achieve high availability, disaster tolerance, and compliance with stringent business continuity requirements.