This comprehensive guide delves into the nuances of the Google Cloud Certified Associate Cloud Engineer exam, offering insights into its structure, content, and the expertise required to excel. Designed for aspiring cloud professionals, this resource provides a deep dive into the core responsibilities of an Associate Cloud Engineer and equips you with the knowledge to confidently approach the certification.

The Role of a Google Associate Cloud Engineer: A Foundation for Cloud Mastery

A Google Associate Cloud Engineer serves as a pivotal figure in modern IT environments, bridging the gap between development and operations within the Google Cloud ecosystem. Their primary responsibilities encompass the administration of corporate cloud solutions, the meticulous implementation of applications, and the diligent monitoring of operational workflows. These professionals are adept at leveraging both the Google Cloud Console and the command-line interface (CLI) to execute a myriad of routine platform-based tasks. Their purview extends to maintaining one or more host systems on Google Cloud, irrespective of whether these systems employ Google-managed or self-managed technologies. In essence, an Associate Cloud Engineer is the bedrock of cloud infrastructure, ensuring its stability, scalability, and security.

Navigating the Google Associate Cloud Engineer Exam: Expectations and Evaluation Criteria

The Google Cloud Certified Associate Cloud Engineer examination is meticulously crafted to assess a candidate’s proficiency across several critical domains. These assessments gauge your aptitude in:

• Architecting a Cloud Solution Infrastructure: This involves understanding and applying best practices for designing scalable, resilient, and cost-effective cloud architectures on Google Cloud. It necessitates a solid grasp of core GCP services and their interrelationships.
• Creating and Managing Cloud Solutions: This domain focuses on the practical aspects of deploying and overseeing cloud resources. Candidates are expected to demonstrate competence in provisioning, configuring, and maintaining various GCP services.
• Implementing and Configuring Cloud Solutions: This section evaluates your ability to translate architectural designs into tangible cloud deployments. It emphasizes hands-on skills in setting up and customizing GCP services to meet specific project requirements.
• Ensuring Seamless Cloud Solution Operation: This crucial area assesses your capacity for monitoring, troubleshooting, and optimizing deployed cloud solutions. It covers aspects like performance management, logging, and incident response within the GCP environment.
• Configuring Authentication and Accessibility: Security is paramount in the cloud, and this domain examines your understanding of identity and access management (IAM) principles within Google Cloud. Candidates should be proficient in configuring granular access controls and ensuring secure interactions with cloud resources.

The Rigor of the Google Associate Cloud Engineer Exam: Strategies for Success

The Google Associate Cloud Engineer exam presents a formidable challenge, demanding both theoretical understanding and practical application of Google Cloud concepts. While it’s not an easy certification to acquire, with diligent preparation, success is well within reach. To maximize your chances of passing, consider these indispensable strategies:

1. Deconstruct the Exam Objectives: Before embarking on your study journey, it’s imperative to thoroughly comprehend the official exam objectives. This foundational step will serve as your compass, guiding your studies and allowing you to anticipate the types of questions you’ll encounter. A granular understanding of each objective ensures your preparation is targeted and efficient.

2. Harness Diverse Study Resources: The landscape of Google Cloud certification resources is rich and varied. Leverage a multiplicity of study materials, including official Google Cloud documentation, online courses, video tutorials, and dedicated study guides. Supplementing your learning with insights from diverse sources can provide a more holistic understanding of the subject matter.

3. Embrace Extensive Practice: Theoretical knowledge alone is insufficient. The Google Associate Cloud Engineer exam heavily emphasizes practical application. Engage in copious practice by tackling Google Cloud certification sample questions and participating in hands-on exercises. The more you immerse yourself in practical scenarios, the more adept you’ll become at navigating the intricacies of Google Cloud. Consider utilizing reputable platforms that offer Associate Cloud Engineer practice exams to simulate the actual testing environment.

4. Prioritize Adequate Rest: The importance of sufficient rest before a high-stakes exam cannot be overstated. A well-rested mind is a focused mind, capable of clearer thought and optimal performance. Ensure you get ample sleep in the days leading up to your exam to enhance your cognitive functions and recall abilities.

5. Cultivate a Positive Mindset: Self-belief is a powerful catalyst for success. Maintain a positive outlook throughout your preparation and on exam day. Avoid succumbing to discouragement and trust in your ability to achieve your goal. With proper preparation and a resilient spirit, you are well-equipped to pass the Google Associate Cloud Engineer exam.

Google Associate Cloud Engineer Exam Questions: A Curated Collection for Practice

To help you acclimate to the characteristics and demands of the Google Cloud Certified Associate Cloud Engineer (GCP-ACE) certification, we’ve compiled a set of practice questions. This collection offers insights into the exam’s pattern, question format, difficulty level, and the estimated time required for each question. This selection of sample questions provides a valuable preview of the GCP Associate Cloud Engineer test design, the types of inquiries posed, and effective strategies for passing the Google Associate Cloud Engineer exam on your initial attempt.

Establishing a Cloud Solution Environment

Question 1: Which gcloud command is used to set the default zone for a Compute Engine server using the gcloud command-line interface?

1. gcloud config set compute/zone us-east-1 B. gcloud config configurations set compute/zone us-east-1a C. gcloud config set compute/zone us-east1-a D. gcloud defaults set compute/zone us-east-1

Correct Answer: C

The correct gcloud command to establish the default zone for a Compute Engine instance is gcloud config set compute/zone us-east1-a. Therefore, option C is the accurate response. Options A, B, and D are incorrect as they do not represent valid gcloud commands for configuring the default Compute Engine zone. This question tests your familiarity with the fundamental gcloud commands essential for setting up your cloud environment efficiently.

Question 2: As a cloud engineer, you have been tasked with upgrading your account’s free trial to a production-tier subscription and subsequently renaming it to “production-inventory-system.” During this process, you encounter a “permission denied” error. Which of the following permissions would resolve this issue?

1. Billing.accounts.update B. Billing.account.upgrade C. Billing.account.update D. Billing.accounts.upgrade

Correct Answer: A

Option A is the correct answer. The necessary permission required to modify billing account details, including upgrading and renaming, is billing.accounts.update on the Billing Account resource. Options B, C, and D are either invalid choices or incorrect command syntax for this operation. This question highlights the importance of understanding IAM permissions within Google Cloud, particularly in the context of billing and account management.

Question 3: Which of the following roles provides granular access for a specific service and is managed directly by Google Cloud Platform?

1. Custom B. Predefined C. Admin D. Primitive

Correct Answer: B

Option B is correct. Predefined roles are managed roles provided by Google Cloud and offer service-specific access, allowing for fine-grained control over resources. Option A is incorrect because custom roles provide granular access for a specific service but are managed by users, not GCP. Option C is incorrect as “Admin” is not a distinct role type in this context; it’s a general category that can apply to various roles. Option D is incorrect as “Primitive” roles refer to older, broader roles that existed prior to the more granular IAM system. This question assesses your knowledge of IAM roles and their categories within GCP.

Question 4: Your company stores 5 TB of testing data in the production database of a testing tool named Quality Center. This data is currently being used to generate a real-time analytics system, which is leading to slow response times for testers utilizing the tool. What action should you take to alleviate the load on the database?

1. Set up Multi-AZ B. Set up a read replica C. Scale the database instance D. Run the analytics query only weekends

Correct Answer: B

Option B is correct. Implementing a read replica is the most effective solution in this scenario. A read replica can be dedicated to running all queries related to the analytics system, thereby offloading the read burden from the primary production database and improving its responsiveness for testers. Option A, setting up Multi-AZ, would primarily enhance data availability and disaster recovery, but wouldn’t directly address the performance impact of analytical queries. Option C, scaling the database instance, might offer some temporary relief but is not the most efficient or targeted solution for separating read workloads. Option D, running analytics queries only on weekends, would prevent real-time analytics, which is a stated requirement, and wouldn’t solve the underlying architectural issue during weekdays. This question evaluates your understanding of database optimization strategies in a cloud environment.

Question 5: You have been asked to list the name of the active account using the gcloud command-line interface. Which of the following commands would you use?

1. Gcloud config list B. Gcloud auth list C. Gcloud account list D. Gcloud project list

Correct Answer: B

Option B is correct. To display the name of the currently active gcloud account, the gcloud auth list command is used. Option A, gcloud config list, is used to enumerate all properties of the active gcloud configuration. Option C, gcloud account list, is an invalid command. Option D, gcloud project list, is used to display all active projects accessible to your account. This question tests your practical knowledge of fundamental gcloud commands for managing your authentication and project context.

Architecting and Planning a Cloud Solution

Question 6: What does the CIDR 10.0.2.0/26 correspond to?

10. 10.0.2.0 – 10.0.2.26 B. 10.0.2.0 – 10.0.2.63 C. 10.0.0.0 – 10.0.63.0 D. 10.0.2.0 – 10.0.0.26

Correct Answer: B

Option B is correct. A /26 CIDR notation signifies that the first 26 bits of the IP address are fixed, leaving the remaining 32−26=6 bits for host addresses. This allows for 26=64 possible IP addresses within the subnet. For the given network address 10.0.2.0, the range of IP addresses will be from 10.0.2.0 (network address) to 10.0.2.63 (broadcast address). Options A, C, and D are incorrect CIDR choices that do not accurately reflect the /26 subnet calculation. This question tests your understanding of CIDR notation, a crucial concept for network planning in cloud environments.

Question 7: A cloud engineer intends to create a virtual machine (VM) named whiz-server-1 equipped with four CPUs. Which of the following commands would they utilize to instantiate the VM whiz-server-1?

1. gcloud compute instances create –machine-type=n1-standard-4 whiz-server-1 B. gcloud compute instances create –cpus=4 whiz-server-1 C. gcloud compute instances create –machine-type=n1-standard-4 –instancename whiz-server-1 D. gcloud compute instances create –machine-type=n1-4-cpu whiz-server-1

Correct Answer: A

To create a Google Cloud Compute Engine virtual machine instance, the gcloud compute instances create command is employed. The number of CPUs is specified through the machine-type parameter. For a comprehensive list of available machine types, one can use gcloud compute machine-types list. If no machine type is explicitly defined, the default is n1-standard-1. In this scenario, since the cloud engineer requires four CPUs, the appropriate machine type is n1-standard-4, followed by the VM’s designated name.

Option A is correct. gcloud compute instances create –machine-type=n1-standard-4 whiz-server-1 is the accurate command to create a VM with four CPUs. It correctly specifies the machine type and appropriately provides the instance’s name as an argument.

Option B is incorrect. The command gcloud compute instances create –cpus=4 whiz-server-1 is flawed because the cpus parameter does not exist within the Google Cloud command syntax for instance creation.

Option C is incorrect. The command gcloud compute instances create –machine-type=n1-standard-4 –instance-name whiz-server-1 is not the proper way to create a VM instance. It incorrectly uses the instance-name parameter, which is not a valid argument for this command; the instance name is passed directly as a positional argument.

Option D is incorrect. gcloud compute instances create –machine-type=n1-4-cpu whiz-server-1 is not a valid command to create a VM instance. The specified machine type, n1-4-cpu, is incorrect; the correct machine type for a standard four-CPU instance is n1-standard-4. This question assesses your detailed understanding of gcloud commands for Compute Engine instance provisioning and the correct machine type specifications.

Question 8: You have configured a firewall rule intended to permit inbound connections to a virtual machine instance named whizserver-2. You wish for this rule to apply only if no other existing rule would explicitly deny that specific traffic. What priority should you assign to this firewall rule?

1. 1000 B. 1 C. 65535 D. 0

Correct Answer: C

If the firewall rule is to have the lowest possible priority, thereby allowing other matching rules to take precedence, it should be assigned the highest numerical value. In Google Cloud firewall rules, a larger number denotes a lower priority. To ensure that other rules matching the traffic are applied first, the largest permissible number should be chosen for the priority.

Option A is incorrect. 1000 is not the largest number among the provided options. For the lowest priority, the largest number is required.

Option B is incorrect. 1 is a very small number, which would result in a very high priority. Thus, it is not the correct answer for achieving the lowest priority.

Option C is correct. 65535 represents the largest permissible numerical value within the range of priorities for Google Cloud firewall rules. Assigning this value ensures the rule has the lowest possible priority, allowing other rules to be evaluated and applied first.

Option D is incorrect. A lower numerical value signifies a higher priority. Assigning 0 would result in the highest priority, which is contrary to the requirement of setting the lowest priority. This question tests your understanding of firewall rule priorities and their impact on traffic flow within a Google Cloud Virtual Private Cloud (VPC).

Question 9: You want your application, hosted on a VM, to retrieve the metadata of that specific instance. Which command will assist you in fetching this information?

1. curl metadata.google.internal/compute-metadata/v1/ B. curl <instance-private-ip>/metadata/v1/ C. curl metadata.google.internal/computeMetadata/v1/ D. curl internal.googleapi.com/computeMetadata/v1/

Correct Answer: C

The correct command to fetch instance metadata is curl metadata.google.internal/computeMetadata/v1/. Therefore, option C is the accurate response. Options A, B, and D are incorrect as they do not represent valid gcloud commands or the correct metadata server URL for this purpose. This question assesses your knowledge of how to access and retrieve metadata from Google Cloud Compute Engine instances, which is crucial for dynamic application configurations and operational insights.

Question 10: You possess 100TB of non-relational data and aim to perform analytics on it to discern the net sales from the previous year. Which tool is best suited for your requirement?

1. BigQuery B. BigTable C. Datastore D. GCS

Correct Answer: B

Option B is correct. BigTable is a fully managed NoSQL database service specifically engineered for the efficient handling and processing of vast quantities of data, making it ideal for analytical workloads on non-relational datasets. Option A, BigQuery, is a relational database service designed for data warehousing and analytics on structured data, thus it is not suitable for directly storing non-relational data in this context. Option C, Datastore (now Firestore in Datastore mode), is also a NoSQL managed database service, but while it can handle non-relational data, 100TB is generally considered a very large scale for Datastore to process with optimal efficiency for this specific analytical workload. Option D, Google Cloud Storage (GCS), is primarily used for storing various file types and objects; it does not offer direct analytical capabilities on the stored data itself without integration with other services. This question tests your understanding of Google Cloud’s data storage and analytics services and their appropriate use cases based on data type and scale.

Question 11: You have been contracted by an oil company to oversee the migration of their on-premise Oracle and DB2 databases to Google Cloud. Which of the following options represents the most suitable approach for this migration?

1. CloudSQL for Oracle and VM for DB2 B. CloudSQL for both Oracle and DB2 C. VM for both Oracle and DB2 D. Google App Engine for both Oracle and DB2

Correct Answer: C

Option C is correct. As there is currently no managed service directly supporting Oracle and DB2 databases within Google Cloud, the most viable and common option is to install and manage both database systems on virtual machines (VMs). This provides the necessary flexibility and control over the database environment. Option A is incorrect because Cloud SQL only supports MySQL, PostgreSQL, and SQL Server, not Oracle. Therefore, it does not fulfill the requirement for Oracle migration. Option B is incorrect for the same reason as A: Cloud SQL does not support either Oracle or DB2. Option D, Google App Engine, is primarily a platform-as-a-service (PaaS) for deploying applications and is not designed for hosting and managing traditional relational databases like Oracle and DB2 directly. This question assesses your knowledge of Google Cloud’s database services and their compatibility with various database technologies for migration scenarios.

Question 12: A client of yours requires the migration of their on-premise MySQL data to Google Cloud with absolutely no downtime. Which service would you recommend for facilitating this seamless SQL data migration to the Cloud?

1. Cloud Migration B. Anthos C. CloudSQL D. Cloud Run

Correct Answer: C

Option C is correct. Cloud SQL offers robust database migration services, in addition to being a fully managed MySQL database service itself. It provides tools and capabilities to perform online migrations with minimal or no downtime. Option A, “Cloud Migration,” is a generic term and not a specific Google Cloud service. While Google Cloud has migration tools and programs, this option isn’t precise. Option B, Anthos, is primarily used for migrating and managing Kubernetes workloads across on-premises and multi-cloud environments; it is not designed for direct relational database migration. Option D, Cloud Run, is a managed compute platform for deploying stateless HTTP containers and is unrelated to database migration. This question tests your awareness of specific Google Cloud services tailored for database migrations, especially those requiring high availability.

Question 13: You are commencing work on a client’s project, who is seeking a database service within Google Cloud that offers horizontal scalability, supports relational data up to gigabyte sizes, and provides ACID (Atomicity, Consistency, Isolation, Durability) guarantees for reliable data storage. Which service would you recommend?

1. Datastore B. BigQuery C. CloudSQL D. Cloud Spanner

Correct Answer: D

Option D is correct. Cloud Spanner is Google Cloud’s globally distributed, highly consistent, and horizontally scalable relational database service. It is unique in its ability to offer ACID transactions while scaling across multiple regions, making it an ideal choice for large, mission-critical relational datasets that require high availability and strong consistency. Option A, Datastore (Firestore in Datastore mode), is a NoSQL database that supports ACID transactions, but it is not horizontally scalable in the same way as Spanner and is primarily designed for document-oriented data. Option B, BigQuery, is a serverless data warehouse designed for analytics on massive datasets; while it handles relational data, it is not a transactional database service suitable for operational workloads requiring ACID guarantees in the same manner as Spanner. Option C, Cloud SQL, supports ACID transactions and relational data, but it primarily offers vertical scaling (scaling up resources for a single instance) rather than native horizontal scaling across multiple regions like Cloud Spanner. This question evaluates your understanding of the distinct characteristics and use cases of various Google Cloud database services.

Question 14: You are distributing traffic among a fleet of virtual machines within your Virtual Private Cloud (VPC) using an Internal TCP/UDP Load Balancer. Which of the following specifications is NOT supported by the selected Load Balancing Type?

1. Preserved Client IP B. Global Availability C. Internal Load Balancing D. Any Destination Ports

Correct Answer: B

Option B is correct. Internal TCP/UDP Load Balancers are designed for internal traffic within a specific region. They do not offer global availability; they operate solely within the region where they are configured. Option A is incorrect because Internal TCP/UDP Load Balancers are capable of preserving the client’s original IP address. Option C is incorrect because, as the name suggests, they are inherently designed for internal load balancing within your VPC. Option D is incorrect because Internal TCP/UDP Load Balancers allow traffic to be directed to any destination port on the backend instances. This question tests your specific knowledge of the capabilities and limitations of Google Cloud’s Internal TCP/UDP Load Balancers.

Deploying and Implementing a Cloud Solution

Question 15: A developer has requested that you establish a single NGINX server for a development environment. Which service would enable you to launch a virtual machine using predefined images, simplifying the deployment process?

1. GKE B. GAE C. CloudSQL D. Marketplace

Correct Answer: D

Option D is correct. Google Cloud Marketplace provides a curated catalog of pre-built and configured software solutions, including virtual machine images with applications like NGINX already installed. This allows users to launch VMs with minimal configuration, often with just a few clicks. Option A, Google Kubernetes Engine (GKE), is used for deploying and managing containerized applications at scale using Kubernetes clusters, not for launching a single VM from a predefined image in this manner. Option B, Google App Engine (GAE), is a platform-as-a-service (PaaS) for building and deploying web applications; while it can host applications, it doesn’t directly offer NGINX predefined images for VM deployment in the way Marketplace does. Option C, Cloud SQL, is a fully managed relational database service and is unrelated to deploying an NGINX web server. This question assesses your knowledge of Google Cloud’s various deployment options and which service best suits the rapid deployment of common software stacks.

Question 16: Your company has secured a new project that necessitates a gradual migration of on-premise servers and data to Google Cloud. In the interim, you need to establish a secure VPN tunnel between the on-premise infrastructure and Google Cloud. Which service will you use in conjunction with Cloud VPN to facilitate a smooth setup?

1. Cloud CDN B. Cloud NAT C. Cloud Run D. Cloud Router

Correct Answer: D

Option D is correct. Google Cloud Router is an essential service that, when used with Cloud VPN, enables the dynamic exchange of routes between your Virtual Private Cloud (VPC) network and your on-premises networks utilizing Border Gateway Protocol (BGP). The Cloud Router automatically learns about new subnets within your VPC network and advertises them to your on-premises network, simplifying network connectivity and routing. Option A, Cloud CDN (Content Delivery Network), is used to accelerate content delivery for websites and applications by caching content at edge locations; it is unrelated to establishing a VPN tunnel. Option B, Cloud NAT (Network Address Translation), allows instances without public IP addresses to access the internet for updates and other outbound connections in a controlled manner; it’s not directly involved in setting up the VPN tunnel itself. Option C, Cloud Run, is a managed compute platform for deploying stateless containers; it has no direct role in establishing network connectivity between on-premises and Google Cloud. This question evaluates your understanding of network connectivity services in Google Cloud, particularly for hybrid cloud architectures.

Question 17: Your company is operating a high-availability deployment named “hello-server” within Kubernetes Engine on port 8080. This deployment needs to be exposed to the public internet via a load balancer on port 80. Which of the following commands will help accomplish this deployment?

1. kubectl expose deployment hello-server –type LoadBalancer –port 8080 –target-port 80 B. kubectl run deployment hello-server –type LoadBalancer –port 80 –target-port 8080 C. kubectl expose deployment hello-server –type LoadBalancer –port 80 –target-port 8080 D. kubectl run deployment hello-server –type LoadBalancer –port 8080 –target-port 80

Correct Answer: C

Option C is correct. The kubectl expose deployment command is used to create a service (in this case, of type LoadBalancer) that exposes a deployment. The –port flag specifies the port that the load balancer will listen on for incoming traffic (external port), and the –target-port flag specifies the port on which the pods in the deployment are listening (internal port). Therefore, kubectl expose deployment hello-server –type LoadBalancer –port 80 –target-port 8080 correctly configures the load balancer to listen on port 80 and forward traffic to the hello-server deployment’s pods on port 8080.

Option A is incorrect because the –port and –target-port values are reversed. This would mean the load balancer listens on 8080 and forwards to 80, which is not the desired outcome for exposing on port 80.

Options B and D are incorrect. The kubectl run command is used to create a deployment or run a pod, not to expose an existing deployment via a load balancer service. Furthermore, the run command does not directly support the –type LoadBalancer argument in this context for exposing a deployment. This question tests your practical knowledge of kubectl commands for managing and exposing applications in Kubernetes Engine.

Question 18: Which of the following gcloud commands allows you to view the detailed specifications of a custom subnet you have created in a particular region?

1. gcloud compute networks subnets view [SUBNET_NAME] –region us-central1 B. gcloud compute networks subnets describe [SUBNET_NAME] –region us-central1 C. gcloud compute networks subnets list [SUBNET_NAME] –region us-central1 D. gcloud compute networks subnets read [SUBNET_NAME] –region us-central1

Correct Answer: B

Option B is correct. The describe flag within the gcloud compute networks subnets command provides a comprehensive and detailed description of the specified subnet, including its configuration, IP ranges, and associated resources. Options A, C, and D are incorrect: view and read are not valid gcloud flags for this purpose. The list flag (as in gcloud compute networks subnets list) is used to enumerate multiple subnets within a project or region, but it does not provide the detailed information of a single subnet that describe does. This question assesses your ability to use gcloud commands for inspecting and understanding network configurations, a fundamental skill for cloud engineers.

Ensuring Successful Cloud Solution Operation

Question 19: While inspecting containers running on a virtual machine, you discovered an unwanted pod that is no longer necessary. Despite attempting to delete it, a new pod is consistently recreated in its place. What essential Kubernetes resource do you need to delete to permanently remove that pod and prevent its re-creation?

1. ReplicaSet B. VM C. Container D. Service

Correct Answer: A

Option A is correct. A ReplicaSet (or a Deployment which manages ReplicaSets) is the Kubernetes resource responsible for ensuring a desired number of identical pods are running at all times. If you delete a pod that is managed by a ReplicaSet, the ReplicaSet will immediately detect that the desired count is not met and will create a new pod to restore the desired state. Therefore, to permanently remove the pod and prevent its re-creation, you must delete the managing ReplicaSet (or the Deployment that controls it).

Option B is incorrect. Directly deleting the VM would result in the deletion of all other containers and pods running on it, which is an overly aggressive and likely undesirable action if only a specific pod needs to be removed.

Option C is incorrect. Deleting a container within a pod is akin to deleting the pod itself in this context; if the pod is managed by a ReplicaSet, a new pod (with its containers) will be created.

Option D is incorrect. Deleting a Service will remove the network abstraction that provides access to the pod(s), but it will not delete the underlying pods themselves. The pods will continue to run unless their managing ReplicaSet is deleted. This question tests your fundamental understanding of Kubernetes object relationships, particularly how ReplicaSet ensures application availability and how to properly scale down or remove applications.

Question 20: Your company has recently secured a significant big data project. This project requires you to deploy Apache Spark clusters on Google Cloud. Which service will you utilize for this purpose?

1. DataFlow B. DataProc C. BigTable D. Cloud Composer

Correct Answer: B

Option B is correct. Cloud Dataproc is a fast, user-friendly, and fully managed cloud service specifically designed for running Apache Spark and Apache Hadoop clusters. It simplifies the deployment and management of these big data frameworks in a more cost-effective manner.

Option A, Cloud Dataflow, is a fully-managed service for transforming and enriching data, supporting both real-time streaming and batch processing with unified reliability and expressiveness. While it works with big data, it’s not primarily for deploying Spark clusters.

Option C, BigTable, is a petabyte-scale, fully managed NoSQL database service optimized for large analytical and operational workloads, supporting the open-source HBase API. It’s a data store, not a compute platform for Spark clusters.

Option D, Cloud Composer, is a fully managed workflow orchestration service built on Apache Airflow. It helps author, schedule, and monitor data pipelines that span across clouds and on-premises environments, but it doesn’t directly deploy Spark clusters. This question assesses your knowledge of Google Cloud’s big data services and their specific use cases, differentiating between data processing, data storage, and orchestration tools.

Question 21: Your client wishes to migrate their 30 TB Hadoop or Spark cluster, currently running on RHEL 6.5 on-premise servers, to Google Cloud Platform. Which of the following Google Cloud services can be effectively used for this migration?

1. Compute Engine B. App Engine C. Dataproc D. BigQuery

Correct Answer: C

Option C is correct. Cloud Dataproc provides a faster, easier, and more cost-effective way to run Apache Spark and Apache Hadoop workloads on Google Cloud. It is a fully managed service that simplifies the deployment, management, and scaling of these clusters, making it ideal for migrating existing Hadoop/Spark environments.

Option A, Compute Engine, while capable of running custom VM instances where you could manually install and configure Hadoop/Spark, would require significant administrative overhead and would not be as cost-effective or managed as Dataproc for a 30 TB cluster.

Option B, App Engine, is not an appropriate service for this purpose. App Engine is a platform-as-a-service (PaaS) for deploying web applications and does not directly support the native execution and management of Hadoop or Spark clusters.

Option D, BigQuery, is a serverless data warehouse for analytics on structured data. While it can be integrated with Spark for data processing, BigQuery itself is not designed to run Spark commands or host Spark clusters directly. This question tests your understanding of the most appropriate Google Cloud services for migrating and managing large-scale Apache Hadoop and Spark workloads.

Configuring Access and Security

Question 22: Your company has subscribed to a third-party threat detection service and requires you to upload all network logs to this application for analysis. Which of the following Google Cloud services will fulfill your requirements for comprehensive network logging?

1. Activity Logs B. Flow Logs C. Network Logs D. System Logs

Correct Answer: B

Option B is correct. Flow Logs, specifically VPC Flow Logs, are designed to capture detailed information about every packet flowing within your Virtual Private Cloud (VPC) network. These logs record critical details such as source IP address, destination IP address, source port, destination port, protocols, and timestamps, making them invaluable for network monitoring, security analysis, and troubleshooting.

Option A, Activity Logs (part of Cloud Audit Logs), primarily record administrative activities and API calls made within your Google Cloud project, such as launching instances, creating firewall rules, or creating storage buckets. They do not capture detailed network traffic information at the packet level.

Option C, “Network Logs,” is a generic term and not a specific, recognized type of log within Google Cloud’s logging services. The specific term for detailed network traffic logs is Flow Logs.

Option D, “System Logs,” is also a general term and could refer to various logs from operating systems or applications running on VMs, but it does not specifically refer to the comprehensive network traffic logs required for a threat detection service. This question assesses your understanding of Google Cloud’s logging capabilities and the specific types of logs available for network introspection and security.

Question 23: One of your team members inadvertently committed a service account private JSON key to a public GitHub repository. What immediate actions should you perform to mitigate the security risk?

1. Delete the JSON file from GitHub. B. Delete the project and all its resources. C. Delete the JSON file from GitHub, revoke the compromised key from Google Cloud IAM, and generate a new key for use. D. None of the above

Correct Answer: C

Option C is correct. Private keys, especially service account keys, are highly sensitive credentials and must be protected. If a key is exposed (e.g., by being pushed to a public repository), immediate and decisive action is required to prevent unauthorized access to your Google Cloud resources. The best practice involves a three-pronged approach:

1. Delete the JSON file from GitHub: This removes the exposed credential from the public repository.
2. Revoke the compromised key from Google Cloud IAM: This is the most crucial step as it immediately invalidates the exposed key, rendering it useless for authentication.
3. Generate a new key for use: After the compromised key is revoked, a new, secure key should be generated and used for all legitimate operations.

Option A is incorrect because merely deleting the file from GitHub does not fully mitigate the risk; if the key is still active in IAM, anyone who had access to the repository before the deletion could still use it.

Option B is incorrect. Deleting the entire project and all its resources is an extreme and often impractical measure, especially for projects with numerous running resources. It is not the recommended first response for a compromised service account key.

Option D is incorrect because there is a clear and effective best practice for such a scenario. This question emphasizes critical security incident response procedures and best practices for managing sensitive credentials in Google Cloud.

Question 24: Your project manager intends to create a new user account for Aston Smith, who will serve as the new Cloud SQL administrator within your organization. Which of the following IAM roles would grant him the capability to manage specific Cloud SQL instances but restrict his ability to import or restore data from backups?

1. Cloud SQL Editor B. Cloud SQL Admin C. Cloud SQL Viewer D. Cloud SQL Client

Correct Answer: A

Option A is correct. The Cloud SQL Editor role (roles/cloudsql.editor) allows users to manage specific Cloud SQL instances. However, this role explicitly restricts the ability to see or modify permissions, modify users or SSL certificates, import data, restore from a backup, or clone, delete, or promote instances. This aligns precisely with the requirement to manage instances without data import/restore capabilities.

Option B, Cloud SQL Admin (roles/cloudsql.admin), provides full control over all Cloud SQL resources, including the ability to import data and restore from backups, which goes against the specified restriction.

Option C, Cloud SQL Viewer (roles/cloudsql.viewer), grants read-only access to all Cloud SQL resources, which is insufficient for managing instances.

Option D, Cloud SQL Client (roles/cloudsql.client), primarily provides connectivity access to Cloud SQL instances from App Engine and the Cloud SQL Proxy; it does not grant administrative privileges for managing instances. This question tests your detailed understanding of Google Cloud IAM roles for Cloud SQL and their specific permissions, which is crucial for implementing least privilege security principles.

Question 25: Your company has uploaded several business-critical documents to Cloud Storage, and your project manager requires you to restrict access to these objects using Access Control Lists (ACLs). Which of the following permissions would allow you to update the object ACLs?

1. Storage.objects.update B. Storage.objects.setIamPolicy C. Storage.objects.create D. Storage.objects.getIamPolicy

Correct Answer: B

Option B is correct. As per Google Cloud documentation, the storage.objects.setIamPolicy permission is specifically required to update object Access Control Lists (ACLs) when using IAM policies.

Option A, storage.objects.update, allows users to update an object’s metadata, but it explicitly excludes the ability to modify ACLs or IAM policies.

Option C, storage.objects.create, grants permission to add new objects to a bucket.

Option D, storage.objects.getIamPolicy, allows users to read an object’s IAM policies, but not to modify them. This question assesses your precise knowledge of Google Cloud Storage IAM permissions related to object access control, highlighting the distinction between metadata updates and policy modifications.

Establishing a Cloud Solution Environment

Question 26: Following your manager’s instructions, you provisioned a custom Virtual Private Cloud (VPC) with a subnet mask of /24, which theoretically provides 256 IP addresses. However, you discover that you can only utilize 252 addresses. Your manager, puzzled by this discrepancy, asks for an explanation. What is the correct answer you would provide?

252. Inform your manager that you will recreate the VPC because you suspect an error occurred during subnet creation. B. Google Cloud Platform reserves four IP addresses in each primary subnet range, which accounts for the usable IP count being 252. C. It’s because your account has reached a soft limit for the number of private IP address space; you need to submit a request for a quota increase. D. None of the above.

Correct Answer: B

Option B is correct. Google Cloud Platform consistently reserves four IP addresses within every primary subnet range you create. The rationale for this reservation is as follows:

• The first IP address in the range is designated as the network address.
• The second IP address is reserved for the default gateway.
• The second-to-last IP address is reserved for future use by Google Cloud.
• The last IP address in the range is designated as the broadcast address.

Therefore, for a /24 subnet, which has 256 total addresses (232−24=28=256), only 256−4=252 addresses are actually available for your virtual machine instances.

Option A is incorrect: The subnet creation process is functioning as intended, and the discrepancy is due to a standard GCP network design feature, not an error in creation.

Option C is incorrect: This scenario is not related to reaching a soft limit for private IP address space or requiring a quota increase; it’s a fundamental aspect of how subnets are provisioned in GCP.

Option D is incorrect: The correct answer is B, rendering this option invalid. This question tests your fundamental understanding of networking in Google Cloud, specifically how IP addresses are allocated within subnets and the reasons for reserved addresses.

Architecting and Planning a Cloud Solution

Question 27: You are employed by a retail company with a thriving online store. As the New Year approaches, you observe a substantial surge in traffic to your e-commerce platform. Although your web servers are deployed behind a managed instance group, you notice that the web tier is frequently scaling up and down, sometimes multiple times within an hour. You need to mitigate this rapid scaling behavior to prevent unnecessary fluctuations. Which of the following options would effectively help you achieve this?

1. Change the auto scaling metric to use multiple metrics instead of just one metric. B. Reduce the number of maximum instance count. C. Associate a health check with the instance group. D. Increase the cool-down period.

Correct Answer: D

Option D is correct. Increasing the cool-down period for your autoscaling policy will instruct the instance group to wait for a slightly longer duration after a scaling event (either scale-up or scale-down) before initiating another scaling action. This delay helps to stabilize the instance group size by preventing rapid, consecutive scaling operations due to momentary traffic spikes or dips, thereby reducing oscillation.

Option A is incorrect: While using multiple autoscaling metrics can provide a more nuanced scaling behavior, it doesn’t directly address rapid oscillation if the issue is a very sensitive scaling trigger or a short cool-down period. It could even complicate the scaling logic further if not configured carefully.

Option B is incorrect: Reducing the maximum instance count would limit the upper bound of your instance group’s size, but it would not prevent rapid scaling up and down within that allowed range. In fact, it might lead to capacity issues during peak traffic.

Option C is incorrect: Associating a health check with the instance group primarily ensures that unhealthy instances are replaced, thereby improving the availability of your application. While important for reliability, it does not directly control the frequency or rate of scaling operations. This question assesses your understanding of Compute Engine autoscaling configuration, specifically how to fine-tune its behavior to prevent undesirable oscillations.

Deploying and Implementing a Cloud Solution

Question 28: A developer inadvertently deleted some files from a Google Cloud Storage bucket. Fortunately, these files were not critical and were promptly re-created. Because of this incident, your team lead has instructed you to enable versioning on the bucket. Which command would assist you in enabling this feature?

1. gsutil versioning enable gs://examlabs-bucket B. gsutil gs://examlabs-bucket enable versioning C. gsutil enable versioning gs://examlabs-bucket D. gsutil versioning set on gs://examlabs-bucket

Correct Answer: D

The correct gsutil command to enable object versioning on a Google Cloud Storage bucket is gsutil versioning set on gs://examlabs-bucket. Therefore, Option D is the accurate response. Options A, B, and C are incorrect because they represent invalid gsutil command syntax for configuring bucket versioning. This question tests your practical knowledge of gsutil commands for managing Google Cloud Storage features, particularly data protection mechanisms like object versioning.

Deploying and Implementing a Cloud Solution

Question 29: A critical bug has been identified within your Python application, which is hosted on App Engine. You are preparing to roll out a new version of the application to resolve this bug, but you want to prevent traffic from automatically shifting to the new version immediately. This is to ensure that the new version does not introduce any unforeseen issues. How would you achieve this controlled deployment?

1. Pass a custom version ID so that App Engine does not send traffic to the new version. B. Pass the –no-promote flag while deploying the new version. C. Pass the –no-active flag while deploying the new version. D. Use the –inactive-mode flag while deploying the new version of the app.

Correct Answer: B

Option B is correct. When deploying a new version of an App Engine application, including the –no-promote flag with the gcloud app deploy command will prevent App Engine from automatically routing traffic to the newly deployed version. This allows you to manually split traffic to the new version after thorough testing, ensuring a controlled rollout and minimizing the risk of disruptions.

Option A is incorrect: Passing a custom version ID (e.g., using –version) will merely assign a specific name to your new version; it does not inherently prevent traffic from being directed to it upon deployment if it’s set as the default or promoted.

Option C is incorrect: –no-active is not a valid flag for controlling traffic promotion during App Engine deployment.

Option D is incorrect: –inactive-mode is not a valid flag for controlling traffic promotion during App Engine deployment. This question assesses your knowledge of App Engine deployment strategies, specifically how to manage traffic routing and conduct controlled rollouts for new application versions.

Configuring Access and Security

Question 30: You are attempting to retrieve metadata from a virtual machine (VM) using the command curl metadata.google.internal/computeMetadata/v1/, but you are consistently receiving a “403 Forbidden” error. What could be the most probable reason for this access denial?

1. The service account is missing. B. The Metadata-Flavor: Google header is missing. C. The Metadata-Access: Google header is missing. D. A firewall rule attached to the VM is blocking the request.

Correct Answer: B

Option B is correct. When querying the instance metadata server for an instance’s metadata, it is a strict requirement to include the Metadata-Flavor: Google header in your curl request. This header serves as an explicit indicator that the request is intentionally for metadata retrieval, rather than an accidental or potentially malicious request from an insecure source. Without this header, the metadata server will deny your request, resulting in a “403 Forbidden” error.

Option A is incorrect: A missing service account would typically result in authentication errors for accessing other Google Cloud services, but not directly a “403 Forbidden” for the metadata server itself, which is designed to be accessible from the instance without explicit service account authentication in this specific context.

Option C is incorrect: Metadata-Access: Google is not a valid or required header for accessing instance metadata.

Option D is incorrect: If a firewall rule were blocking the request, you would likely not receive a “403 Forbidden” response from the server; instead, the connection would typically time out or be refused without a specific HTTP status code from the metadata server. The “403 Forbidden” specifically indicates that the server received the request but denied it due to a policy or authentication/authorization issue, which in this case points to the missing required header. This question emphasizes a crucial security requirement for interacting with the Google Cloud Compute Engine metadata server.