All practice questions

An organization is planning to deploy batch machine learning training jobs on Google Cloud Compute Engine. The jobs support native checkpointing, can tolerate unexpected instance preemptions without losing progress, and must be executed at the lowest possible cost. Which Compute Engine provisioning model should you recommend?

An enterprise organization uses a Google Cloud resource hierarchy consisting of an Organization node, department Folders, and environment Projects. A compliance auditor needs read-only access to all current and future Google Cloud resources grouped under the 'Finance-Dept' folder. You need to configure access control following Google Cloud best practices and the principle of least privilege. Which action should you take?

A software development team needs to deploy a stateless web application packaged inside a custom Docker container image to Google Cloud without managing underlying infrastructure or virtual machines. Which Google Cloud serverless compute option should the team select?

A cloud security auditor requires read-only visibility into all cloud resources contained within a specific business unit's folder. An IT administrator grants the auditor the Viewer role (roles/viewer) directly on that folder. Which statement correctly describes the outcome of this role assignment across the resource hierarchy?

A data processing team needs to run a 4-hour nightly batch job that validates large data files. The application is designed to be fault-tolerant and can checkpoint its progress to resume if interrupted. The primary objective is to minimize compute costs as much as possible. Which Compute Engine resource planning option is best suited for this workload?

An enterprise logistics firm is planning Compute Engine virtual machine specifications for a legacy telemetry parser service. The workload runs continuously 24 hours a day, 7 days a week, and strictly requires 2 vCPUs and 14 GB of memory to run efficiently without waste. Standard machine types provide either too little memory (2 vCPUs with 8 GB) or unnecessary compute (4 vCPUs with 16 GB). Which deployment strategy should the Cloud Engineer recommend to minimize monthly operational costs while meeting these exact workload requirements?

A financial analytics company is designing its Google Cloud infrastructure to handle two distinct workload requirements:
1. A batch risk-modeling application that runs nightly for 6 hours, processing fault-tolerant worker tasks that checkpoint state to Cloud Storage every 10 minutes.
2. A core licensing and authentication service that must run continuously 24/7 with strict uptime requirements.

The team wants to optimize infrastructure costs while maintaining compliance with operational requirements. Which Compute Engine provisioning strategy should the cloud engineer recommend?

A cloud administrator needs to request an increase for a Compute Engine GPU quota in a specific region for a Google Cloud project. Which two actions should the administrator take to perform this request? (Select TWO.)

A security audit reveals that the Google Group `[email protected]` has been granted the `roles/compute.admin` role at a parent Folder level named `Finance-Prod`. This folder contains ten production projects, including a sensitive audit project named `payments-main`. Company security policy requires members of `[email protected]` to retain Compute Engine administrative access across nine of the projects, but they must explicitly have no administrative access to `payments-main`. How should you restructure the IAM configuration to meet this requirement following the principle of least privilege?

A data engineering team is attempting to deploy an automated batch processing pipeline inside a target Google Cloud project named `warehouse-analytics-live`. The execution fails because the Cloud Dataflow API (`dataflow.googleapis.com`) has not been activated in the project. As a Cloud Engineer, you must enable this service specifically for `warehouse-analytics-live` using the Google Cloud CLI. Which command should you execute?

An enterprise platform engineering team manages an automated infrastructure pipeline. The pipeline uses a custom service account to provision new Google Cloud projects. During execution, a script in the pipeline executes the command `gcloud services enable artifactregistry.googleapis.com --project=fintech-core-prod` to enable the Artifact Registry API in the target project. The execution fails with an authorization error indicating permission denied. Adhering to the Google Cloud security principle of least privilege, which action should the system administrator take to resolve this issue?

An enterprise logistics company is planning the Google Cloud Compute Engine architecture for two distinct workloads:

1. An in-memory route calculation service running continuously $24/7$ with a constant baseline demand. It requires a specific non-standard configuration of $16$ vCPUs and $128\text{ GB}$ of RAM ($8\text{ GB}$ per vCPU).
2. A high-throughput image rendering pipeline that processes user-uploaded media. The rendering pipeline is stateless, fault-tolerant, and capable of resuming tasks if an instance terminates unexpectedly.

Which Compute Engine provisioning strategy optimizes infrastructure costs while meeting all operational requirements?

An organization is designing a Cloud Storage lifecycle policy for financial audit archives. The data access pattern is strictly defined as follows: objects are actively accessed multiple times daily for the first 30 days; between 31 and 90 days, objects are queried only once per month during financial reconciliation; after 90 days, objects are strictly retained for compliance and accessed less than once a year for 7 years. To minimize total cost of ownership (TCO) while avoiding early deletion/transition fee penalties and high data retrieval charges, which storage class lifecycle strategy should be planned?

A financial services firm is building two backend components for a real-time transaction verification pipeline on Google Cloud:

1. Component X: An HTTP microservice that receives high-throughput API traffic. It relies on a custom C++ native binary compiled for Linux and must process up to 80 concurrent HTTP requests per instance to maximize resource efficiency.
2. Component Y: A lightweight Python event handler that executes briefly whenever a transaction log object is finalized in a Cloud Storage bucket, parsing the log and writing summary statistics to a database.

Which architecture recommendation correctly pairs these workloads with the appropriate Google Cloud serverless compute options?

A Cloud Engineer needs to request an increase for a Compute Engine CPU resource quota in a specific region using the Google Cloud Console. What is the correct sequence of steps to submit this quota request?

An organization needs to provision Google Cloud Compute Engine virtual machines for a fault-tolerant batch processing application. The application requires a non-standard configuration of 3 vCPUs and 11 GB of RAM to run efficiently. Which TWO configuration options should you select to meet the technical requirements while minimizing costs?

An enterprise DevOps team needs to configure an automated service account, [email protected], to provision new Google Cloud projects inside a designated folder named Engineering-Apps. Additionally, these newly created projects must be linked to the company central billing account (ID: 01ABCD-EF1234-567890). Following the principle of least privilege, which configuration of IAM roles should be assigned to the service account?

A DevOps engineer needs to establish a new application environment in Google Cloud following standard operational procedures. In which order should the engineer execute the administrative steps to correctly position the project in the resource hierarchy, enable billing, and grant access?

A principal cloud engineer is preparing to deploy an automated data processing pipeline across a cluster of Compute Engine virtual machines in the us-central1 region. During initialization testing, instance creation fails with a QUOTA_EXCEEDED error for N2_CPUS. Upon inspecting the project's Quotas & System Limits page, the engineer confirms that current usage has reached the regional limit of 24 CPUs, but the pipeline requires 64 CPUs to meet SLA requirements. Which action should the engineer take to resolve this limitation following Google Cloud best practices?

A digital publishing company is architecting serverless compute solutions for two new services on Google Cloud:

1. Service 1: An interactive web API that requires handling up to 250 concurrent HTTP requests per container instance to optimize resource utilization.
2. Service 2: A lightweight background script that executes automatically whenever a raw text file is uploaded to a Cloud Storage bucket.

Which TWO deployment decisions correctly align with Google Cloud serverless compute capabilities for these services?