Cloud Digital Leader Google Cloud Products and Services Practice Test 3 — 15 Questions

Question 1

A company needs to store files that are accessed infrequently (once a quarter) and wants the lowest storage cost. Data retrieval can take a few hours. Which Cloud Storage class should they use?

Accepted Answer

Archive. The correct option is A, Archive, because it is designed for data accessed less than once a year, offers the lowest storage cost, and has retrieval times of hours, matching the requirement of infrequent quarterly access with a few hours of retrieval latency. Nearline (B) is for data accessed less than once a month and has a higher storage cost than Archive. Coldline (C) is for data accessed less than once a quarter and is cheaper than Nearline but still more expensive than Archive. Standard (D) is for frequently accessed data and has the highest storage cost, so it does not fit the lowest-cost requirement.

Answer

Nearline

Answer

Coldline

Answer

Standard

Question 2

A company is running a stateful workload on Compute Engine and needs persistent block storage that can be attached to multiple VMs in read-only mode. Which two Google Cloud storage solutions meet this requirement?

Accepted Answer

Persistent Disk (with read-only replica). Persistent Disk (PD) is a block storage solution that can be attached to multiple VMs in read-only mode. Both standard Persistent Disk and Persistent Disk with a read-only replica support this capability, making them suitable for sharing stateful data across multiple instances in the same zone.

Answer

Filestore

Answer

Local SSD

Answer

Cloud Storage

Question 3

A company runs a microservices application on Google Kubernetes Engine (GKE) and wants to reduce costs by using preemptible nodes for stateless workloads. However, they need to ensure that critical stateful workloads are not disrupted. Which two actions should they take?

Accepted Answer

Taint the regular node pool and use tolerations for stateful pods. Option D is correct because creating a dedicated preemptible node pool and applying a taint to it (e.g., cloud.google.com/gke-preemptible=true:NoSchedule) forces only stateless pods that carry the matching toleration to land on those cheap, evictable VMs, keeping stateful pods off them. Option A is correct because tainting the regular node pool and giving stateful pods the corresponding toleration ensures those pods can still schedule onto the stable, non-preemptible nodes while stateless pods (lacking the toleration) are repelled from them. Option B is wrong because a single mixed node pool gives no scheduling control, so stateful pods could be placed on preemptible VMs and be disrupted. Option C is wrong because a high priority class only affects eviction/preemption ordering during resource pressure; it does not prevent a stateful pod from being scheduled onto a preemptible node or from being reclaimed by GCE. Option E is wrong because node affinity is a soft/hard scheduling preference based on labels and does not by itself guarantee exclusion from preemptible nodes the way taints and tolerations do, and it omits the required taint on the preemptible pool.

Answer

Use a single node pool with a mix of regular and preemptible VMs

Answer

Set pod priority class to 'high' for stateful workloads

Answer

Use node affinity rules to schedule stateful pods on regular nodes

Question 4

A company needs to store petabytes of time-series IoT sensor data and query it with single-digit millisecond latency at millions of reads per second. The data has a simple key-value structure with timestamps. Which Google Cloud database is MOST appropriate?

Accepted Answer

Cloud Bigtable. Cloud Bigtable is a fully managed, scalable NoSQL database designed for large analytical and operational workloads, including time-series data. It provides single-digit millisecond latency at high throughput (millions of reads/writes per second) and is ideal for key-value data with timestamps, making it the best fit for IoT sensor data at petabyte scale.

Answer

Firestore

Answer

Cloud Spanner

Answer

BigQuery

Question 5

A startup is building a mobile app backend that stores user profiles and session data. They need a NoSQL database with real-time synchronization across devices and offline support. Which TWO Google Cloud services are suitable?

Accepted Answer

Firestore. Firestore is a NoSQL document database that provides real-time listeners and offline persistence, making it ideal for mobile app backends requiring synchronization across devices and offline support. Cloud Storage is an object storage service, not a NoSQL database, and does not offer real-time sync or offline database capabilities. None of the other options (Memorystore, Cloud Bigtable, Cloud Spanner) meet the specific requirements of a NoSQL database with real-time sync and offline support.

Answer

Memorystore

Answer

Cloud Bigtable

Answer

Cloud Spanner

Answer

Cloud Storage

Question 6

A startup wants to build a chatbot that can understand natural language and integrate with Google Workspace (e.g., Gmail, Calendar). They have limited ML expertise. Which TWO Google Cloud services should they use?

Accepted Answer

Dialogflow. Dialogflow is the managed Google Cloud service for building conversational interfaces. It provides natural language understanding, conversation management, and Google Workspace integrations while requiring minimal ML expertise. Cloud Functions is the serverless compute service used for webhook fulfillment, allowing the chatbot to call Google Workspace APIs such as Gmail and Calendar. Vertex AI is a general-purpose ML platform, Cloud Translation API translates text, and Natural Language API provides text analysis, but none of these directly builds and integrates a chatbot.

Answer

Vertex AI

Answer

Cloud Translation API

Answer

Natural Language API

Question 7

A regional bank is modernizing its branch teller applications. Policy requires that all customer data remain inside the bank's own on-premises data center for regulatory reasons, but the bank wants to use Google Cloud's AI APIs for document processing. Which Google Cloud deployment model should the bank choose?

Accepted Answer

Anthos deployed on the bank's own hardware in its data center. Anthos is designed to run Google Cloud services on the customer's own infrastructure, including on-premises hardware, which is exactly what a strict data-residency rule demands. The other choices all place data or workloads inside Google-managed facilities, or provide only networking or security controls, so they cannot satisfy the requirement that customer data remain in the bank's data center.

Answer

A VPC Service Controls perimeter around a Compute Engine project

Answer

A Dedicated Interconnect connection between the bank and a Google region

Answer

A multi-region Cloud Storage bucket with dual-region replication

Question 8

A company needs to store petabytes of time-series IoT sensor data and query it with single-digit millisecond latency at millions of reads per second. The data has a simple key-value structure with timestamps. Which Google Cloud database is MOST appropriate?

Accepted Answer

Cloud Bigtable. Cloud Bigtable is designed for petabyte-scale, low-latency, high-throughput NoSQL storage for time-series, IoT, and financial data. It scales horizontally by adding nodes.

Answer

Cloud Spanner

Answer

BigQuery

Answer

Firestore

Question 9

A developer wants to deploy a containerized web application that can automatically scale to zero when there are no requests, and charges only for resources used during request processing. Which Google Cloud compute service should they use?

Accepted Answer

Cloud Run. Cloud Run is a serverless container platform that scales to zero and charges per request. Google Kubernetes Engine and Compute Engine require running instances, and App Engine Standard is a platform as a service but not container-based.

Answer

Compute Engine

Answer

Google Kubernetes Engine (GKE)

Answer

App Engine Standard Environment

Question 10

An organization needs to run a batch process every night that analyzes terabytes of data from Cloud Storage and writes results back to BigQuery. The job is not time-sensitive and can be preempted. Which compute approach is most cost-effective?

Accepted Answer

Compute Engine with preemptible VMs. Preemptible VMs on Compute Engine offer the lowest cost for fault-tolerant batch workloads because they are up to 80% cheaper than regular VMs but can be terminated at any time. Cloud Run has a request timeout limit and is not ideal for long-running batch jobs. GKE with preemptible nodes is also cost-effective but requires Kubernetes expertise and is more complex than simply using preemptible VMs. Cloud Functions has a timeout limit.

Answer

Cloud Functions with background trigger

Answer

Google Kubernetes Engine with standard nodes

Answer

Cloud Run with manual scaling

Question 11

Which Google Cloud service provides a fully managed, scalable data warehouse for running SQL queries on petabyte-scale data and supports BI tools like Looker?

Accepted Answer

BigQuery. BigQuery is a serverless data warehouse that scales to petabytes and uses SQL for analytics. Cloud SQL is for OLTP, Cloud Storage is object storage, and Dataflow is for data processing pipelines.

Answer

Cloud SQL

Answer

Cloud Storage

Answer

Dataflow

Question 12

A company wants to migrate its on-premises PostgreSQL database to Google Cloud with minimal application changes. They need high availability and want to leverage AI-powered optimizations for performance. Which service should they choose?

Accepted Answer

AlloyDB. AlloyDB for PostgreSQL is a fully managed, PostgreSQL-compatible database service on Google Cloud that offers high availability and uses AI-powered optimizations for performance, such as adaptive caching and automated tuning. It is designed for minimal application changes because it is wire-compatible with PostgreSQL. This makes it the best fit for migrating an on-premises PostgreSQL database with high availability and AI-driven performance.

Answer

Bigtable

Answer

Cloud SQL for PostgreSQL

Answer

Cloud Spanner

Question 13

A developer needs to run a small piece of Python code that processes a message from Pub/Sub and stores the result in Firestore. The code runs infrequently (a few hundred times per day) and takes less than a second to execute. Which compute service is most cost-effective and simple to manage?

Accepted Answer

Cloud Functions. Cloud Functions is the most cost-effective and simple option for infrequent, short-running event-driven code. It automatically scales to zero when not in use, so you only pay for actual execution time and resources consumed. It integrates natively with Pub/Sub and Firestore, requiring minimal configuration.

Answer

Cloud Run

Answer

Compute Engine with preemptible VM

Answer

App Engine Standard Environment

Question 14

What is the primary purpose of Google Cloud Armor?

Accepted Answer

To protect applications from DDoS attacks and application-level threats. Google Cloud Armor is a security service that provides DDoS protection and WAF capabilities for applications behind Google Cloud load balancers. It filters malicious traffic at the edge, protecting against Layer 3/4 DDoS and Layer 7 application attacks like SQL injection and XSS. It is the primary tool for edge security in GCP.

Answer

To accelerate content delivery globally

Answer

To provide outbound internet connectivity to private instances

Answer

To manage virtual private cloud networking

Question 15

A data engineer needs to process a continuous stream of clickstream events from a website, perform real-time aggregations (e.g., counts per page per minute), and write the results to BigQuery for dashboarding. Which combination of services should they use?

Accepted Answer

Pub/Sub, Dataflow, BigQuery. Pub/Sub ingests the stream, Dataflow processes real-time aggregations using Apache Beam, and BigQuery stores results. Cloud Functions is not suitable for streaming aggregations. Cloud Storage is for batch, not real-time. Cloud SQL is not for streaming analytics.

Answer

Pub/Sub, Cloud Functions, Cloud SQL

Answer

Cloud Storage, Dataflow, Cloud SQL

Answer

Pub/Sub, Cloud Functions, BigQuery