Cloud Digital Leader Google Cloud Products and Services Practice Test 8 — 15 Questions

Question 1

A data scientist wants to train a custom machine learning model using a large dataset stored in BigQuery. They need a managed service that supports distributed training with GPU accelerators. Which service should they use?

Choose an answer to begin — your selection is scored in the full session.

Accepted Answer

Vertex AI Training. Vertex AI provides a unified ML platform with managed training jobs that support distributed training and GPU accelerators.

Answer

Dataflow

Answer

Cloud Functions

Answer

AutoML (within Vertex AI)

Question 2

A company wants to implement a hybrid cloud architecture connecting their on-premises data center to Google Cloud. They need high bandwidth (10 Gbps), low latency, and a service-level agreement (SLA). Which TWO services can provide dedicated connectivity? (Choose two.)

Accepted Answer

Cloud Interconnect (Partner). Cloud Interconnect (dedicated or partner) provides high-bandwidth, low-latency connections with SLAs. HA VPN is a VPN alternative but does not offer dedicated bandwidth or SLA for throughput. So the two correct are Cloud Interconnect (Dedicated Interconnect) and Cloud Interconnect (Partner Interconnect). However, the question asks for services that provide dedicated connectivity with SLA. Both Dedicated Interconnect and Partner Interconnect offer SLAs. HA VPN does not. So I'll include both types of Interconnect, but since they are the same service, I need to differentiate. Let's list options: A. Cloud VPN, B. HA VPN, C. Cloud Interconnect (Dedicated), D. Cloud Interconnect (Partner), E. Cloud CDN. So C and D are correct.

Answer

HA VPN

Answer

Cloud CDN

Answer

Cloud VPN

Question 3

A developer wants to build a mobile app backend that uses a real-time database for chat messages, user profiles, and file storage for images. They want a fully managed, serverless solution. Which THREE Google Cloud services should they use? (Choose three.)

Accepted Answer

Cloud Functions. Firestore provides real-time document database for chat and profiles; Cloud Storage for images; Cloud Functions for backend logic triggered by database or storage events. App Engine is not required for serverless backend if using Cloud Functions.

Answer

Cloud SQL

Answer

App Engine

Question 4

A developer wants to deploy a containerised web application that can scale to zero when not in use, and only pay for actual request processing time. Which Google Cloud compute service should they choose?

Accepted Answer

Cloud Run. Cloud Run is a serverless compute platform that runs containers, scales to zero when idle, and charges per request and CPU/memory usage only during request handling. App Engine Standard can scale to zero but does not support arbitrary containers. GKE and Compute Engine are provisioned infrastructure that does not scale to zero.

Answer

App Engine Standard Environment

Answer

Google Kubernetes Engine (GKE)

Answer

Compute Engine with Preemptible VMs

Question 5

A company wants to analyse streaming data from IoT devices in real time with sub-second latency, using SQL queries. Which combination of services should they use?

Accepted Answer

Cloud Pub/Sub + Dataflow + BigQuery. Dataflow with unbounded sources (like Pub/Sub) and SQL via Beam SQL or Dataflow SQL can process streaming data with low latency. BigQuery can also stream data but with higher latency (seconds). Cloud Functions is not ideal for real-time SQL analytics. Dataproc is for batch processing.

Answer

Cloud IoT Core + Cloud Functions + Bigtable

Answer

Cloud Pub/Sub + Dataproc + Cloud Storage

Answer

Cloud Pub/Sub + Cloud Functions + Cloud SQL

Question 6

Which Google Cloud service provides a fully managed, serverless data warehouse for petabyte-scale analytics with SQL?

Accepted Answer

BigQuery. BigQuery is Google Cloud's fully managed, serverless data warehouse. It supports SQL queries at petabyte scale with no infrastructure to manage. Cloud SQL is for OLTP, Dataproc is for Hadoop/Spark, and Dataflow is for stream/batch processing.

Answer

Cloud SQL

Answer

Dataproc

Answer

Dataflow

Question 7

An organisation needs to block common web attacks like SQL injection and cross-site scripting (XSS) at the edge of Google's network, before traffic reaches their applications. Which Google Cloud service should they use?

Accepted Answer

Cloud Armor. Cloud Armor is Google's web application firewall (WAF) service that protects against web attacks at the edge. It integrates with Cloud Load Balancing and Cloud CDN. Cloud CDN caches content, Cloud Load Balancing distributes traffic, and Cloud IDS is for network threat detection.

Answer

Cloud CDN

Answer

Cloud IDS

Answer

Cloud Load Balancing

Question 8

A developer wants to trigger a serverless function whenever a new object is uploaded to a Cloud Storage bucket. Which Google Cloud service should they use?

Accepted Answer

Cloud Functions. Cloud Functions is an event-driven serverless compute service that can be triggered by Cloud Storage events such as object finalise/create. Cloud Run can also be triggered by events via Eventarc, but Cloud Functions is the simpler choice for small code snippets triggered by events. Dataflow and App Engine are not designed for event-triggered functions from Cloud Storage.

Answer

Cloud Run

Answer

App Engine

Answer

Dataflow

Question 9

A data analyst wants to create interactive dashboards and reports using data from BigQuery, without writing code. Which Google Cloud BI tool should they use?

Accepted Answer

Looker Studio. Looker Studio is a free, self-service BI tool that allows users to create interactive dashboards and reports from various data sources including BigQuery, with a drag-and-drop interface. Looker is a more advanced enterprise BI platform. Data Studio is the former name; it is now Looker Studio. Dataflow is for data processing.

Answer

Data Studio

Answer

Dataflow

Answer

Looker

Question 10

A company has a batch processing job that reads data from Cloud Storage, transforms it, and writes to BigQuery. The job runs nightly and takes approximately 2 hours. The team wants to reduce costs by using a managed service that automatically provisions and de-provisions resources. Which service should they use?

Accepted Answer

Dataflow. Dataflow is a managed service that automatically scales resources up and down for batch and stream processing. It reads from Cloud Storage, transforms data, and writes to BigQuery. Dataproc is also managed but requires cluster configuration and is more suited for Hadoop/Spark. Cloud Composer is for workflow orchestration, not data transformation. Cloud Functions is not suitable for long-running batch jobs.

Answer

Cloud Composer

Answer

Cloud Functions

Answer

Dataproc

Question 11

A DevOps team wants to automatically build a Docker image from a GitHub repository and store it in a private registry whenever a new tag is pushed. Which Google Cloud services should they combine?

Accepted Answer

Cloud Build and Artifact Registry. Cloud Build can be triggered by GitHub events (like tag push) to build a container image and push it to Artifact Registry. Artifact Registry is the managed container registry. Container Registry is deprecated. Cloud Source Repositories is a Git repository, not a registry. Cloud Functions could trigger a build but is not the primary service.

Answer

Cloud Build and Container Registry

Answer

Cloud Source Repositories and Container Registry

Answer

Cloud Functions and Artifact Registry

Question 12

A company runs a high-performance computing (HPC) workload on Compute Engine that requires low-latency, high-throughput scratch storage. The workload is checkpointed every hour. Which TWO storage options should the engineer consider for the scratch storage? (Choose 2)

Accepted Answer

Persistent Disk (SSD). For HPC scratch storage, local SSDs provide very high IOPS and low latency but are ephemeral. Persistent Disk balanced or SSD provides durable block storage with good performance, but local SSDs are often preferred for scratch due to lower latency. Cloud Storage is object storage, not block. Filestore is file storage but typically has higher latency than local SSD. The best options are local SSD for performance and Persistent Disk for durability if checkpointed data needs to persist.

Answer

Persistent Disk (HDD)

Answer

Filestore

Answer

Cloud Storage

Question 13

A startup is building a mobile app that needs to store user profiles and preferences with low latency. The data is unstructured and frequently read/written. Which TWO Google Cloud database services are most suitable? (Choose 2)

Accepted Answer

Bigtable. Firestore is a NoSQL document database optimised for mobile/web apps with low-latency reads/writes. Bigtable is also NoSQL but designed for high-throughput time-series data. Memorystore is a cache, not a primary database. Cloud SQL is relational. The best options are Firestore for user profiles and preferences (unstructured, low-latency) and Bigtable if the scale is very high, but typically Firestore is the go-to for mobile. However, the question asks for TWO; Bigtable is also NoSQL and can be used for user data but is overkill. Alternatively, Firestore and Memorystore can be combined: Firestore as primary, Memorystore as cache. But Memorystore is a cache, not a database. The question says 'database services'. So likely Firestore and Bigtable are both NoSQL databases. But for user profiles, Firestore is more appropriate. I'll select Firestore and Bigtable as two NoSQL options.

Answer

Memorystore

Answer

Cloud Spanner

Answer

Cloud SQL

Question 14

A company is migrating a legacy monolithic application to Google Cloud. They want to reduce operational overhead by eliminating server management while keeping the ability to run containers. The application has unpredictable traffic patterns and needs to scale to zero when idle. Which compute option is the best fit?

Accepted Answer

Cloud Run. Cloud Run is a serverless container platform that automatically scales to zero when idle, eliminating server management and cost during idle periods. GKE requires cluster management, Compute Engine is not serverless, and App Engine Flex requires VMs always running.

Answer

Google Kubernetes Engine (GKE)

Answer

App Engine Flexible Environment

Answer

Compute Engine with managed instance groups

Question 15

What is the primary benefit of using preemptible VMs on Compute Engine?

Accepted Answer

Cost savings for fault-tolerant workloads. Preemptible VMs are significantly cheaper than standard VMs but can be terminated at any time. They are ideal for fault-tolerant, batch workloads.

Answer

Support for live migration

Answer

Higher performance than standard VMs

Answer

Guaranteed availability of resources