Cloud Digital Leader Google Cloud Products and Services Practice Test 10 — 15 Questions

Question 1

A DevOps engineer wants to automatically delete a Cloud Storage object after 30 days from creation. The object is stored in a bucket with the 'Standard' storage class. Which approach should the engineer use?

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

Accepted Answer

Add a lifecycle rule to delete objects after 30 days. Object Lifecycle Management rules can be configured on a bucket to delete objects based on age (days since creation). The rule sets a condition (e.g., age: 30) and action (Delete). Changing the storage class or using bucket lock does not delete objects. Object versioning is for keeping multiple versions.

Answer

Set a retention policy on the bucket with a 30-day retention period

Answer

Change the storage class to 'Archive' which automatically deletes after 30 days

Answer

Enable object versioning and set a noncurrent time deletion of 30 days

Question 2

A company wants to migrate its on-premises MySQL database to Google Cloud with minimal changes to the application. Which managed database service should they use?

Accepted Answer

Cloud SQL for MySQL. Cloud SQL provides managed MySQL, PostgreSQL, and SQL Server databases. It is compatible with existing MySQL applications. Cloud Spanner is globally distributed but not drop-in MySQL. Firestore and Bigtable are NoSQL.

Answer

Cloud Spanner

Answer

Cloud Bigtable

Answer

Firestore

Question 3

A company runs a video processing application that triggers a function each time a new video is uploaded to Cloud Storage. The function transcodes the video and stores the result. Which compute service is BEST suited for this event-driven workload?

Accepted Answer

Cloud Functions. Cloud Functions is designed for event-driven triggers from Cloud Storage (e.g., object finalize). It is lightweight and cost-effective. Cloud Run is for containerized HTTP services. Compute Engine and GKE are overkill for simple event-driven tasks.

Answer

Compute Engine

Answer

Google Kubernetes Engine (GKE)

Answer

Cloud Run

Question 4

A data analyst needs to create interactive dashboards and reports from data stored in BigQuery. They want a fully managed business intelligence platform without building custom applications. Which Google Cloud product should they use?

Accepted Answer

Looker (Google Cloud's BI platform). Looker is a BI platform that connects to BigQuery and provides interactive dashboards, reports, and embedded analytics. Looker Studio is a free tool for simple visualizations. Data Studio is the old name. Vertex AI is for ML.

Answer

Looker Studio

Answer

Vertex AI

Answer

Data Studio

Question 5

A company wants to run a critical stateful application on Compute Engine with the highest availability. The application requires block storage that can survive a zone failure. Which TWO actions should they take? (Choose TWO)

Accepted Answer

Use regional Persistent Disk. Regional Persistent Disk replicates data across zones synchronously, surviving a zone failure. The instances should be in a regional managed instance group to distribute across zones. Zonal PD and single-zone MIG would not survive zone failure.

Answer

Place instances in a zonal managed instance group

Answer

Enable object versioning on a Cloud Storage bucket

Answer

Use zonal Persistent Disk

Question 6

A company is building a microservices architecture on Google Kubernetes Engine (GKE). They need to expose services externally with HTTPS, distribute traffic across the cluster, and protect against DDoS attacks. Which THREE Google Cloud services should they combine? (Choose THREE)

Accepted Answer

Cloud CDN. Cloud Load Balancing distributes external traffic, Cloud Armor provides DDoS and WAF protection, and Cloud CDN caches content and absorbs some DDoS. Cloud DNS resolves names but is not for traffic distribution. VPC firewall rules operate at network layer, not application.

Answer

Cloud DNS

Answer

VPC firewall rules

Question 7

A developer wants to deploy a serverless application that runs code in response to HTTP requests and events from other Google Cloud services. They also need to store configuration and session data in a fast, in-memory data store. Which TWO services should they use? (Choose TWO)

Accepted Answer

Cloud Functions. Cloud Functions handles HTTP and event-driven triggers serverlessly. Memorystore provides managed Redis/Memcached for caching and session storage. Cloud SQL is relational and not in-memory. Cloud Storage is object storage. Bigtable is NoSQL but not in-memory.

Answer

Cloud SQL

Answer

Cloud Bigtable

Answer

Cloud Storage

Question 8

A developer wants to deploy a containerized web application that automatically scales to zero when not in use, and they want to minimize operational overhead. Which compute service should they use?

Accepted Answer

Cloud Run. Cloud Run is a serverless compute platform that executes containers in a fully managed environment, automatically scaling from zero to thousands of requests per second. It is ideal for containerized stateless applications that need to scale down to zero. Google Kubernetes Engine (GKE) does not scale to zero, Compute Engine requires VM management, and App Engine Flexible does not support custom containers that scale to zero as seamlessly.

Answer

Google Kubernetes Engine (GKE)

Answer

Compute Engine

Answer

App Engine Flexible Environment

Question 9

A data engineer needs to process a continuous stream of clickstream events from multiple sources, aggregate them into 1-minute windows, and write the results to BigQuery for real-time dashboarding. The solution must handle exactly-once processing semantics. Which combination of services should they use?

Accepted Answer

Pub/Sub -> Dataflow -> BigQuery. Dataflow (Apache Beam) provides exactly-once processing semantics and can read from Pub/Sub, apply windowed aggregations, and write to BigQuery. Pub/Sub is the ingestion layer for streaming events. Cloud Functions and Cloud Run are not designed for stateful windowed aggregations at scale, and Cloud Dataproc (Hadoop/Spark) would require more overhead.

Answer

Pub/Sub -> Cloud Functions -> BigQuery

Answer

Cloud Storage -> Dataflow -> BigQuery

Answer

Pub/Sub -> Cloud Dataproc -> BigQuery

Question 10

A company needs to perform interactive SQL analytics on petabytes of data without managing any infrastructure. They need to query data stored in Cloud Storage and want the fastest query performance. Which Google Cloud service should they use?

Accepted Answer

BigQuery. BigQuery is a serverless, highly scalable data warehouse that supports SQL queries on data stored in Cloud Storage (external tables) or natively. It provides fast performance on petabyte-scale data without infrastructure management. Dataflow is for ETL, not ad-hoc analytics; Cloud SQL is for OLTP; Looker is a BI layer on top of a data warehouse.

Answer

Looker

Answer

Dataflow

Answer

Cloud SQL

Question 11

A developer is deploying a web application on Compute Engine and needs to distribute traffic across multiple VM instances in different regions. They also need SSL termination and health checks. Which Google Cloud networking service should they use?

Accepted Answer

Cloud Load Balancing. Cloud Load Balancing (HTTP(S) Load Balancer) is a global, scalable load balancing service that distributes traffic across instance groups in multiple regions, provides SSL termination, and performs health checks. Cloud CDN is for caching content; Cloud Armor is for security policies; VPC peering connects networks.

Answer

VPC peering

Answer

Cloud Armor

Answer

Cloud CDN

Question 12

A company has a batch processing job that runs once per day and can be interrupted without significant impact. They want to reduce costs by using Google Cloud infrastructure. Which compute option should they choose?

Accepted Answer

Preemptible VMs. Preemptible VMs offer significant cost savings (up to 60-91% discount) but can be terminated at any time by Google. They are ideal for fault-tolerant batch jobs. Spot VMs are similar but with a newer pricing model (no maximum runtime). Both are good, but Preemptible is the classic answer. Custom machine types are not cost-saving by themselves; standard VMs are more expensive.

Answer

Standard persistent disk

Answer

Sustained use discounts

Answer

Custom machine types

Question 13

A security engineer wants to block malicious traffic patterns at the edge of Google's network before it reaches their application. Which service should they configure?

Accepted Answer

Cloud Armor. Cloud Armor is a web application firewall (WAF) and DDoS protection service that works with Cloud Load Balancing to filter traffic based on IP addresses, geo-location, and Layer 7 attributes. Cloud CDN caches content, Cloud DNS resolves domain names, and VPC firewall rules protect at the instance level, not at the edge.

Answer

VPC firewall rules

Answer

Cloud DNS

Answer

Cloud CDN

Question 14

A startup is building a mobile app and needs a real-time database that synchronises data across user devices automatically. The data model is document-based, and the app needs offline support. Which database should they use?

Accepted Answer

Firestore. Firestore is a NoSQL document database designed for mobile and web apps with real-time synchronization, offline support, and automatic multi-device sync. Cloud SQL is relational and not designed for mobile offline sync. Bigtable is for time-series. Memorystore is a cache.

Answer

Cloud Bigtable

Answer

Cloud SQL

Answer

Memorystore

Question 15

A data scientist wants to train a custom machine learning model using their own data and deploy it for online predictions. They want a unified platform that manages the entire ML lifecycle from data preparation to model serving. Which service should they use?

Accepted Answer

Vertex AI. Vertex AI is Google Cloud's unified ML platform that covers data labeling, training, tuning, evaluation, and deployment (online prediction endpoints). AutoML is part of Vertex AI but focuses on automated model building. Cloud Functions is for serverless code, not ML. AI Platform (unified) is the old name for Vertex AI.

Answer

Cloud Functions

Answer

AutoML

Answer

AI Platform (Unified)