Cloud Digital Leader Free Practice Questions — Page 8
Question 71
An organization is developing a new container-based application. They do not know how popular the application will be when launched and they do not want to pay for idle infrastructure resources. Which benefit of serverless computing will address this concern?
A. Disaster recovery
B. Reduced development costs
C. Scalability
D. Built-in security
Show Answer
Correct Answer: C
Explanation: Serverless computing automatically scales resources up and down based on demand, so the organization does not need to provision capacity in advance or pay for idle infrastructure. This elasticity directly addresses unpredictable application popularity while supporting a pay-for-use model.
Question 72
An organization has a small development team that has created a web application which runs in a single container. They need a simple, serverless, and scalable way to host their container. Which Google service should the organization use?
A. Compute Engine
B. App Engine
C. Kubernetes Engine
D. Cloud Run
Show Answer
Correct Answer: D
Explanation: Cloud Run is the best fit because it is a fully managed, serverless platform designed to run containerized applications. It automatically scales based on traffic and requires no infrastructure or Kubernetes cluster management. Compute Engine requires VM management, App Engine is a PaaS not primarily focused on arbitrary container deployment, and Google Kubernetes Engine adds unnecessary operational complexity for a single-container web application.
Question 73
An organization has hired a team of data scientists and developers. They want to create unique value in their business by coding an advanced machine learning model in Vertex AI Workbench. Which service should the organization use to train the model?
A. Custom training
B. AutoML
C. Compute Engine
D. Prebuilt APIs
Show Answer
Correct Answer: A
Explanation: Custom training is the correct choice because the organization has data scientists and developers who want to code and train an advanced machine learning model in Vertex AI Workbench. Vertex AI Custom Training supports user-defined training code, custom frameworks, and full control over the training process. AutoML is intended for automated model creation with minimal coding, Compute Engine is general-purpose infrastructure rather than a Vertex AI training service, and Prebuilt APIs are for inference using existing Google models, not training custom models.
Question 74
Which scenario uses machine learning to unlock business value from unstructured data?
A. Analyzing tabular records of product defects to predict future maintenance cycles.
B. Recommending new products based on previous purchases.
C. Monitoring financial transactions to identify potential fraud and risk.
D. Determining customer sentiments from call center voice recordings.
Show Answer
Correct Answer: D
Explanation: The key phrase is 'unstructured data.' Call center voice recordings are unstructured audio data, and using machine learning (speech recognition and NLP/sentiment analysis) to determine customer sentiment is a classic example of extracting business value from unstructured data. The other options primarily involve structured transactional or tabular data.
Question 75
An organization wants to collect and store all logs generated by applications running in Google Cloud. Which service should they use?
A. Cloud Profiler
B. Cloud Monitoring
C. Cloud Trace
D. Cloud Logging
Show Answer
Correct Answer: D
Explanation: Cloud Logging is Google Cloud's managed logging service for collecting, storing, searching, analyzing, and routing logs generated by applications and Google Cloud resources. Cloud Monitoring is for metrics, Cloud Trace is for distributed tracing, and Cloud Profiler is for performance profiling.
Question 76
An organization is running Kubernetes applications across multiple cloud environments. They want a consistent and centralized management platform. Which service should they choose?
A. Cloud Functions
B. GKE Enterprise
C. Cloud Run
D. Compute Engine
Show Answer
Correct Answer: B
Explanation: GKE Enterprise (formerly Anthos) is designed to provide centralized, consistent management of Kubernetes clusters and applications across hybrid and multi-cloud environments. Cloud Functions and Cloud Run are serverless execution platforms, and Compute Engine provides virtual machines rather than centralized Kubernetes management.
Question 77
When is data automatically encrypted in Google Cloud?
A. When it is in transit only,
B. When it is at rest and in transit.
C. Data is not automatically encrypted by default.
D. When it is at rest only.
Show Answer
Correct Answer: B
Explanation: Google Cloud automatically encrypts customer data at rest by default and encrypts data in transit across its infrastructure and via TLS-supported connections. Therefore the correct choice is that data is automatically encrypted both at rest and in transit.
Question 78
An organization wants to build a data pipeline to transform its data so it can be reconciled in a data warehouse. The solution must be scalable and require little or no management. Which Google product or service should the organization choose?
A. Cloud Bigtable
B. Cloud Storage
C. Pub/Sub
D. Dataflow
Show Answer
Correct Answer: D
Explanation: Dataflow is Google Cloud's fully managed, autoscaling data processing service designed for building batch and streaming ETL/data transformation pipelines. It is the appropriate choice for transforming data before loading it into a data warehouse with minimal operational management. Cloud Bigtable is a NoSQL database, Cloud Storage is object storage, and Pub/Sub is a messaging service rather than a transformation engine.
Question 79
How does the resource hierarchy in Google Cloud help organizations implement security policies?
A. Policies can be applied at the folder level and are inherited by projects inside the folder.
B. Projects in the resource hierarchy are not affected by security policies.
C. Policies can only be applied at the organization level and affect all projects.
D. Policies can only be applied to individual projects.
Show Answer
Correct Answer: A
Explanation: Google Cloud's resource hierarchy (Organization → Folders → Projects → Resources) supports inheritance of IAM and organization policies. Policies can be applied at the organization, folder, or project level. A policy applied at a folder is inherited by the projects and resources beneath it. Options C and D are incorrect because policies are not limited to only the organization or only individual projects, and B is incorrect because projects are affected by inherited security policies.
Question 80
What is the typical cloud spending behavior of most organizations?
A. Decentralized and variable
B. Centralized and variable
C. Decentralized and fixed
D. Centralized and fixed
Show Answer
Correct Answer: A
Explanation: Most organizations experience decentralized and variable cloud spending. Cloud resources are often provisioned by multiple teams or business units rather than through a single centralized purchasing process, and costs fluctuate because cloud services are primarily consumption-based (pay-as-you-go). This combination makes spending both decentralized and variable.
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