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| Section | Objectives |
|---|---|
| Topic 1: Digital Transformation with Google Cloud | - Understanding digital transformation concepts - Google Cloud value proposition - Business value of cloud adoption |
| Topic 2: Data and Artificial Intelligence | - Data analytics fundamentals on Google Cloud - Data-driven decision making - Machine learning and AI capabilities overview |
| Topic 3: Infrastructure and Application Modernization | - Cloud infrastructure fundamentals - Compute, storage, and networking basics - Application modernization approaches |
| Topic 4: Google Cloud Security and Operations | - Monitoring, logging, and operations tools - Identity and access management basics - Security principles in Google Cloud |
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NEW QUESTION # 137
What load balancer type is supported with Cloud Armor security policies?
Answer: B
Explanation:
Google Cloud Armor security policies protect your application by providing Layer 7 filtering and by scrubbing incoming requests for common web attacks or other Layer 7 attributes to potentially block traffic before it reaches your load balanced backend services or backend buckets. Each security policy is made up of a set of rules that filter traffic based on conditions such as an incoming request's IP address, IP range, region code, or request headers.
-> Google Cloud Armor security policies are available only for backend services behind an external HTTP(S) load balancer. The load balancer can be in Premium Tier or Standard Tier.
-> Google Cloud Armor security policies and IP DENY lists and ALLOW lists are available only for HTTP(S) load balancing.
Reference link- https://cloud.google.com/armor/docs/security-policy-overview
NEW QUESTION # 138
A manufacturing organization has a large collection of images labeled as intact or defective parts. They want to use this data to build a simple solution to detect faulty parts on their production line. They have no data science expertise. Which solution should they use?
Answer: B
Explanation:
The correct answer is D. AutoML. Here's why:
Context of the Questio n : The organization wants to build a solution to detect faulty parts on a production line using a large collection of labeled images (intact or defective parts). They do not have data science expertise, so they need a tool that simplifies the machine learning process.
Google Cloud Product Relevance:
AutoML is a suite of machine learning products that allows users to build custom models easily without needing deep expertise in machine learning or data science. It is designed to simplify the process of training, evaluating, and deploying models, especially in cases like image recognition where labeled datasets are already available.
AutoML Vision, a part of AutoML, would be ideal for this use case as it specifically handles image classification and can easily differentiate between intact and defective parts.
Why Not Other Options:
A . Discovery AI for Retail: This is a solution tailored for retail use cases like product discovery and search optimization, not for manufacturing defect detection.
B . Pre-trained APIs: While pre-trained APIs (like Vision API) can recognize general image patterns, they may not be specific enough for a custom use case like detecting defective parts.
C . Document AI: This service is designed for understanding and processing documents, not for analyzing images.
Google Cloud Digital Leader Reference:
For more information on AutoML, refer to the AutoML Vision documentation.
NEW QUESTION # 139
Your organization wants to migrate your on-premises environment to Google Cloud. The on-premises environment consists of containers and virtual machine instances. Which Google Cloud products can help to migrate the container images and the virtual machine disks?
Answer: A
Explanation:
Reference:
NEW QUESTION # 140
An organization wants to scale their existing virtual machine architecture as quickly as possible. Why should the organization use VMware Engine?
Answer: B
Explanation:
VMware Engine helps migrate and run virtual machines in Google Cloud with minimal changes to the VM architecture.
https://cloud.google.com/learn/what-is-a-virtual-machine
NEW QUESTION # 141
What is the difference between Standard and Coldline storage?
Answer: A
Explanation:
Reference:
Google Cloud Coldline is a new cold-tier storage for archival data with access frequency of less than once per year. Unlike other cold storage options, Nearline has no delays prior to data access, so now it is the leading solution among competitors.
NEW QUESTION # 142
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