Valid Professional-Cloud-Architect Exam Q&A PDF Professional-Cloud-Architect Dump is Ready (Updated 230 Questions)
Exam Questions and Answers for Professional-Cloud-Architect Study Guide
NEW QUESTION 126
You are designing a large distributed application with 30 microservices. Each of your distributed microservices needs to connect to a database back-end. You want to store the credentials securely.
Where should you store the credentials?
- A. In an environment variable
- B. In the source code
- C. In a secret management system
- D. In a config file that has restricted access through ACLs
Answer: C
Explanation:
https://cloud.google.com/docs/authentication/production#providing_credentials_to_your_application
NEW QUESTION 127
A development manager is building a new application. He asks you to review his requirements and identify what cloud technologies he can use to meet them. The application must:
1. Be based on open-source technology for cloud portability
2. Dynamically scale compute capacity based on demand
3. Support continuous software delivery
4. Run multiple segregated copies of the same application stack
5. Deploy application bundles using dynamic templates
6. Route network traffic to specific services based on URL
Which combination of technologies will meet all of his requirements?
- A. Google Kubernetes Engine and Cloud Load Balancing
- B. Google Kubernetes Engine, Jenkins, and Cloud Load Balancing
- C. Google Kubernetes Engine, Jenkins, and Helm
- D. Google Kubernetes Engine and Cloud Deployment Manager
Answer: B
Explanation:
Jenkins is an open-source automation server that lets you flexibly orchestrate your build, test, and deployment pipelines. Kubernetes Engine is a hosted version of Kubernetes, a powerful cluster manager and orchestration system for containers.
When you need to set up a continuous delivery (CD) pipeline, deploying Jenkins on Kubernetes Engine provides important benefits over a standard VM-based deployment Incorrect Answers:
A: Helm is a tool for managing Kubernetes charts. Charts are packages of pre-configured Kubernetes resources.
Use Helm to:
* Find and use popular software packaged as Kubernetes charts
* Share your own applications as Kubernetes charts
* Create reproducible builds of your Kubernetes applications
* Intelligently manage your Kubernetes manifest files
* Manage releases of Helm packages
Reference: https://cloud.google.com/solutions/jenkins-on-kubernetes-engine
NEW QUESTION 128
Operational parameters such as oil pressure are adjustable on each of TerramEarth's vehicles to increase their efficiency, depending on their environmental conditions. Your primary goal is to increase the operating efficiency of all 20 million cellular and unconnected vehicles in the field.
How can you accomplish this goal?
- A. Have you engineers inspect the data for patterns, and then create an algorithm with rules that make operational adjustments automatically
- B. Capture all operating data, train machine learning models that identify ideal operations, and host in Google Cloud Machine Learning (ML) Platform to make operational adjustments automatically
- C. Capture all operating data, train machine learning models that identify ideal operations, and run locally to make operational adjustments automatically
- D. Implement a Google Cloud Dataflow streaming job with a sliding window, and use Google Cloud Messaging (GCM) to make operational adjustments automatically
Answer: B
Explanation:
Explanation/Reference: https://cloud.google.com/customers/ocado/
TerramEarth, B
Testlet 1
Company Overview
TerramEarth manufactures heavy equipment for the mining and agricultural industries. About 80% of their business is from mining and 20% from agriculture. They currently have over 500 dealers and service centers in
100 countries. Their mission is to build products that make their customers more productive.
Solution Concept
There are 20 million TerramEarth vehicles in operation that collect 120 fields of data per second. Data is stored locally on the vehicle and can be accessed for analysis when a vehicle is serviced. The data is downloaded via a maintenance port. This same port can be used to adjust operational parameters, allowing the vehicles to be upgraded in the field with new computing modules.
Approximately 200,000 vehicles are connected to a cellular network, allowing TerramEarth to collect data directly. At a rate of 120 fields of data per second, with 22 hours of operation per day, TerramEarth collects a total of about 9 TB/day from these connected vehicles.
Existing Technical Environment
TerramEarth's existing architecture is composed of Linux and Windows-based systems that reside in a single
U.S, west coast based data center. These systems gzip CSV files from the field and upload via FTP, and place the data in their data warehouse. Because this process takes time, aggregated reports are based on data that is 3 weeks old.
With this data, TerramEarth has been able to preemptively stock replacement parts and reduce unplanned downtime of their vehicles by 60%. However, because the data is stale, some customers are without their vehicles for up to 4 weeks while they wait for replacement parts.
Business Requirements
* Decrease unplanned vehicle downtime to less than 1 week
* Support the dealer network with more data on how their customers use their equipment to better position new products and services
* Have the ability to partner with different companies - especially with seed and fertilizer suppliers in the fast- growing agricultural business - to create compelling joint offerings for their customers Technical Requirements
* Expand beyond a single datacenter to decrease latency to the American Midwest and east coast
* Create a backup strategy
* Increase security of data transfer from equipment to the datacenter
* Improve data in the data warehouse
* Use customer and equipment data to anticipate customer needs
Application 1: Data ingest
A custom Python application reads uploaded datafiles from a single server, writes to the data warehouse.
Compute:
* Windows Server 2008 R2
- 16 CPUs
- 128 GB of RAM
- 10 TB local HDD storage
Application 2: Reporting
An off the shelf application that business analysts use to run a daily report to see what equipment needs repair.
Only 2 analysts of a team of 10 (5 west coast, 5 east coast) can connect to the reporting application at a time.
Compute:
* Off the shelf application. License tied to number of physical CPUs
- Windows Server 2008 R2
- 16 CPUs
- 32 GB of RAM
- 500 GB HDD
Data warehouse:
* A single PostgreSQL server
- RedHat Linux
- 64 CPUs
- 128 GB of RAM
- 4x 6TB HDD in RAID 0
Executive Statement
Our competitive advantage has always been in our manufacturing process, with our ability to build better vehicles for lower cost than our competitors. However, new products with different approaches are constantly being developed, and I'm concerned that we lack the skills to undergo the next wave of transformations in our industry. My goals are to build our skills while addressing immediate market needs through incremental innovations.
NEW QUESTION 129
Mountkirk Games needs to create a repeatable and configurable mechanism for deploying isolated
application environments. Developers and testers can access each other's environments and resources,
but they cannot access staging or production resources. The staging environment needs access to some
services from production.
What should you do to isolate development environments from staging and production?
- A. Create one project for development, a second for staging and a third for production
- B. Create one subnetwork for development and another for staging and production
- C. Create a project for development and test and another for staging and production
- D. Create a network for development and test and another for staging and production
Answer: C
Explanation:
Explanation/Reference:
References: https://cloud.google.com/appengine/docs/standard/go/creating-separate-dev-environments
NEW QUESTION 130
For this question, refer to the Dress4Win case study.
Dress4Win has asked you to recommend machine types they should deploy their application servers to.
How should you proceed?
- A. Perform a mapping of the on-premises physical hardware cores and RAM to the nearest machine types in the cloud.
- B. Recommend that Dress4Win deploy into production with the smallest instances available, monitor them over time, and scale the machine type up until the desired performance is reached.
- C. Recommend that Dress4Win deploy application servers to machine types that offer the highest RAM to CPU ratio available.
- D. Identify the number of virtual cores and RAM associated with the application server virtual machines align them to a custom machine type in the cloud, monitor performance, and scale the machine types up until the desired performance is reached.
Answer: A
NEW QUESTION 131
Your company is designing its application landscape on Compute Engine. Whenever a zonal outage occurs, the application should be restored in another zone as quickly as possible with the latest application data. You need to design the solution to meet this requirement. What should you do?
- A. Create a snapshot schedule for the disk containing the application data. Whenever a zonal outage occurs, use the latest snapshot to restore the disk in the same zone.
- B. Create a snapshot schedule for the disk containing the application data. Whenever a zonal outage occurs, use the latest snapshot to restore the disk in another zone within the same region.
- C. Configure the Compute Engine instances with an instance template for the application, and use a regional persistent disk for the application data. Whenever a zonal outage occurs, use the instance template to spin up the application in another region. Use the regional persistent disk for the application data,
- D. Configure the Compute Engine instances with an instance template for the application, and use a regional persistent disk for the application data. Whenever a zonal outage occurs, use the instance template to spin up the application in another zone in the same region. Use the regional persistent disk for the application data.
Answer: C
NEW QUESTION 132
You write a Python script to connect to Google BigQuery from a Google Compute Engine virtual machine.
The script is printing errors that it cannot connect to BigQuery. What should you do to fix the script?
- A. Run your script on a new virtual machine with the BigQuery access scope enabled
- B. Install the latest BigQuery API client library for Python
- C. Install the bq component for gccloud with the command gcloud components install bq.
- D. Create a new service account with BigQuery access and execute your script with that user
Answer: B
Explanation:
Explanation
https://cloud.google.com/bigquery/docs/python-client-migration
Applications that use BigQuery must be associated with a Google Cloud Platform Console project with the BigQuery API enabled.
Reference: https://cloud.google.com/bigquery/create-simple-app-api
NEW QUESTION 133
For this question, refer to the Dress4Win case study. Considering the given business requirements, how would you automate the deployment of web and transactional data layers?
- A. Deploy Nginx and Tomcat using Cloud Launcher. Deploy a MySQL server using Cloud Launcher. Deploy Jenkins to Compute Engine using Cloud Deployment Manager scripts.
- B. Migrate Nginx and Tomcat to App Engine. Deploy a Cloud Datastore server to replace the MySQL server in a high-availability configuration. Deploy Jenkins to Compute Engine using Cloud Launcher.
- C. Migrate Nginx and Tomcat to App Engine. Deploy a MySQL server using Cloud Launcher. Deploy Jenkins to Compute Engine using Cloud Launcher.
- D. Deploy Nginx and Tomcat using Cloud Deployment Manager to Compute Engine. Deploy a Cloud SQL server to replace MySQL. Deploy Jenkins using Cloud Deployment Manager.
Answer: B
NEW QUESTION 134
You are monitoring Google Kubernetes Engine (GKE) clusters in a Cloud Monitoring workspace. As a Site Reliability Engineer (SRE), you need to triage incidents quickly. What should you do?
- A. Navigate the predefined dashboards in the Cloud Monitoring workspace, create custom metrics, and install alerting software on a Compute Engine instance.
- B. Write a shell script that gathers metrics from GKE nodes, publish these metrics to a Pub/Sub topic, export the data to BigQuery, and make a Data Studio dashboard.
- C. Create a custom dashboard in the Cloud Monitoring workspace for each incident, and then add metrics and create alert policies.
- D. Navigate the predefined dashboards in the Cloud Monitoring workspace, and then add metrics and create alert policies.
Answer: D
Explanation:
Reference:
https://cloud.google.com/stackdriver/docs/solutions/gke/legacy-stackdriver/monitoring
NEW QUESTION 135
You write a Python script to connect to Google BigQuery from a Google Compute Engine virtual machine. The script is printing errors that it cannot connect to BigQuery. What should you do to fix the script?
- A. Install the latest BigQuery API client library for Python
- B. Run your script on a new virtual machine with the BigQuery access scope enabled
- C. Install the bq component for gccloud with the command gcloud components install bq.
- D. Create a new service account with BigQuery access and execute your script with that user
Answer: B
Explanation:
Reference:
The error is most like caused by the access scope issue. When create new instance, you have the default Compute engine default service account but most serves access including BigQuery is not enable. Create an instance Most access are not enabled by default You have default service account but don't have the permission (scope) you can stop the instance, edit, change scope and restart it to enable the scope access. Of course, if you Run your script on a new virtual machine with the BigQuery access scope enabled, it also works
https://cloud.google.com/compute/docs/access/service-accounts
NEW QUESTION 136
A recent audit that a new network was created in Your GCP project. In this network, a GCE instance has an SSH port open the world. You want to discover this network's origin. What should you do?
- A. Connect to the GCE instance using project SSH Keys. Identify previous logins in system logs, and match these with the project owners list.
- B. Navigate to the Activity page in the Home section. Set category to Data Access and search for Create VM entry.
- C. Search for Create VM entry in the Stackdriver alerting console.
- D. In the logging section of the console, specify GCE Network as the logging section. Search for the Create Insert entry.
Answer: D
Explanation:
Incorrect Answers:
A: To use the Stackdriver alerting console we must first set up alerting policies.
B: Data access logs only contain read-only operations.
Audit logs help you determine who did what, where, and when.
Cloud Audit Logging returns two types of logs:
NEW QUESTION 137
Case Study: 4 - Dress4Win case study
Company Overview
Dress4win is a web-based company that helps their users organize and manage their personal wardrobe using a website and mobile application. The company also cultivates an active social network that connects their users with designers and retailers. They monetize their services through advertising, e-commerce, referrals, and a freemium app model.
Company Background
Dress4win's application has grown from a few servers in the founder's garage to several hundred servers and appliances in a colocated data center. However, the capacity of their infrastructure is now insufficient for the application's rapid growth. Because of this growth and the company's desire to innovate faster, Dress4win is committing to a full migration to a public cloud.
Solution Concept
For the first phase of their migration to the cloud, Dress4win is considering moving their development and test environments. They are also considering building a disaster recovery site, because their current infrastructure is at a single location. They are not sure which components of their architecture they can migrate as is and which components they need to change before migrating them.
Existing Technical Environment
The Dress4win application is served out of a single data center location.
Databases:
MySQL - user data, inventory, static data
* Redis - metadata, social graph, caching
* Application servers:
Tomcat - Java micro-services
* Nginx - static content
* Apache Beam - Batch processing
* Storage appliances:
iSCSI for VM hosts
* Fiber channel SAN - MySQL databases
* NAS - image storage, logs, backups
* Apache Hadoop/Spark servers:
Data analysis
* Real-time trending calculations
* MQ servers:
Messaging
* Social notifications
* Events
* Miscellaneous servers:
Jenkins, monitoring, bastion hosts, security scanners
* Business Requirements
* Build a reliable and reproducible environment with scaled parity of production. Improve security by defining and adhering to a set of security and Identity and Access Management (IAM) best practices for cloud.
Improve business agility and speed of innovation through rapid provisioning of new resources.
Analyze and optimize architecture for performance in the cloud. Migrate fully to the cloud if all other requirements are met.
Technical Requirements
Evaluate and choose an automation framework for provisioning resources in cloud. Support failover of the production environment to cloud during an emergency. Identify production services that can migrate to cloud to save capacity.
Use managed services whenever possible.
Encrypt data on the wire and at rest.
Support multiple VPN connections between the production data center and cloud environment.
CEO Statement
Our investors are concerned about our ability to scale and contain costs with our current infrastructure. They are also concerned that a new competitor could use a public cloud platform to offset their up-front investment and freeing them to focus on developing better features.
CTO Statement
We have invested heavily in the current infrastructure, but much of the equipment is approaching the end of its useful life. We are consistently waiting weeks for new gear to be racked before we can start new projects. Our traffic patterns are highest in the mornings and weekend evenings; during other times, 80% of our capacity is sitting idle.
CFO Statement
Our capital expenditure is now exceeding our quarterly projections. Migrating to the cloud will likely cause an initial increase in spending, but we expect to fully transition before our next hardware refresh cycle. Our total cost of ownership (TCO) analysis over the next 5 years puts a cloud strategy between 30 to 50% lower than our current model.
For this question, refer to the Dress4Win case study.
As part of their new application experience, Dress4Wm allows customers to upload images of themselves. The customer has exclusive control over who may view these images. Customers should be able to upload images with minimal latency and also be shown their images quickly on the main application page when they log in. Which configuration should Dress4Win use?
- A. Use a distributed file system to store customers' images. As storage needs increase, add more persistent disks and/or nodes. Use a Google Cloud SQL database to maintain metadata that maps each customer's ID to their image files.
- B. Store image files in a Google Cloud Storage bucket. Use Google Cloud Datastore to maintain metadata that maps each customer's ID and their image files.
- C. Store image files in a Google Cloud Storage bucket. Add custom metadata to the uploaded images in Cloud Storage that contains the customer's unique ID.
- D. Use a distributed file system to store customers' images. As storage needs increase, add more persistent disks and/or nodes. Assign each customer a unique ID, which sets each file's owner attribute, ensuring privacy of images.
Answer: B
NEW QUESTION 138
You write a Python script to connect to Google BigQuery from a Google Compute Engine virtual machine.
The script is printing errors that it cannot connect to BigQuery. What should you do to fix the script?
- A. Install the latest BigQuery API client library for Python
- B. Run your script on a new virtual machine with the BigQuery access scope enabled
- C. Install the bq component for gccloud with the command gcloud components install bq.
- D. Create a new service account with BigQuery access and execute your script with that user
Answer: B
Explanation:
Explanation
https://cloud.google.com/compute/docs/access/service-accounts
NEW QUESTION 139
Your company has decided to build a backup replica of their on-premises user authentication PostgreSQL database on Google Cloud Platform. The database is 4 TB, and large updates are frequent. Replication requires private address space communication. Which networking approach should you use?
- A. A NAT and TLS translation gateway installed on-premises
- B. A Google Compute Engine instance with a VPN server installed connected to the data center network
- C. Google Cloud Dedicated Interconnect
- D. Google Cloud VPN connected to the data center network
Answer: C
Explanation:
Explanation
https://cloud.google.com/docs/enterprise/best-practices-for-enterprise-organizations Google Cloud Dedicated Interconnect provides direct physical connections and RFC 1918 communication between your on-premises network and Google's network. Dedicated Interconnect enables you to transfer large amounts of data between networks, which can be more cost effective than purchasing additional bandwidth over the public Internet or using VPN tunnels.
Benefits:
* Traffic between your on-premises network and your VPC network doesn't traverse the public Internet.
Traffic traverses a dedicated connection with fewer hops, meaning there are less points of failure where traffic might get dropped or disrupted.
* Your VPC network's internal (RFC 1918) IP addresses are directly accessible from your on-premises network. You don't need to use a NAT device or VPN tunnel to reach internal IP addresses. Currently, you can only reach internal IP addresses over a dedicated connection. To reach Google external IP addresses, you must use a separate connection.
* You can scale your connection to Google based on your needs. Connection capacity is delivered over one or more 10 Gbps Ethernet connections, with a maximum of eight connections (80 Gbps total per interconnect).
* The cost of egress traffic from your VPC network to your on-premises network is reduced. A dedicated connection is generally the least expensive method if you have a high-volume of traffic to and from Google's network.
References: https://cloud.google.com/interconnect/docs/details/dedicated
NEW QUESTION 140
To speed up data retrieval, more vehicles will be upgraded to cellular connections and be able to transmit data to the ETL process. The current FTP process is error-prone and restarts the data transfer from the start of the file when connections fail, which happens often. You want to improve the reliability of the solution and minimize data transfer time on the cellular connections.
What should you do?
- A. Directly transfer the files to different Google Cloud Multi-Regional Storage bucket locations in US, EU, and Asia using Google APIs over HTTP(S). Run the ETL process using the data in the bucket
- B. Directly transfer the files to a different Google Cloud Regional Storage bucket location in US, EU, and Asia using Google APIs over HTTP(S). Run the ETL process to retrieve the data from each Regional bucket
- C. Use one Google Container Engine cluster of FTP servers. Save the data to a Multi-Regional bucket.
Run the ETL process using data in the bucket - D. Use multiple Google Container Engine clusters running FTP servers located in different regions. Save the data to Multi-Regional buckets in US, EU, and Asia. Run the ETL process using the data in the bucket
Answer: B
NEW QUESTION 141
As part of implementing their disaster recovery plan, your company is trying to replicate their production MySQL database from their private data center to their GCP project using a Google Cloud VPN connection.
They are experiencing latency issues and a small amount of packet loss that is disrupting the replication.
What should they do?
- A. Send the replicated transaction to Google Cloud Pub/Sub.
- B. Configure a Google Cloud Dedicated Interconnect.
- C. Configure their replication to use UDP.
- D. Add additional VPN connections and load balance them.
- E. Restore their database daily using Google Cloud SQL.
Answer: B
NEW QUESTION 142
Your company plans to migrate a multi-petabyte data set to the cloud. The data set must be available 24hrs a day. Your business analysts have experience only with using a SQL interface. How should you store the data to optimize it for ease of analysis?
- A. Load data into Google BigQuery.
- B. Put flat files into Google Cloud Storage.
- C. Insert data into Google Cloud SQL.
- D. Stream data into Google Cloud Datastore.
Answer: A
Explanation:
BigQuery is Google's serverless, highly scalable, low cost enterprise data warehouse designed to make all your data analysts productive. Because there is no infrastructure to manage, you can focus on analyzing data to find meaningful insights using familiar SQL and you don't need a database administrator.
BigQuery enables you to analyze all your data by creating a logical data warehouse over managed, columnar storage as well as data from object storage, and spreadsheets.
References: https://cloud.google.com/bigquery/
Reference:
Google Big Query is for multi peta byte storage , HA(High availability) which means 24 hours, SQL interface .
https://medium.com/google-cloud/the-12-components-of-google-bigquery-c2b49829a7c7
https://cloud.google.com/solutions/bigquery-data-warehouse
https://cloud.google.com/bigquery/
NEW QUESTION 143
You have created several preemptible Linux virtual machine instances using Google Compute Engine.
You want to properly shut down your application before the virtual machines are preempted. What should you do?
- A. Create a shutdown script, registered as a xinetd service in Linux, and use the gcloud compute instances add-metadata command to specify the service URL as the value for a new metadata entry with the key shutdown-script-url
- B. Create a shutdown script and use it as the value for a new metadata entry with the key shutdown- script in the Cloud Platform Console when you create the new virtual machine instance.
- C. Create a shutdown script named k99.shutdown in the /etc/rc.6.d/ directory.
- D. Create a shutdown script registered as a xinetd service in Linux and configure a Stackdnver endpoint check to call the service.
Answer: B
Explanation:
https://cloud.google.com/compute/docs/shutdownscript
NEW QUESTION 144
Your customer support tool logs all email and chat conversations to Cloud Bigtable for retention and analysis. What is the recommended approach for sanitizing this data of personally identifiable information or payment card information before initial storage?
- A. De-identify the data with the Cloud Data Loss Prevention API
- B. Use regular expressions to find and redact phone numbers, email addresses, and credit card numbers
- C. Encrypt all data using elliptic curve cryptography
- D. Hash all data using SHA256
Answer: A
Explanation:
https://cloud.google.com/solutions/pci-dss-compliance-
ingcp#using_data_loss_prevention_api_to_sanitize_data
NEW QUESTION 145
One of the developers on your team deployed their application In Google Container Engine with the Dockerfile below. They report that their application deployments are taking too long.
You want to optimize this Dockerfile for faster deployment times without adversely affecting the app's functionality. Which two actions should you take? Choose 2 answers
- A. Copy the source after the package dependencies (Python and pip) are installed.
- B. Use a slimmed-down base image like Alpine linux.
- C. Use larger machine types for your Google Container Engine node pools.
- D. Remove Python after running pip.
- E. Remove dependencies from requirements.txt.
Answer: A,D
NEW QUESTION 146
Your company has developed a monolithic, 3-tier application to allow external users to upload and share files.
The solution cannot be easily enhanced and lacks reliability. The development team would like to re-architect the application to adopt microservices and a fully managed service approach, but they need to convince their leadership that the effort is worthwhile. Which advantage(s) should they highlight to leadership?
- A. The process can be automated with Migrate for Compute Engine.
- B. The new approach will be significantly less costly, make it easier to manage the underlying infrastructure, and automatically manage the CI/CD pipelines.
- C. The new approach will make it easier to decouple infrastructure from application, develop and release new features, manage the underlying infrastructure, manage CI/CD pipelines and perform A/B testing, and scale the solution if necessary.
- D. The monolithic solution can be converted to a container with Docker. The generated container can then be deployed into a Kubernetes cluster.
Answer: C
NEW QUESTION 147
Your company wants to track whether someone is present in a meeting room reserved for a scheduled meeting.
There are 1000 meeting rooms across 5 offices on 3 continents. Each room is equipped with a motion sensor that reports its status every second. The data from the motion detector includes only a sensor ID and several different discrete items of information. Analysts will use this data, together with information about account owners and office locations. Which database type should you use?
- A. Blobstore
- B. Relational
- C. Flat file
- D. NoSQL
Answer: D
Explanation:
Explanation
Relational databases were not designed to cope with the scale and agility challenges that face modern applications, nor were they built to take advantage of the commodity storage and processing power available today.
NoSQL fits well for:
Developers are working with applications that create massive volumes of new, rapidly changing data types - structured, semi-structured, unstructured and polymorphic data.
NEW QUESTION 148
A lead engineer wrote a custom tool that deploys virtual machines in the legacy data center. He wants to migrate the custom tool to the new cloud environment. You want to advocate for the adoption of Google Cloud Deployment Manager.
What are two business risks of migrating to Cloud Deployment Manager? (Choose two.)
- A. Cloud Deployment Manager APIs could be deprecated in the future
- B. Cloud Deployment Manager requires a Google APIs service account to run
- C. Cloud Deployment Manager only supports automation of Google Cloud resources
- D. Cloud Deployment Manager uses Python
- E. Cloud Deployment Manager can be used to permanently delete cloud resources
- F. Cloud Deployment Manager is unfamiliar to the company's engineers
Answer: A,C
Explanation:
Explanation/Reference:
NEW QUESTION 149
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