[2021] Free Professional-Cloud-Architect Exam Dumps to Pass Exam Easily
Professional-Cloud-Architect Exam Dumps, Professional-Cloud-Architect Practice Test Questions
NEW QUESTION 90
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. Restore their database daily using Google Cloud SQL.
- B. Add additional VPN connections and load balance them.
- C. Configure a Google Cloud Dedicated Interconnect.
- D. Send the replicated transaction to Google Cloud Pub/Sub.
- E. Configure their replication to use UDP.
Answer: C
NEW QUESTION 91
You want to make a copy of a production Linux virtual machine in the US-Central region. You want to manage and replace the copy easily if there are changes on the production virtual machine. You will deploy the copy as a new instances in a different project in the US-East region. What steps must you take?
- A. Use the Linux dd and netcat command to copy and stream the root disk contents to a new virtual machine instance in the US-East region.
- B. Create a snapshot of the root disk and select the snapshot as the root disk when you create a new virtual machine instance in the US-East region.
- C. Create a snapshot of the root disk, create an image file in Google Cloud Storage from the snapshot, and create a new virtual machine instance in the US-East region using the image file for the root disk.
- D. Create an image file from the root disk with Linux dd command, create a new disk from the image file, and use it to create a new virtual machine instance in the US-East region
Answer: C
Explanation:
https://stackoverflow.com/questions/36441423/migrate-google-compute-engine-instance-to-a-different-region
NEW QUESTION 92
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: D
Explanation:
https://cloud.google.com/docs/enterprise/best-practices-for-enterprise-organizations
NEW QUESTION 93
Which of TerramEarth's legacy enterprise processes will experience significant change as a result of increased Google Cloud Platform adoption?
- A. Opex/capex allocation, LAN changes, capacity planning
- B. Data Center expansion, TCO calculations, utilization measurement
- C. Capacity planning, TCO calculations, opex/capex allocation
- D. Capacity planning, utilization measurement, data center expansion
Answer: C
NEW QUESTION 94
You are creating a solution to remove backup files older than 90 days from your backup Cloud Storage bucket. You want to optimize ongoing Cloud Storage spend.
What should you do?
- A. Schedule a cron script using gsutil ls -lr gs://backups/**to find and remove items older than 90 days
- B. Schedule a cron script using gsutil ls -l gs://backups/**to find and remove items older than
90 days and schedule it with cron - C. Write a lifecycle management rule in JSON and push it to the bucket with gsutil
- D. Write a lifecycle management rule in XML and push it to the bucket with gsutil
Answer: C
NEW QUESTION 95
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. Stream data into Google Cloud Datastore
- B. Put flat files into Google Cloud Storage
- C. Insert data into Google Cloud SQL
- D. Load data into Google BigQuery
Answer: D
Explanation:
Explanation/Reference:
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/
NEW QUESTION 96
For this question, refer to the Mountkirk Games case study.
Mountkirk Games wants to set up a continuous delivery pipeline. Their architecture includes many small services that they want to be able to update and roll back quickly.
Mountkirk Games has the following requirements:
* Services are deployed redundantly across multiple regions in the US and Europe.
* Only frontend services are exposed on the public internet.
* They can provide a single frontend IP for their fleet of services.
* Deployment artifacts are immutable.
Which set of products should they use?
- A. Google Cloud Functions, Google Cloud Pub/Sub, Google Cloud Deployment Manager
- B. Google Cloud Storage, Google Cloud Dataflow, Google Compute Engine
- C. Google Container Registry, Google Container Engine, Google HTTP(s) Load Balancer
- D. Google Cloud Storage, Google App Engine, Google Network Load Balancer
Answer: C
NEW QUESTION 97
Mountkirk Games wants to set up a real-time analytics platform for their new game. The new platform must
meet their technical requirements.
Which combination of Google technologies will meet all of their requirements?
- A. Cloud Pub/Sub, Compute Engine, Cloud Storage, and Cloud Dataproc
- B. Cloud Dataproc, Cloud Pub/Sub, Cloud SQL, and Cloud Dataflow
- C. Cloud SQL, Cloud Storage, Cloud Pub/Sub, and Cloud Dataflow
- D. Kubernetes Engine, Cloud Pub/Sub, and Cloud SQL
- E. Cloud Dataflow, Cloud Storage, Cloud Pub/Sub, and BigQuery
Answer: E
Explanation:
Explanation/Reference:
Explanation:
Ingest millions of streaming events per second from anywhere in the world with Cloud Pub/Sub, powered
by Google's unique, high-speed private network. Process the streams with Cloud Dataflow to ensure
reliable, exactly-once, low-latency data transformation. Stream the transformed data into BigQuery, the
cloud-native data warehousing service, for immediate analysis via SQL or popular visualization tools.
From scenario: They plan to deploy the game's backend on Google Compute Engine so they can capture
streaming metrics, run intensive analytics.
Requirements for Game Analytics Platform
1. Dynamically scale up or down based on game activity
2. Process incoming data on the fly directly from the game servers
3. Process data that arrives late because of slow mobile networks
4. Allow SQL queries to access at least 10 TB of historical data
5. Process files that are regularly uploaded by users' mobile devices
6. Use only fully managed services
References: https://cloud.google.com/solutions/big-data/stream-analytics/
Testlet 1
Company Overview
Mountkirk Games makes online, session-based, multiplayer games for mobile platforms. They build all of
their games using some server-side integration. Historically, they have used cloud providers to lease
physical servers.
Due to the unexpected popularity of some of their games, they have had problems scaling their global
audience, application servers, MySQL databases, and analytics tools.
Their current model is to write game statistics to files and send them through an ETL tool that loads them
into a centralized MySQL database for reporting.
Solution Concept
Mountkirk Games is building a new game, which they expect to be very popular. They plan to deploy the
game's backend on Google Compute Engine so they can capture streaming metrics, run intensive
analytics, and take advantage of its autoscaling server environment and integrate with a managed NoSQL
database.
Business Requirements
Increase to a global footprint.
Improve uptime - downtime is loss of players.
Increase efficiency of the cloud resources we use.
Reduce latency to all customers.
Technical Requirements
Requirements for Game Backend Platform
Dynamically scale up or down based on game activity.
Connect to a transactional database service to manage user profiles and game state.
Store game activity in a timeseries database service for future analysis.
As the system scales, ensure that data is not lost due to processing backlogs.
Run hardened Linux distro.
Requirements for Game Analytics Platform
Dynamically scale up or down based on game activity
Process incoming data on the fly directly from the game servers
Process data that arrives late because of slow mobile networks
Allow queries to access at least 10 TB of historical data
Process files that are regularly uploaded by users' mobile devices
Executive Statement
Our last successful game did not scale well with our previous cloud provider, resulting in lower user
adoption and affecting the game's reputation. Our investors want more key performance indicators (KPIs)
to evaluate the speed and stability of the game, as well as other metrics that provide deeper insight into
usage patterns so we can adapt the game to target users. Additionally, our current technology stack
cannot provide the scale we need, so we want to replace MySQL and move to an environment that
provides autoscaling, low latency load balancing, and frees us up from managing physical servers.
NEW QUESTION 98
You have developed an application using Cloud ML Engine that recognizes famous paintings from uploaded images. You want to test the application and allow specific people to upload images for the next 24 hours. Not all users have a Google Account. How should you have users upload images?
- A. Create an App Engine web application where users can upload images for the next 24 hours. Authenticate users via Cloud Identity.
- B. Have users upload the images to Cloud Storage using a signed URL that expires after 24 hours.
- C. Have users upload the images to Cloud Storage. Protect the bucket with a password that expires after 24 hours.
- D. Create an App Engine web application where users can upload images. Configure App Engine to disable the application after 24 hours. Authenticate users via Cloud Identity.
Answer: C
Explanation:
Reference:
https://cloud.google.com/blog/products/storage-data-transfer/uploading-images-directly-to-cloud-storage-by-using-signed-url
NEW QUESTION 99
All compute Engine instances in your VPC should be able to connect to an Active Directory server on specific ports. Any other traffic emerging from your instances is not allowed. You want to enforce this using VPC firewall rules.
How should you configure the firewall rules?
- A. Create an egress rule with priority 1000 to deny all traffic for all instances. Create another egress rule with priority 100 to allow the Active Directory traffic for all instances.
- B. Create an egress rule with priority 1000 to allow the Active Directory traffic. Rely on the implied deny egress rule with priority 100 to block all traffic for all instances.
- C. Create an egress rule with priority 100 to allow the Active Directory traffic. Rely on the implied deny egress rule with priority 1000 to block all traffic for all instances.
- D. Create an egress rule with priority 100 to deny all traffic for all instances. Create another egress rule with priority 1000 to allow the Active Directory traffic for all instances.
Answer: A
NEW QUESTION 100
Case Study: 6 - TerramEarth
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 the 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.
For this question, refer to the TerramEarth case study. Considering the technical requirements, how should you reduce the unplanned vehicle downtime in GCP?
- A. Use BigQuery as the data warehouse. Connect all vehicles to the network and upload gzip files to a Multi-Regional Cloud Storage bucket using gcloud. Use Google Data Studio for analysis and reporting.
- B. Use Cloud Dataproc Hive as the data warehouse. Upload gzip files to a MultiRegional Cloud Storage bucket. Upload this data into BigQuery using gcloud. Use Google data Studio for analysis and reporting.
- C. Use Cloud Dataproc Hive as the data warehouse. Directly stream data into prtitioned Hive tables.
Use Pig scripts to analyze data. - D. Use BigQuery as the data warehouse. Connect all vehicles to the network and stream data into BigQuery using Cloud Pub/Sub and Cloud Dataflow. Use Google Data Studio for analysis and reporting.
Answer: D
NEW QUESTION 101
You have an App Engine application that needs to be updated. You want to test the update with production traffic before replacing the current application version.
What should you do?
- A. Deploy the update as a new version in the App Engine application, and split traffic between the new and current versions.
- B. Deploy the update using the Instance Group Updater to create a partial rollout, which allows for canary testing.
- C. Deploy the update in a new VPC, and use Google's global HTTP load balancing to split traffic between the update and current applications.
- D. Deploy the update as a new App Engine application, and use Google's global HTTP load balancing to split traffic between the new and current applications.
Answer: A
Explanation:
https://cloud.google.com/appengine/docs/standard/python/splitting-traffic
NEW QUESTION 102
For this question, refer to the TerramEarth case study. A new architecture that writes all incoming data to
BigQuery has been introduced. You notice that the data is dirty, and want to ensure data quality on an
automated daily basis while managing cost.
What should you do?
- A. Create a SQL statement on the data in BigQuery, and save it as a view. Run the view daily, and save
the result to a new table. - B. Use Cloud Dataprep and configure the BigQuery tables as the source. Schedule a daily job to clean the
data. - C. Create a Cloud Function that reads data from BigQuery and cleans it. Trigger it. Trigger the Cloud
Function from a Compute Engine instance. - D. Set up a streaming Cloud Dataflow job, receiving data by the ingestion process. Clean the data in a
Cloud Dataflow pipeline.
Answer: B
NEW QUESTION 103
For this question, refer to the JencoMart case study.
JencoMart wants to move their User Profiles database to Google Cloud Platform. Which Google Database should they use?
- A. Google Cloud SQL
- B. Cloud Spanner
- C. Google BigQuery
- D. Google Cloud Datastore
Answer: D
Explanation:
Common workloads for Google Cloud Datastore:
User profiles
Product catalogs
Game state
References: https://cloud.google.com/storage-options/
https://cloud.google.com/datastore/docs/concepts/overview
Reference:
https://cloud.google.com/datastore/docs/concepts/overview
NEW QUESTION 104
Case Study: 2 - TerramEarth Case Study
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.
Company Background
TerramEarth formed in 1946, when several small, family owned companies combined to retool after World War II. The company cares about their employees and customers and considers them to be extended members of their family.
TerramEarth is proud of their ability to innovate on their core products and find new markets as their customers' needs change. For the past 20 years trends in the industry have been largely toward increasing productivity by using larger vehicles with a human operator.
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-based systems that reside in a data center. These systems gzip CSV files from the field and upload via FTP, transform and aggregate them, 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, without
increasing the cost of carrying surplus inventory
- Support the dealer network with more data on how their customers use
their equipment IP 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
CEO Statement
We have been successful in capitalizing on the trend toward larger vehicles to increase the productivity of our customers. Technological change is occurring rapidly and TerramEarth has taken advantage of connected devices technology to provide our customers with better services, such as our intelligent farming equipment. With this technology, we have been able to increase farmers' yields by 25%, by using past trends to adjust how our vehicles operate. These advances have led to the rapid growth of our agricultural product line, which we expect will generate 50% of our revenues by 2020.
CTO Statement
Our competitive advantage has always been in the manufacturing process with our ability to build better vehicles for tower 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. Unfortunately, our CEO doesn't take technology obsolescence seriously and he considers the many new companies in our industry to be niche players. My goals are to build our skills while addressing immediate market needs through incremental innovations.
For this question, refer to the TerramEarth case study.
Your development team has created a structured API to retrieve vehicle data.
They want to allow third parties to develop tools for dealerships that use this vehicle event data.
You want to support delegated authorization against this data. What should you do?
- A. Create secondary credentials for each dealer that can be given to the trusted third party.
- B. Restrict data access based on the source IP address of the partner systems.
- C. Build or leverage an OAuth-compatible access control system.
- D. Build SAML 2.0 SSO compatibility into your authentication system.
Answer: C
Explanation:
Delegate application authorization with OAuth2
Cloud Platform APIs support OAuth 2.0, and scopes provide granular authorization over the methods that are supported. Cloud Platform supports both service-account and user-account OAuth, also called three-legged OAuth.
References: https://cloud.google.com/docs/enterprise/best-practices-for-enterprise- organizations#delegate_application_authorization_with_oauth2
https://cloud.google.com/appengine/docs/flexible/go/authorizing-apps
NEW QUESTION 105
You want to optimize the performance of an accurate, real-time, weather-charting application. The data comes from 50,000 sensors sending 10 readings a second, in the format of a timestamp and sensor reading. Where should you store the data?
- A. Google Cloud SQL
- B. Google BigQuery
- C. Google Cloud Bigtable
- D. Google Cloud Storage
Answer: C
NEW QUESTION 106
Your company is using BigQuery as its enterprise data warehouse. Data is distributed over several Google Cloud projects. All queries on BigQuery need to be billed on a single project. You want to make sure that no query costs are incurred on the projects that contain the data. Users should be able to query the datasets, but not edit them.
How should you configure users' access roles?
- A. Add all users to a group. Grant the group the roles of BigQuery dataViewer on the billing project and BigQuery jobUser on the projects that contain the data.
- B. Add all users to a group. Grant the group the roles of BigQuery dataViewer on the billing project and BigQuery user on the projects that contain the data.
- C. Add all users to a group. Grant the group the roles of BigQuery jobUser on the billing project and BigQuery dataViewer on the projects that contain the data.
- D. Add all users to a group. Grant the group the role of BigQuery user on the billing project and BigQuery dataViewer on the projects that contain the data.
Answer: C
NEW QUESTION 107
For this question, refer to the TerramEarth case study. You are asked to design a new architecture for the ingestion of the data of the 200,000 vehicles that are connected to a cellular network. You want to follow Google-recommended practices.
Considering the technical requirements, which components should you use for the ingestion of the data?
- A. Compute Engine with project-wide SSH keys
- B. Cloud IoT Core with public/private key pairs
- C. Google Kubernetes Engine with an SSL Ingress
- D. Compute Engine with specific SSH keys
Answer: B
Explanation:
Explanation
https://cloud.google.com/solutions/iot-overview
NEW QUESTION 108
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. Use larger machine types for your Google Container Engine node pools.
- B. Remove dependencies from requirements.txt.
- C. Remove Python after running pip.
- D. Copy the source after the package dependencies (Python and pip) are installed.
- E. Use a slimmed-down base image like Alpine linux.
Answer: D,E
Explanation:
Explanation
The speed of deployment can be changed by limiting the size of the uploaded app, limiting the complexity of the build necessary in the Dockerfile, if present, and by ensuring a fast and reliable internet connection.
Note: Alpine Linux is built around musl libc and busybox. This makes it smaller and more resource efficient than traditional GNU/Linux distributions. A container requires no more than 8 MB and a minimal installation to disk requires around 130 MB of storage. Not only do you get a fully-fledged Linux environment but a large selection of packages from the repository.
References: https://groups.google.com/forum/#!topic/google-appengine/hZMEkmmObDU
https://www.alpinelinux.org/about/
NEW QUESTION 109
You want to enable your running Google Kubernetes Engine cluster to scale as demand for your application changes.
What should you do?
- A. Add a tag to the instances in the cluster with the following command:gcloud compute instances add-tagsINSTANCE - -tags enable-autoscaling max-nodes-10
- B. Update the existing Kubernetes Engine cluster with the following command:gcloud alpha container clustersupdate mycluster - -enable-autoscaling - -min-nodes=1 - -max-nodes=10
- C. Add additional nodes to your Kubernetes Engine cluster using the following command:gcloud container clusters resizeCLUSTER_Name - -size 10
- D. Create a new Kubernetes Engine cluster with the following command:gcloud alpha container clusterscreate mycluster - -enable-autoscaling - -min-nodes=1 - -max-nodes=10and redeploy your application
Answer: B
Explanation:
Reference:
https://cloud.google.com/kubernetes-engine/docs/concepts/cluster-autoscaler To enable autoscaling for an existing node pool, run the following command:
gcloud container clusters update [CLUSTER_NAME] --enable-autoscaling \ --min-nodes 1 --max-nodes 10 --zone [COMPUTE_ZONE] --node-pool default-pool
NEW QUESTION 110
......
Managing & Provisioning Solution Infrastructures
- Configure individual storage systems: the areas of focus should include data storage allocation; access management and security; data processing and compute provisioning; data lifecycle management and data retention; network configuration for the data latency and transfer;
- Configure compute systems: you should understand system provisioning; compute volatility configuration; container orchestration using Kubernetes; technology configuration for infrastructure provisioning; network configuration for the compute nodes.
- Configure network topologies: the examinees should have the ability to extend to hybrid and on-premises networking and multi-Cloud environment that may entail GCP to GCP communication. It also requires their understanding of data protection and security;
Ensuring Operations and Solution Reliability
- Assist with solutions support within the operation;
- Evaluate quality control measures.
- Monitor, log, profile, and alert solutions;
- Deploy and release management;
Section #2. Handling the solution’s infrastructure
The key knowledge area covered in this domain includes the development of an on-premises environment, designing a setup with multiple clouds, security concepts, and storage space allotment for diverse data.
Professional-Cloud-Architect Exam Dumps, Professional-Cloud-Architect Practice Test Questions: https://www.exams4sures.com/Google/Professional-Cloud-Architect-practice-exam-dumps.html
Free Professional-Cloud-Architect Study Guides Exam Questions & Answer: https://drive.google.com/open?id=1a18SgvSvKJBcCuGkcHWaZsS0ehNE02uJ