Latest [Sep 18, 2021] Professional-Cloud-Architect Exam with Accurate Google Certified Professional - Cloud Architect (GCP) PDF Questions
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NEW QUESTION 30
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 31
For this question, refer to the Helicopter Racing League (HRL) case study. A recent finance audit of cloud infrastructure noted an exceptionally high number of Compute Engine instances are allocated to do video encoding and transcoding. You suspect that these Virtual Machines are zombie machines that were not deleted after their workloads completed. You need to quickly get a list of which VM instances are idle. What should you do?
- A. From the Google Console, identify which Compute Engine instances in the managed instance groups are no longer responding to health check probes.
- B. Use the gcloud recommender command to list the idle virtual machine instances.
- C. Log into each Compute Engine instance and collect disk, CPU, memory, and network usage statistics for analysis.
- D. Use the gcloud compute instances list to list the virtual machine instances that have the idle: true label set.
Answer: B
Explanation:
Reference:
NEW QUESTION 32
You have deployed several instances on Compute Engine. As a security requirement, instances cannot have a public IP address. There is no VPN connection between Google Cloud and your office, and you need to connect via SSH into a specific machine without violating the security requirements. What should you do?
- A. Create a bastion host in the network to SSH into the bastion host from your office location. From the bastion host, SSH into the desired instance.
- B. Configure Identity-Aware Proxy (IAP) for the instance and ensure that you have the role of IAP-secured Tunnel User. Use the gcloud command line tool to ssh into the instance.
- C. Configure Cloud NAT on the subnet where the instance is hosted. Create an SSH connection to the Cloud NAT IP address to reach the instance.
- D. Add all instances to an unmanaged instance group. Configure TCP Proxy Load Balancing with the instance group as a backend. Connect to the instance using the TCP Proxy IP.
Answer: A
Explanation:
Reference: https://cloud.google.com/solutions/connecting-securely
NEW QUESTION 33
The application reliability team at your company has added a debug feature to their backend service to send all server events to Google Cloud Storage for eventual analysis. The event records are at least 50 KB and at most
15 MB and are expected to peak at 3,000 events per second. You want to minimize data loss.
Which process should you implement?
- A. * Append metadata to file body.
* Compress individual files.
* Name files with serverName-Timestamp.
* Create a new bucket if bucket is older than 1 hour and save individual files to the new bucket.
Otherwise, save files to existing bucket - B. * Compress individual files.
* Name files with serverName-EventSequence.
* Save files to one bucket
* Set custom metadata headers for each object after saving. - C. * Batch every 10,000 events with a single manifest file for metadata.
* Compress event files and manifest file into a single archive file.
* Name files using serverName-EventSequence.
* Create a new bucket if bucket is older than 1 day and save the single archive file to the new bucket.
Otherwise, save the single archive file to existing bucket. - D. * Append metadata to file body.
* Compress individual files.
* Name files with a random prefix pattern.
* Save files to one bucket
Answer: A
NEW QUESTION 34
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. Google Kubernetes Engine with an SSL Ingress
- C. Cloud IoT Core with public/private key pairs
- D. Compute Engine with specific SSH keys
Answer: C
Explanation:
Explanation
https://cloud.google.com/solutions/iot-overview
NEW QUESTION 35
You are using Cloud CDN to deliver static HTTP(S) website content hosted on a Compute Engine instance
group. You want to improve the cache hit ratio.
What should you do?
- A. Replicate the static content in a Cloud Storage bucket. Point CloudCDN toward a load balancer on that
bucket. - B. Shorten the expiration time of the cached objects.
- C. Customize the cache keys to omit the protocol from the key.
- D. Make sure the HTTP(S) header "Cache-Region" points to the closest region of your users.
Answer: C
Explanation:
Explanation/Reference:
Reference https://cloud.google.com/cdn/docs/best-
practices#using_custom_cache_keys_to_improve_cache_hit_ratio
NEW QUESTION 36
For this question, refer to the TerramEarth case study.
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. 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.
- B. 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. - C. 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.
- D. 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.
Answer: C
NEW QUESTION 37
During a high traffic portion of the day, one of your relational databases crashes, but the replica is never promoted to a master. You want to avoid this in the future. What should you do?
- A. Choose larger instances for your database.
- B. Implement routinely scheduled failovers of your databases.
- C. Create snapshots of your database more regularly.
- D. Use a different database.
Answer: B
Explanation:
Explanation
https://cloud.google.com/solutions/dr-scenarios-planning-guide
NEW QUESTION 38
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 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.
- B. 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
- 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: A
Explanation:
Running Shutdown Scripts: Create and run shutdown scripts that execute commands right before an instance is terminated or restarted, on a best-effort basis. This is useful if you rely on automated scripts to start up and shut down instances, allowing instances time to clean up or perform tasks, such as exporting logs, or syncing with other systems.
https://cloud.google.com/compute/docs/shutdownscript
To setup Shutdown Scripts, go to GCP console and follow the steps:
Compute Engine -> VM instance -> Create Instance -> (Expand) Management, disks, networking, SSH keys Enter the key "shutdown-script" and proper value
NEW QUESTION 39
You want to enable your running Google Kubernetes Engine cluster to scale as demand for your application changes.
What should you do?
- A. 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
- 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 a tag to the instances in the cluster with the following command:gcloud compute instances add-tagsINSTANCE - -tags enable-autoscaling max-nodes-10
- D. Add additional nodes to your Kubernetes Engine cluster using the following command:gcloud container clusters resizeCLUSTER_Name - -size 10
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 40
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 Storage
- B. Google Cloud SQL
- C. Google Cloud Bigtable
- D. Google BigQuery
Answer: C
Explanation:
Google Cloud Bigtable is a scalable, fully-managed NoSQL wide-column database that is suitable for both real- time access and analytics workloads.
Good for:
* Low-latency read/write access
* High-throughput analytics
* Native time series support
Common workloads:
* IoT, finance, adtech
* Personalization, recommendations
* Monitoring
* Geospatial datasets
* Graphs
References: https://cloud.google.com/storage-options/
NEW QUESTION 41
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. Have users upload the images to Cloud Storage using a signed URL that expires after 24 hours.
- B. 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.
- C. Create an App Engine web application where users can upload images for the next 24 hours.
Authenticate users via Cloud Identity. - D. Have users upload the images to Cloud Storage. Protect the bucket with a password that expires after 24 hours.
Answer: A
Explanation:
https://cloud.google.com/storage/docs/access-control/signed-urls
NEW QUESTION 42
You have been asked to select the storage system for the click-data of your company's large portfolio of websites. This data is streamed in from a custom website analytics package at a typical rate of 6,000 clicks per minute, with bursts of up to 8,500 clicks per second. It must been stored for future analysis by your data science and user experience teams. Which storage infrastructure should you choose?
- A. Google Cloud SQL
- B. Google cloud Datastore
- C. Google Cloud Storage
- D. Google Cloud Bigtable
Answer: C
NEW QUESTION 43
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.
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 44
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. TerramEarth has decided to store data files in Cloud Storage. You need to configure Cloud Storage lifecycle rule to store 1 year of data and minimize file storage cost.
Which two actions should you take?
- A. Create a Cloud Storage lifecycle rule with Age: "30", Storage Class: "Standard", and Action: "Set to Coldline", and create a second GCS life-cycle rule with Age: "365", Storage Class: "Nearline", and Action: "Delete".
- B. Create a Cloud Storage lifecycle rule with Age: "90", Storage Class: "Standard", and Action: "Set to Nearline", and create a second GCS life-cycle rule with Age: "91", Storage Class: "Nearline", and Action: "Set to Coldline".
- C. Create a Cloud Storage lifecycle rule with Age: "30", Storage Class: "Standard", and Action: "Set to Coldline", and create a second GCS life-cycle rule with Age: "365", Storage Class: "Coldline", and Action: "Delete".
- D. Create a Cloud Storage lifecycle rule with Age: "30", Storage Class: "Coldline", and Action: "Set to Nearline", and create a second GCS life-cycle rule with Age: "91", Storage Class: "Coldline", and Action: "Set to Nearline".
Answer: C
NEW QUESTION 45
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