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How to Prepare For Google Professional Cloud Architect Exam
Preparation Guide for Google Professional Cloud Architect Exam
Introduction
Google has designed a track for IT professionals to endorse as a cloud architect on the GCP platform. This accreditation program gives Google cloud professionals a way to endorse their skills. The evaluation relies on a meticulous exam using industry standard methodology to conclude whether or not a aspirant meets GoogleâÂÂs proficiency standards.
According to Google, a Google Certified Professional Cloud Architect facilitate organizations to influence Google Cloud technologies. With a thorough understanding of cloud architecture and Google Cloud Platform, this individual can design, develop, and manage robust, secure, scalable, highly available, and dynamic solutions to drive business objectives.
Certification is evidence of your skills, expertise in those areas in which you like to work. If candidate wants to work on Google Professional Cloud Architect and prove his knowledge, Certification offered by Google. This Google Professional Cloud Architect Certification helps a candidate to validates his skills in Google Professional Cloud Architect Technology.
In this guide, we will cover the Google Professional Cloud Architect Exam, Google Professional Cloud Architect Certified Professionals salary and all aspects of the Google Professional Cloud Architect Certification.
Getting Ready for the Exam
Following training courses is a great way to be exam-ready. Enrolling in the programs like Architecting with Google Cloud: Design and Process, Google Cloud Fundamentals: Core Infrastructure, and Architecting with Google Compute Engine will help you gain mastery over the test’s content.
NEW QUESTION 27
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. Remove dependencies from requirements.txt.
- B. Copy the source after the package dependencies (Python and pip) are installed.
- C. Remove Python after running pip.
- D. Use larger machine types for your Google Container Engine node pools.
- E. Use a slimmed-down base image like Alpine linux.
Answer: B,E
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 28
Dress4win has end to end tests covering 100% of their endpoints.
They want to ensure that the move of cloud does not introduce any new bugs.
Which additional testing methods should the developers employ to prevent an outage?
- A. They should enable google stack driver debugger on the application code to show errors in the code
- B. They should add canary tests so developers can measure how much of an impact the new release causes to latency
- C. They should add additional unit tests and production scale load tests on their cloud staging environment.
- D. They should run the end to end tests in the cloud staging environment to determine if the code is working as intended.
Answer: C
NEW QUESTION 29
Your operations team has asked you to help diagnose a performance issue in a production application that runs on Compute Engine. The application is dropping requests that reach it when under heavy load. The process list for affected instances shows a single application process that is consuming all available CPU, and autoscaling has reached the upper limit of instances. There is no abnormal load on any other related systems, including the database. You want to allow production traffic to be served again as quickly as possible. Which action should you recommend?
- A. Restart the affected instances on a staggered schedule.
- B. Increase the maximum number of instances in the autoscaling group.
- C. SSH to each instance and restart the application process.
- D. Change the autoscaling metric to agent.googleapis.com/memory/percent_used.
Answer: B
NEW QUESTION 30
To reduce costs, the Director of Engineering has required all developers to move their development infrastructure resources from on-premises virtual machines (VMs) to Google Cloud Platform. These resources go through multiple start/stop events during the day and require state to persist. You have been asked to design the process of running a development environment in Google Cloud while providing cost visibility to the finance department. Which two steps should you take? Choose 2 answers
- A. Store all state into local SSD, snapshot the persistent disks, and terminate the VM.
- B. Use Google BigQuery billing export and labels to associate cost to groups.
- C. Use the -auto-delete flag on all persistent disks and terminate the VM.
- D. Store all state in Google Cloud Storage, snapshot the persistent disks, and terminate the VM.
- E. Apply VM CPU utilization label and include it in the BigQuery billing export.
- F. Use the --no-auto-delete flag on all persistent disks and stop the VM.
Answer: B,F
Explanation:
https://cloud.google.com/billing/docs/how-to/export-data-bigquery
NEW QUESTION 31
The current Dress4win system architecture has high latency to some customers because it is located in one data center.
As of a future evaluation and optimizing for performance in the cloud, Dresss4win wants to distribute its system architecture to multiple locations when Google cloud platform.
Which approach should they use?
- A. Use regional managed instance groups and a global load balancer to increase performance because the regional managed instance group can grow instances in each region separately based on traffic.
- B. Use a global load balancer with a set of virtual machines that forward the requests to a closer group of virtual machines as part of a separate managed instance groups.
- C. Use regional managed instance groups and a global load balancer to increase reliability by providing automatic failover between zones in different regions.
- D. Use a global load balancer with a set of virtual machines that forward the requests to a closer group of virtual machines managed by your operations team.
Answer: B
Explanation:
Explanation/Reference:
Dress4Win, B
Testlet 1
Company Overview
Dress4win is a web-based company that helps their users organize and manage their personal wardrobe using a webapp 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. The 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 moving their development and test environments. They are also 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. All servers run Ubuntu LTS v16.04.
Databases:
* MySQL. 1 server for user data, inventory, static data:
- MySQL 5.8
- 8 core CPUs
- 128 GB of RAM
- 2x 5 TB HDD (RAID 1)
* Redis 3 server cluster for metadata, social graph, caching. Each server is:
- Redis 3.2
- 4 core CPUs
- 32GB of RAM
Compute:
* 40 Web Application servers providing micro-services based APIs and static content.
- Tomcat - Java
- Nginx
- 4 core CPUs
- 32 GB of RAM
* 20 Apache Hadoop/Spark servers:
- Data analysis
- Real-time trending calculations
- 8 core CPUS
- 128 GB of RAM
- 4x 5 TB HDD (RAID 1)
* 3 RabbitMQ servers for messaging, social notifications, and events:
- 8 core CPUs
- 32GB of RAM
* Miscellaneous servers:
- Jenkins, monitoring, bastion hosts, security scanners
- 8 core CPUs
- 32GB of RAM
Storage appliances:
* iSCSI for VM hosts
* Fiber channel SAN - MySQL databases
- 1 PB total storage; 400 TB available
* NAS - image storage, logs, backups
- 100 TB total storage; 35 TB available
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.
Technical Requirements
* Easily create non-production environment in the cloud.
* Implement an automation framework for provisioning resources in cloud.
* Implement a continuous deployment process for deploying applications to the on-premises datacenter or cloud.
* Support failover of the production environment to cloud during an emergency.
* Encrypt data on the wire and at rest.
* Support multiple private connections between the production data center and cloud environment.
Executive Statement
Our investors are concerned about our ability to scale and contain costs with our current infrastructure. They are also concerned that a competitor could use a public cloud platform to offset their up-front investment and free them to focus on developing better features. Our traffic patterns are highest in the mornings and weekend evenings; during other times, 80% of our capacity is sitting idle.
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 for a public cloud strategy achieves a cost reduction between 30% and 50% over our current model.
NEW QUESTION 32
For this question, refer to the TerramEarth case study.
TerramEarth's 20 million vehicles are scattered around the world. Based on the vehicle's location its telemetry data is stored in a Google Cloud Storage (GCS) regional bucket (US. Europe, or Asia). The CTO has asked you to run a report on the raw telemetry data to determine why vehicles are breaking down after 100 K miles. You want to run this job on all the dat a. What is the most cost-effective way to run this job?
- A. Move all the data into 1 zone, then launch a Cloud Dataproc cluster to run the job.
- B. Launch a cluster in each region to preprocess and compress the raw data, then move the data into a multi region bucket and use a Dataproc cluster to finish the job.
- C. Move all the data into 1 region, then launch a Google Cloud Dataproc cluster to run the job.
- D. Launch a cluster in each region to preprocess and compress the raw data, then move the data into a region bucket and use a Cloud Dataproc cluster to finish the jo
Answer: D
Explanation:
Storageguarantees 2 replicates which are geo diverse (100 miles apart) which can get better remote latency and availability.
More importantly, is that multiregional heavily leverages Edge caching and CDNs to provide the content to the end users.
All this redundancy and caching means that Multiregional comes with overhead to sync and ensure consistency between geo-diverse areas. As such, it's much better for write-once-read-many scenarios. This means frequently accessed (e.g. "hot" objects) around the world, such as website content, streaming videos, gaming or mobile applications.
References: https://medium.com/google-cloud/google-cloud-storage-what-bucket-class-for-the-best-performance-5c847ac8f9f2
NEW QUESTION 33
Your architecture calls for the centralized collection of all admin activity and VM system logs within your project.
How should you collect these logs from both VMs and services?
- A. Install the Stackdriver Logging agent on a single compute instance and let it collect all audit and access logs for your environment.
- B. All admin and VM system logs are automatically collected by Stackdriver.
- C. Stackdriver automatically collects admin activity logs for most services. The Stackdriver Logging agent must be installed on each instance to collect system logs.
- D. Launch a custom syslogd compute instance and configure your GCP project and VMs to forward all logs to it.
Answer: C
Explanation:
https://cloud.google.com/logging/docs/agent/
NEW QUESTION 34
Your organization wants to control IAM policies for different departments independently, but centrally.
Which approach should you take?
- A. A single Organization with Folder for each department
- B. Multiple Organizations, one for each department
- C. Multiple Organizations with multiple Folders
- D. A single Organization with multiple projects, each with a central owner
Answer: A
Explanation:
Folders are nodes in the Cloud Platform Resource Hierarchy. A folder can contain projects, other folders, or a combination of both. You can use folders to group projects under an organization in a hierarchy. For example, your organization might contain multiple departments, each with its own set of GCP resources. Folders allow you to group these resources on a per-department basis. Folders are used to group resources that share common IAM policies. While a folder can contain multiple folders or resources, a given folder or resource can have exactly one parent.
References: https://cloud.google.com/resource-manager/docs/creating-managing-folders
NEW QUESTION 35
For this question, refer to the TerramEarth case study.
TerramEarth's CTO wants to use the raw data from connected vehicles to help identify approximately when a vehicle in the development team to focus their failure. You want to allow analysts to centrally query the vehicle data. Which architecture should you recommend?
- A. Option D
- B. Option B
- C. Option A
- D. Option C
Answer: C
Explanation:
https://cloud.google.com/solutions/iot/
https://cloud.google.com/solutions/designing-connected-vehicle-platform
https://cloud.google.com/solutions/designing-connected-vehicle-platform#data_ingestion
http://www.eweek.com/big-data-and-analytics/google-touts-value-of-cloud-iot-core-for-analyzing- connected-car-data
https://cloud.google.com/solutions/iot/
NEW QUESTION 36
A production database virtual machine on Google Compute Engine has an ext4-formatted persistent disk for data files The database is about to run out of storage space How can you remediate the problem with the least amount of downtime?
- A. In the Cloud Platform Console, increase the size of the persistent disk and verify the new space is ready to use with the fdisk command in Linux.
- B. Shut down the virtual machine, use the Cloud Platform Console to increase the persistent disk size, then restart the virtual machine.
- C. In the Cloud Platform Console, create a snapshot of the persistent disk, restore the snapshot to a new larger disk, unmount the old disk, mount the new disk, and restart the database service.
- D. In the Cloud Platform Console, create a new persistent disk attached to the virtual machine, format and mount it, and configure the database service to move the files to the new disk.
- E. In the Cloud Platform Console, increase the size of the persistent disk and use the resize2fs command in Linux.
Answer: E
NEW QUESTION 37
Your customer wants to capture multiple GBs of aggregate real-time key performance indicators (KPIs) from their game servers running on Google Cloud Platform and monitor the KPIs with low latency. How should they capture the KPIs?
- A. Insert the KPIs into Cloud Datastore entities, and run ad hoc analysis and visualizations of them in Cloud Datalab.
- B. Output custom metrics to Stackdriver from the game servers, and create a Dashboard in Stackdriver Monitoring Console to view them.
- C. Schedule BigQuery load jobs to ingest analytics files uploaded to Cloud Storage every ten minutes, and visualize the results in Google Data Studio.
- D. Store time-series data from the game servers in Google Bigtable, and view it using Google Data Studio.
Answer: D
Explanation:
Explanation/Reference: https://cloud.google.com/solutions/data-lifecycle-cloud-platform
NEW QUESTION 38
TerramEarth has equipped all connected trucks with servers and sensors to collect telemetry data. Next
year they want to use the data to train machine learning models. They want to store this data in the cloud
while reducing costs.
What should they do?
- A. Push the telemetry data in real-time to a streaming dataflow job that compresses the data, and store it
in Cloud Bigtable - B. Push the telemetry data in real-time to a streaming dataflow job that compresses the data, and store it
in Google BigQuery - C. Have the vehicle's computer compress the data in hourly snapshots, and store it in a GCS Coldline
bucket - D. Have the vehicle's computer compress the data in hourly snapshots, and store it in a Google Cloud
Storage (GCS) Nearline bucket
Answer: C
Explanation:
Explanation/Reference:
Explanation:
Storage is the best choice for data that you plan to access at most once a year, due to its slightly lower
availability, 90-day minimum storage duration, costs for data access, and higher per-operation costs. For
example:
Cold Data Storage - Infrequently accessed data, such as data stored for legal or regulatory reasons, can
be stored at low cost as Coldline Storage, and be available when you need it.
Disaster recovery - In the event of a disaster recovery event, recovery time is key. Cloud Storage provides
low latency access to data stored as Coldline Storage.
References: https://cloud.google.com/storage/docs/storage-classes
NEW QUESTION 39
For this question, refer to the Mountkirk Games case study.
Mountkirk Games' gaming servers are not automatically scaling properly. Last month, they rolled out a new feature, which suddenly became very popular. A record number of users are trying to use the service, but many of them are getting 503 errors and very slow response times. What should they investigate first?
- A. Verify that the new feature code did not introduce any performance bugs.
- B. Verify that the load-testing team is not running their tool against production.
- C. Verify that the project quota hasn't been exceeded.
- D. Verify that the database is online.
Answer: D
Explanation:
503 is service unavailable error.
NEW QUESTION 40
TerramEarth's 20 million vehicles are scattered around the world. Based on the vehicle's location, its telemetry data is stored in a Google Cloud Storage (GCS) regional bucket (US, Europe, or Asia). The CTO has asked you to run a report on the raw telemetry data to determine why vehicles are breaking down after 100 K miles.
You want to run this job on all the data.
What is the most cost-effective way to run this job?
- A. Launch a cluster in each region to preprocess and compress the raw data, then move the data into a region bucket and use a Cloud Dataproc cluster to finish the job
- B. Move all the data into 1 zone, then launch a Cloud Dataproc cluster to run the job
- C. Launch a cluster in each region to preprocess and compress the raw data, then move the data into a multi- region bucket and use a Dataproc cluster to finish the job
- D. Move all the data into 1 region, then launch a Google Cloud Dataproc cluster to run the job
Answer: C
Explanation:
Storageguarantees 2 replicates which are geo diverse (100 miles apart) which can get better remote latency and availability.
More importantly, is that multiregional heavily leverages Edge caching and CDNs to provide the content to the end users.
All this redundancy and caching means that Multiregional comes with overhead to sync and ensure consistency between geo-diverse areas. As such, it's much better for write-once-read-many scenarios. This means frequently accessed (e.g. "hot" objects) around the world, such as website content, streaming videos, gaming or mobile applications.
Reference: https://medium.com/google-cloud/google-cloud-storage-what-bucket-class-for-the-best- performance-5c847ac8f9f2
NEW QUESTION 41
The Dress4Win security team has disabled external SSH access into production virtual machines (VMs) on
Google Cloud Platform (GCP).
The operations team needs to remotely manage the VMs, build and push Docker containers, and manage
Google Cloud Storage objects.
What can they do?
- A. Have the development team build an API service that allows the operations team to execute specific
remote procedure calls to accomplish their tasks. - B. Develop a new access request process that grants temporary SSH access to cloud VMs when an
operations engineer needs to perform a task. - C. Grant the operations engineer access to use Google Cloud Shell.
- D. Configure a VPN connection to GCP to allow SSH access to the cloud VMs.
Answer: D
NEW QUESTION 42
Your marketing department wants to send out a promotional email campaign. The development team wants to minimize direct operation management. They project a wide range of possible customer responses, from 100 to 500,000 click-throughs per day. The link leads to a simple website that explains the promotion and collects user information and preferences. Which infrastructure should you recommend? (CHOOSE TWO)
- A. Use a Google Container Engine cluster to serve the website and store data to persistent disk.
- B. Use Google App Engine to serve the website and Google Cloud Datastore to store user data.
- C. Use a managed instance group to serve the website and Google Cloud Bigtable to store user data.
- D. Use a single compute Engine virtual machine (VM) to host a web server, backed by Google Cloud SQL.
Answer: B,C
Explanation:
Reference:
References: https://cloud.google.com/storage-options/
NEW QUESTION 43
Your web application uses Google Kubernetes Engine to manage several workloads. One workload
requires a consistent set of hostnames even after pod scaling and relaunches.
Which feature of Kubernetes should you use to accomplish this?
- A. Container environment variables
- B. Persistent Volumes
- C. StatefulSets
- D. Role-based access control
Answer: B
NEW QUESTION 44
Your company operates nationally and plans to use GCP for multiple batch workloads, including some that are not time-critical. You also need to use GCP services that are HIPAA-certified and manage service costs.
How should you design to meet Google best practices?
- A. Provision standard VMs to the same region to reduce cost. Disable and then discontinue use of all GCP services and APIs that are not HIPAA-compliant.
- B. Provision standard VMs in the same region to reduce cost. Discontinue use of all GCP services and APIs that are not HIPAA-compliant.
- C. Provisioning preemptible VMs to reduce cost. Discontinue use of all GCP services and APIs that are not HIPAA-compliant.
- D. Provisioning preemptible VMs to reduce cost. Disable and then discontinue use of all GCP and APIs that are not HIPAA-compliant.
Answer: D
Explanation:
https://cloud.google.com/security/compliance/hipaa/
NEW QUESTION 45
Your company has successfully migrated to the cloud and wants to analyze their data stream to optimize operations. They do not have any existing code for this analysis, so they are exploring all their options.
These options include a mix of batch and stream processing, as they are running some hourly jobs and live-processing some data as it comes in.
Which technology should they use for this?
- A. Google Compute Engine with Google BigQuery
- B. Google Container Engine with Bigtable
- C. Google Cloud Dataproc
- D. Google Cloud Dataflow
Answer: D
Explanation:
Explanation/Reference:
Explanation:
Cloud Dataflow is a fully-managed service for transforming and enriching data in stream (real time) and batch (historical) modes with equal reliability and expressiveness -- no more complex workarounds or compromises needed.
References: https://cloud.google.com/dataflow/
NEW QUESTION 46
For this question, refer to the TerramEarth case study. You need to implement a reliable, scalable GCP solution for the data warehouse for your company, TerramEarth.
Considering the TerramEarth business and technical requirements, what should you do?
- A. Replace the existing data warehouse with a Compute Engine instance with 96 CPUs. Add an additional Compute Engine preemptible instance with 32 CPUs.
- B. Replace the existing data warehouse with BigQuery. Use table partitioning.
- C. Replace the existing data warehouse with a Compute Engine instance with 96 CPUs.
- D. Replace the existing data warehouse with BigQuery. Use federated data sources.
Answer: B
NEW QUESTION 47
......
Exam Details
The Google Professional Cloud Architect test is timed. The exact number of questions has not been revealed by the vendor. But, it is known that candidates will be given 2 hours to complete the exam, and the questions will be based on multiple-choice and multiple select types. Available languages are English and Japanese, and one should pay $200 as a registration fee. Note that there can be an additional tax.
When it comes to the exam delivery formats, there are two choices for an aspirant. They can either sit for it in a testing center near them or can avail of the online proctoring facility. In both methods, the content and pattern of the test will be the same.
For this exam, a beta version is offered as well. Anyone who wants to save 40% on the total fee or willing to recertify can take it. The cost in this case is $120, the length increases to 3 hours, and some questions may be provided in the form of case studies. Also, pay attention to the fact that the results will be known after 6-8 weeks only.
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