[2025] Use Valid New Professional-Cloud-Architect Test Notes & Professional-Cloud-Architect Valid Exam Guide
Professional-Cloud-Architect Actual Questions Answers PDF 100% Cover Real Exam Questions
Exam Domains Overview
The entire syllabus is based on six domains and each tries to educate the learner about various Google Cloud technologies. They are disclosed below in detail:
Section #1. Designing and strategy-making for the Cloud Solution Architecture
Designing a Google Cloud solution as per business and technical needs, handling the cost optimization, data movement, observability, and compliance are some of the most talked-about topics under this module.
The applicants should also demonstrate their expertise regarding the concepts like architecting the storage, network, and compute solutions or resources, multi-cloud or on-premises integration, and fulfilling & monitoring the compute needs of the platform products, picking-up right data processing and related technologies.
NEW QUESTION # 165
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. All admin and VM system logs are automatically collected by Stackdriver.
- B. Stackdriver automatically collects admin activity logs for most services. The Stackdriver Logging agent must be installed on each instance to collect system logs.
- C. Install the Stackdriver Logging agent on a single compute instance and let it collect all audit and access logs for your environment.
- D. Launch a custom syslogd compute instance and configure your GCP project and VMs to forward all logs to it.
Answer: C
Explanation:
Explanation/Reference: https://cloud.google.com/logging/docs/agent/
NEW QUESTION # 166
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 Google BigQuery
- B. Have the vehicle's computer compress the data in hourly snapshots, and store it in a GCS Coldline bucket
- C. Have the vehicle's computer compress the data in hourly snapshots, and store it in a Google Cloud Storage (GCS) Nearline bucket
- D. Push the telemetry data in real-time to a streaming dataflow job that compresses the data, and store it in Cloud Bigtable
Answer: B
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 # 167
You are developing an application using different microservices that should remain internal to the cluster. You want to be able to configure each microservice with a specific number of replicas. You also want to be able to address a specific microservice from any other microservice in a uniform way, regardless of the number of replicas the microservice scales to. You need to implement this solution on Google Kubernetes Engine. What should you do?
- A. Deploy each microservice as a Pod. Expose the Pod in the cluster using a Service, and use the Service DNS name to address the microservice from other microservices within the cluster.
- B. Deploy each microservice as a Deployment. Expose the Deployment in the cluster using an Ingress, and use the Ingress IP address to address the Deployment from other microservices within the cluster.
- C. Deploy each microservice as a Pod. Expose the Pod in the cluster using an Ingress, and use the Ingress IP address name to address the Pod from other microservices within the cluster.
- D. Deploy each microservice as a Deployment. Expose the Deployment in the cluster using a Service, and use the Service DNS name to address it from other microservices within the cluster.
Answer: D
Explanation:
https://kubernetes.io/docs/concepts/services-networking/ingress/
Topic 1, EHR Health Care
Company Overview
EHR Healthcare is a leading provider of electronic health record software to the medical industry. EHR Healthcare provides their software as a service to multi-national medical offices, hospitals, and insurance providers.
Solution concept
Due to rapid changes in the healthcare and insurance industry, EHR Healthcare's business has been growing exponentially year over year. They need to be able to scale their environment, adapt their disaster recovery plan, and roll out new continuous deployment capabilities to update their software at a fast pace. Google Cloud has been chosen to replace their current colocation facilities.
Existing technical environment
EHR's software is currently hosted in multiple colocation facilities. The lease on one of the data centers is about to expire.
Customer-facing applications are web-based, and many have recently been containerized to run on a group of Kubernetes clusters. Data is stored in a mixture of relational and NoSQL databases (MySQL, MS SQL Server, Redis, and MongoDB).
EHR is hosting several legacy file- and API-based integrations with insurance providers on-premises. These systems are scheduled to be replaced over the next several years. There is no plan to upgrade or move these systems at the current time.
Users are managed via Microsoft Active Directory. Monitoring is currently being done via various open source tools. Alerts are sent via email and are often ignored.
Business Requirements
* On-board new insurance providers as quickly as possible.
* Provide a minimum 99.9% availability for all customer-facing systems.
* Provide centralized visibility and proactive action on system performance and usage.
* Increase ability to provide insights into healthcare trends.
* Reduce latency to all customers.
* Maintain regulatory compliance.
* Decrease infrastructure administration costs.
* Make predictions and generate reports on industry trends based on provider data.
Technical Requirements
* Maintain legacy interfaces to insurance providers with connectivity to both on-premises systems and cloud providers.
* Provide a consistent way to manage customer-facing applications that are container-based.
* Provide a secure and high-performance connection between on-premises systems and Google Cloud.
* Provide consistent logging, log retention, monitoring, and alerting capabilities.
* Maintain and manage multiple container-based environments.
* Dynamically scale and provision new environments.
* Create interfaces to ingest and process data from new providers.
Executive statement
Our on-premises strategy has worked for years but has required a major investment of time and money in training our team on distinctly different systems, managing similar but separate environments, and responding to outages. Many of these outages have been a result of misconfigured systems, inadequate capacity to manage spikes in traffic, and inconsistent monitoring practices. We want to use Google Cloud to leverage a scalable, resilient platform that can span multiple environments seamlessly and provide a consistent and stable user experience that positions us for future growth.
NEW QUESTION # 168
For this question, refer to the JencoMart case study.
The migration of JencoMart's application to Google Cloud Platform (GCP) is progressing too slowly. The infrastructure is shown in the diagram. You want to maximize throughput. What are three potential bottlenecks? (Choose 3 answers.)
- A. Complicated internet connectivity between the on-premises infrastructure and GCP
- B. A tier of Google Cloud Storage that is not suited for this task
- C. A separate storage layer outside the VMs, which is not suited for this task
- D. A single VPN tunnel, which limits throughput
- E. Fewer virtual machines (VMs) in GCP than on-premises machines
- F. A copy command that is not suited to operate over long distances
Answer: A,C,D
NEW QUESTION # 169
Your customer is receiving reports that their recently updated Google App Engine application is taking approximately 30 seconds to load for some of their users. This behavior was not reported before the update. What strategy should you take?
- A. Roll back to an earlier known good release initially, then use Stackdriver Trace and logging to diagnose the problem in a development/test/staging environment.
- B. Work with your ISP to diagnose the problem.
- C. Roll back to an earlier known good release, then push the release again at a quieter period to investigate. Then use Stackdriver Trace and logging to diagnose the problem.
- D. Open a support ticket to ask for network capture and flow data to diagnose the problem, then roll back your application.
Answer: A
Explanation:
Stackdriver Logging allows you to store, search, analyze, monitor, and alert on log data and events from Google Cloud Platform and Amazon Web Services (AWS). Our API also allows ingestion of any custom log data from any source. Stackdriver Logging is a fully managed service that performs at scale and can ingest application and system log data from thousands of VMs.
Even better, you can analyze all that log data in real time.
References: https://cloud.google.com/logging/
NEW QUESTION # 170
You are deploying an application on App Engine that needs to integrate with an on-premises database. For security purposes, your on-premises database must not be accessible through the public Internet. What should you do?
- A. Deploy your application on App Engine standard environment and use App Engine firewall rules to limit access to the open on-premises database.
- B. Deploy your application on App Engine standard environment and use Cloud VPN to limit access to the onpremises database.
- C. Deploy your application on App Engine flexible environment and use App Engine firewall rules to limit access to the on-premises database.
- D. Deploy your application on App Engine flexible environment and use Cloud VPN to limit access to the on-premises database.
Answer: D
Explanation:
Reference:
https://cloud.google.com/appengine/docs/flexible/python/using-third-party-databases
NEW QUESTION # 171
For this question, refer to the Mountkirk Games case study.
Mountkirk Games has deployed their new backend on Google Cloud Platform (GCP). You want to create a thorough testing process for new versions of the backend before they are released to the public. You want the testing environment to scale in an economical way.
How should you design the process?
- A. Use the existing infrastructure to test the GCP-based backend at scale.
- B. Create a scalable environment in GCP for simulating production load.
- C. Create a set of static environments in GCP to test different levels of load - for example, high, medium, and low.
- D. Build stress tests into each component of your application using resources internal to GCP to simulate load.
Answer: B
NEW QUESTION # 172
You have developed a non-critical update to your application that is running in a managed instance group, and have created a new instance template with the update that you want to release. To prevent any possible impact to the application, you don't want to update any running instances. You want any new instances that are created by the managed instance group to contain the new update. What should you do?
- A. Start a new rolling replace operation.
- B. Start a new rolling restart operation.
- C. Start a new rolling update. Select the Opportunistic update mode.
- D. Start a new rolling update. Select the Proactive update mode.
Answer: C
Explanation:
In certain scenarios, an opportunistic update is useful because you don't want to cause instability to the system if it can be avoided. For example, if you have a non-critical update that can be applied as necessary without any urgency and you have a MIG that is actively being autoscaled, perform an opportunistic update so that Compute Engine does not actively tear down your existing instances to apply the update. When resizing down, the autoscaler preferentially terminates instances with the old template as well as instances that are not yet in a RUNNING state.
NEW QUESTION # 173
The operations manager asks you for a list of recommended practices that she should consider when migrating a J2EE application to the cloud. Which three practices should you recommend? Choose 3 answers
- A. Migrate from MySQL to a managed NoSQL database like Google Cloud Datastore or Bigtable.
- B. Instrument the application with a monitoring tool like Stackdriver Debugger.
- C. Deploy a continuous integration tool with automated testing in a staging environment.
- D. Select an automation framework to reliably provision the cloud infrastructure.
- E. Port the application code to run on Google App Engine.
- F. Integrate Cloud Dataflow into the application to capture real-time metrics.
Answer: C,D,E
Explanation:
Explanation
References: https://cloud.google.com/appengine/docs/standard/java/tools/uploadinganapp
https://cloud.google.com/appengine/docs/standard/java/building-app/cloud-sql
NEW QUESTION # 174
You need to deploy a stateful workload on Google Cloud. The workload can scale horizontally, but each instance needs to read and write to the same POSIX filesystem. At high load, the stateful workload needs to support up to 100 MB/s of writes. What should you do?
- A. Create a Cloud Filestore instance and mount it in each instance.
- B. Use a regional persistent disk for each instance.
- C. Use a persistent disk for each instance.
- D. Create a Cloud Storage bucket and mount it in each instance using gcsfuse.
Answer: A
Explanation:
Explanation
https://cloud.google.com/storage/docs/gcs-fuse#notes
Cloud Filestore: Cloud Filestore is a scalable and highly available shared file service fully managed by Google. Cloud Filestore provides persistent storage ideal for shared workloads. It is best suited for enterprise applications requiring persistent, durable, shared storage which is accessed by NFS or requires a POSIX compliant file system.
Reference: https://cloud.google.com/storage/docs/gcs-fuse
NEW QUESTION # 175
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 # 176
For this question, refer to the Dress4Win case study. You want to ensure that your on-premises
architecture meets business requirements before you migrate your solution.
What change in the on-premises architecture should you make?
- A. Replace RabbitMQ with Google Pub/Sub.
- B. Resize compute resources to match predefined Compute Engine machine types.
- C. Containerize the micro services and host them in Google Kubernetes Engine.
- D. Downgrade MySQL to v5.7, which is supported by Cloud SQL for MySQL.
Answer: B
Explanation:
Explanation/Reference:
Question Set 1
NEW QUESTION # 177
Your customer runs a web service used by e-commerce sites to offer product recommendations to users. The company has begun experimenting with a machine learning model on Google Cloud Platform to improve the quality of results.
What should the customer do to improve their model's results over time?
- A. Export Cloud Machine Learning Engine performance metrics from Stackdriver to BigQuery, to be used to analyze the efficiency of the model.
- B. Build a roadmap to move the machine learning model training from Cloud GPUs to Cloud TPUs, which offer better results.
- C. Save a history of recommendations and results of the recommendations in BigQuery, to be used as training data.
- D. Monitor Compute Engine announcements for availability of newer CPU architectures, and deploy the model to them as soon as they are available for additional performance.
Answer: C
Explanation:
Reference:
https://cloud.google.com/solutions/building-a-serverless-ml-model
NEW QUESTION # 178
You are implementing Firestore for Mountkirk Games. Mountkirk Games wants to give a new game programmatic access to a legacy game's Firestore database. Access should be as restricted as possible. What should you do?
- A. Create a service account (SA) in the lgacy game's Google Cloud project, give the SA the Organization Admin rule and then give it the Firebase Admin role in both projects
- B. Create a service account (SA) in the legacy game's Google Cloud project, add this SA in the new game's IAM page, and then give it the Firebase Admin role in both projects
- C. Create a service account (SA) in the legacy game's Google Cloud project, give it the Firebase Admin role, and then migrate the new game to the legacy game's project.
- D. Create a service account (SA) in the legacy game's Google Cloud project, add a second SA in the new game's IAM page, and then give the Organization Admin role to both SAs
Answer: D
NEW QUESTION # 179
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 database is online.
- C. Verify that the project quota hasn't been exceeded.
- D. Verify that the load-testing team is not running their tool against production.
Answer: C
Explanation:
Reference:
503 is service unavailable error. If the database was online everyone would get the 503 error.
https://cloud.google.com/docs/quota#capping_usage
NEW QUESTION # 180
Your company has sensitive data in Cloud Storage buckets. Data analysts have Identity Access Management (IAM) permissions to read the buckets. You want to prevent data analysts from retrieving the data in the buckets from outside the office network. What should you do?
- A. 1. Create a VPC Service Controls perimeter that includes the projects with the buckets.
2. Create an access level with the CIDR of the office network. - B. 1. Create a Cloud VPN to the office network.
2. Configure Private Google Access for on-premises hosts. - C. 1. Create a firewall rule for all instances in the Virtual Private Cloud (VPC) network for source range.
2. Use the Classless Inter-domain Routing (CIDR) of the office network. - D. 1. Create a Cloud Function to remove IAM permissions from the buckets, and another Cloud Function to add IAM permissions to the buckets.
2. Schedule the Cloud Functions with Cloud Scheduler to add permissions at the start of business and remove permissions at the end of business.
Answer: A
Explanation:
Explanation
For all Google Cloud services secured with VPC Service Controls, you can ensure that: Resources within a perimeter are accessed only from clients within authorized VPC networks using Private Google Access with either Google Cloud or on-premises. https://cloud.google.com/vpc-service-controls/docs/overview
https://cloud.google.com/vpc-service-controls/docs/overview. You create a service control across your VPC and any cloud bucket or any project resource to restrict access. Anything outside of it can't access the resources within service control perimeter
NEW QUESTION # 181
Your BigQuery project has several users. For audit purposes, you need to see how many queries each user ran in the last month.
- A. In the BigQuery interface, execute a query on the JOBS table to get the required information.
- B. Connect Google Data Studio to BigQuery. Create a dimension for the users and a metric for the amount of queries per user.
- C. Use Cloud Audit Logging to view Cloud Audit Logs, and create a filter on the query operation to get the required information.
- D. Use 'bq show' to list all jobs. Per job, use 'bq Is' to list job information and get the required information.
Answer: D
NEW QUESTION # 182
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