Google Professional-Cloud-Architect Top Exam Dumps & Latest Professional-Cloud-Architect Exam Objectives

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Google Professional-Cloud-Architect Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Managing and provisioning solution infrastructure	15%	- Managing storage and data services 1. Cloud Storage, Filestore, Persistent Disk management 2. Database deployment, replication, and backup - Configuring network topologies and connectivity 1. VPC design, peering, and hybrid connectivity 2. Load balancing and CDN configuration - Provisioning and managing compute resources 1. Auto-scaling and resource management 2. VMs, GKE, App Engine, Cloud Run deployment and management
Topic 2: Designing and planning a cloud solution architecture	25%	- Planning cloud migration and hybrid/multi-cloud environments 1. Data transfer and synchronization 2. Migration planning and execution 3. Interoperability and integration design - Evaluating and selecting Google Cloud services 1. Serverless and managed service adoption 2. Compute, storage, database, and networking service selection - Designing cloud solution infrastructure aligned with business requirements 1. Scalability, high availability, and fault tolerance design 2. Compliance and regulatory requirements consideration 3. Cost optimization strategies
Topic 3: Designing for security and compliance	17.5%	- Implementing identity and access management 1. Organizational policies and resource hierarchy 2. IAM roles, permissions, and service accounts - Enforcing compliance and governance 1. Security controls, auditing, and logging 2. VPC Service Controls and security perimeters - Securing data and communications 1. Encryption at rest and in transit 2. Key management and secret security
Topic 4: Analyzing and optimizing technical and business processes	15%	- Optimizing cost and resource efficiency 1. Committed use discounts and pricing models 2. Resource right-sizing and usage monitoring - Streamlining operational workflows 1. Stakeholder communication and alignment 2. Change management and incident response - Improving reliability and performance 1. SLO, SLA, and error budgeting 2. Latency reduction and throughput optimization
Topic 5: Managing implementation	12.5%	- Using Google Cloud tools and APIs programmatically 1. Infrastructure as Code (Terraform, Deployment Manager) 2. Cloud SDK, Cloud Shell, and Cloud Code - Guiding development and deployment teams 1. Application and infrastructure deployment strategies 2. CI/CD pipelines and automation - Testing and validating solutions 1. Disaster recovery and failover testing 2. Functional, performance, and security testing
Topic 6: Ensuring solution and operations excellence	12.5%	- Planning for continuous improvement 1. Feedback loops and optimization cycles 2. Technology updates and architecture evolution - Implementing monitoring, logging, and observability 1. Cloud Monitoring, Logging, and Error Reporting 2. Alerting, dashboarding, and root cause analysis - Applying Well-Architected Framework principles 1. Operational excellence, reliability, security, cost, and performance pillars

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Google Certified Professional - Cloud Architect (GCP) Sample Questions (Q281-Q286):

NEW QUESTION # 281
Your company is building a new architecture to support its data-centric business focus. You are responsible for setting up the network. Your company's mobile and web-facing applications will be deployed on-premises, and all data analysis will be conducted in GCP. The plan is to process and load 7 years of archived .csv files totaling
900 TB of data and then continue loading 10 TB of data daily. You currently have an existing 100-MB internet connection.
What actions will meet your company's needs?

A. Lease a Transfer Appliance, upload archived files to it, and send it, and send it to Google to transfer archived data to Cloud Storage. Establish one Cloud VPN Tunnel to VPC networks over the public internet, and compares and upload files daily using the gsutil-m option.
B. Lease a Transfer Appliance, upload archived files to it, and send it, and send it to Google to transfer archived data to Cloud Storage. Establish a connection with Google using a Dedicated Interconnect or Direct Peering connection and use it to upload files daily.
C. Compress and upload both archived files and files uploaded daily using the qsutil -moption.
D. Lease a Transfer Appliance, upload archived files to it, and send it to Google to transfer archived data to Cloud Storage. Establish a Cloud VPN Tunnel to VPC networks over the public internet, and compress and upload files daily.

Answer: C

Explanation:
Explanation/Reference:

NEW QUESTION # 282
Dress4Win has end-to-end tests covering 100% of their endpoints.
They want to ensure that the move to the cloud does not introduce any new bugs.
Which additional testing methods should the developers employ to prevent an outage?

A. They should add additional unit tests and production scale load tests on their cloud staging
environment.
B. They should add canary tests so developers can measure how much of an impact the new release
causes to latency.
C. They should enable Google Stackdriver Debugger on the application code to show errors in the code.
D. They should run the end-to-end tests in the cloud staging environment to determine if the code is
working as intended.

Answer: A

NEW QUESTION # 283
Case Study: 7 - Mountkirk Games
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.
For this question, refer to the Mountkirk Games case study. You are in charge of the new Game Backend Platform architecture. The game communicates with the backend over a REST API.
You want to follow Google-recommended practices. How should you design the backend?

A. Create an instance template for the backend. For every region, deploy it on a multi-zone managed instance group. Use an L4 load balancer.
B. Create an instance template for the backend. For every region, deploy it on a single-zone managed instance group. Use an L7 load balancer.
C. Create an instance template for the backend. For every region, deploy it on a multi-zone managed instance group. Use an L7 load balancer.
D. Create an instance template for the backend. For every region, deploy it on a single-zone managed instance group. Use an L4 load balancer.

Answer: A

NEW QUESTION # 284
Your team is developing a web application that will be deployed on Google Kubernetes Engine (GKE). Your CTO expects a successful launch and you need to ensure your application can handle the expected load of tens of thousands of users. You want to test the current deployment to ensure the latency of your application stays below a certain threshold. What should you do?

A. Use Cloud Debugger in the development environment to understand the latency between the different microservices.
B. Use a load testing tool to simulate the expected number of concurrent users and total requests to your application, and inspect the results.
C. Replicate the application over multiple GKE clusters in every Google Cloud region. Configure a global HTTP(S) load balancer to expose the different clusters over a single global IP address.
D. Enable autoscaling on the GKE cluster and enable horizontal pod autoscaling on your application deployments. Send curl requests to your application, and validate if the auto scaling works.

Answer: B

Explanation:
The question focuses more on the current infra and ensuring if the current setup will ensure a latency target. An only a load test can do that. Autoscaling is no need of the hour and may require in the future and that totally depends on the test results. It might be an overkill to have everything in advance even App is fine with current configs.

NEW QUESTION # 285
Your company's user-feedback portal comprises a standard LAMP stack replicated across two zones. It is deployed in the us-central1 region and uses autoscaled managed instance groups on all layers, except the database. Currently, only a small group of select customers have access to the portal. The portal meets a
99.99% availability SLA under these conditions However next quarter, your company will be making the portal available to all users, including unauthenticated users. You need to develop a resiliency testing strategy to ensure the system maintains the SLA once they introduce additional user load. What should you do?

A. Capture existing users input, and replay captured user load until autoscale is triggered on all layers. At the same time, terminate all resources in one of the zones.
B. Create synthetic random user input, replay synthetic load until autoscale logic is triggered on at least one layer, and introduce "chaos" to the system by terminating random resources on both zones.
C. Capture existing users input, and replay captured user load until resource utilization crosses 80%. Also, derive estimated number of users based on existing users usage of the app, and deploy enough resources to handle 200% of expected load.
D. Expose the new system to a larger group of users, and increase group ' size each day until autoscale logic is tnggered on all layers. At the same time, terminate random resources on both zones.

Answer: B

NEW QUESTION # 286
......

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