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Google Professional-Cloud-Architect Exam Syllabus Topics:

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

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Google Certified Professional - Cloud Architect (GCP) Sample Questions (Q90-Q95):

NEW QUESTION # 90
Case Study: 3 - JencoMart Case Study
Company Overview
JencoMart is a global retailer with over 10,000 stores in 16 countries. The stores carry a range of goods, such as groceries, tires, and jewelry. One of the company's core values is excellent customer service. In addition, they recently introduced an environmental policy to reduce their carbon output by 50% over the next 5 years.
Company Background
JencoMart started as a general store in 1931, and has grown into one of the world's leading brands known for great value and customer service. Over time, the company transitioned from only physical stores to a stores and online hybrid model, with 25% of sales online. Currently, JencoMart has little presence in Asia, but considers that market key for future growth.
Solution Concept
JencoMart wants to migrate several critical applications to the cloud but has not completed a technical review to determine their suitability for the cloud and the engineering required for migration. They currently host all of these applications on infrastructure that is at its end of life and is no longer supported.
Existing Technical Environment
JencoMart hosts all of its applications in 4 data centers: 3 in North American and 1 in Europe, most applications are dual-homed.
JencoMart understands the dependencies and resource usage metrics of their on-premises architecture.
Application Customer loyalty portal
LAMP (Linux, Apache, MySQL and PHP) application served from the two JencoMart-owned U.S.
data centers.
Database
* Oracle Database stores user profiles

* PostgreSQL database stores user credentials
-homed in US West

Authenticates all users
Compute
* 30 machines in US West Coast, each machine has:

* 20 machines in US East Coast, each machine has:
-core CPU

Storage
* Access to shared 100 TB SAN in each location
* Tape backup every week
Business Requirements
* Optimize for capacity during peak periods and value during off-peak periods
* Guarantee service availably and support
* Reduce on-premises footprint and associated financial and environmental impact.
* Move to outsourcing model to avoid large upfront costs associated with infrastructure purchase
* Expand services into Asia.
Technical Requirements
* Assess key application for cloud suitability.
* Modify application for the cloud.
* Move applications to a new infrastructure.
* Leverage managed services wherever feasible
* Sunset 20% of capacity in existing data centers
* Decrease latency in Asia
CEO Statement
JencoMart will continue to develop personal relationships with our customers as more people access the web. The future of our retail business is in the global market and the connection between online and in-store experiences. As a large global company, we also have a responsibility to the environment through 'green' initiatives and polices.
CTO Statement
The challenges of operating data centers prevents focus on key technologies critical to our long- term success. Migrating our data services to a public cloud infrastructure will allow us to focus on big data and machine learning to improve our service customers.
CFO Statement
Since its founding JencoMart has invested heavily in our data services infrastructure. However, because of changing market trends, we need to outsource our infrastructure to ensure our long- term success. This model will allow us to respond to increasing customer demand during peak and reduce costs.
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 Datastore
B. Cloud Spanner
C. Google BigQuery
D. Google Cloud SQL

Answer: A

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

NEW QUESTION # 91
Your company has a Google Cloud project that uses BlgQuery for data warehousing There are some tables that contain personally identifiable information (PI!) Only the compliance team may access the PH. The other information in the tables must be available to the data science team. You want to minimize cost and the time it takes to assign appropriate access to the tables What should you do?

A. 1 From the dataset where you have the source data, create materialized views of tables that you want to share excluding Pll
2 Assign an appropriate project-level IAM role to the members of the data science team 3. Assign access controls to the dataset that contains the view.
B. 1. Create a dataset for the data science team.
2. Create materialized views of tables that you want to share, excluding Pll
3. Assign an appropriate project-level IAM role to the members of the data science team
4 Assign access controls to the dataset that contains the view
5 Authorize the view to access the source dataset
C. 1 From the dataset where you have the source data, create views of tables that you want to share, excluding Pll
2 Assign an appropriate project-level IAM role to the members of the data science team
3 Assign access controls to the dataset that contains the view
D. 1 Create a dataset for the data science team
2 Create views of tables that you want to share excluding Pll
3 Assign an appropriate project-level IAM role to the members of the data science team
4 Assign access controls to the dataset that contains the view
5 Authorize the view to access the source dataset

Answer: D

Explanation:
Explanation
This option can help minimize cost and time by using views and authorized datasets. Views are virtual tables defined by a SQL query that can exclude PII columns from the source tables. Views do not incur storage costs and do not duplicate data. Authorized datasets are datasets that have access to another dataset's data without granting direct access to individual users or groups. By creating a dataset for the data science team and creating views of tables that exclude PII, you can share only the relevant information with the team. By assigning an appropriate project-level IAM role to the members of the data science team, you can grant them access to the BigQuery service and resources. By assigning access controls to the dataset that contains the view, you can grant them access to query the views. By authorizing the view to access the source dataset, you can enable the view to read data from the source tables without exposing PII. The other options are not optimal for this scenario, because they either use materialized views instead of views, which incur storage costs and duplicate data (B, D), or do not create a separate dataset for the data science team, which makes it harder to manage access controls (A). References:
https://cloud.google.com/bigquery/docs/views
https://cloud.google.com/bigquery/docs/authorized-datasets

NEW QUESTION # 92
Your customer support tool logs all email and chat conversations to Cloud Bigtable for retention and analysis.
What is the recommended approach for sanitizing this data of personally identifiable information or payment card information before initial storage?

A. Encrypt all data using elliptic curve cryptography
B. Hash all data using SHA256
C. De-identify the data with the Cloud Data Loss Prevention API
D. Use regular expressions to find and redact phone numbers, email addresses, and credit card numbers

Answer: C

Explanation:
Explanation/Reference: https://cloud.google.com/solutions/pci-dss-compliance-in- gcp#using_data_loss_prevention_api_to_sanitize_data

NEW QUESTION # 93
The JencoMart security team requires that all Google Cloud Platform infrastructure is deployed using a least privilege model with separation of duties for administration between production and development resources.
What Google domain and project structure should you recommend?

A. Create two G Suite accounts to manage users: one with a single project for all development applications and one with a single project for all production applications
B. Create a single G Suite account to manage users with each stage of each application in its own project
C. Create two G Suite accounts to manage users: one for development/test/staging and one for production.
Each account should contain one project for every application
D. Create a single G Suite account to manage users with one project for the development/test/staging environment and one project for the production environment

Answer: D

Explanation:
Note: The principle of least privilege and separation of duties are concepts that, although semantically different, are intrinsically related from the standpoint of security. The intent behind both is to prevent people from having higher privilege levels than they actually need
* Principle of Least Privilege: Users should only have the least amount of privileges required to perform their job and no more. This reduces authorization exploitation by limiting access to resources such as targets, jobs, or monitoring templates for which they are not authorized.
* Separation of Duties: Beyond limiting user privilege level, you also limit user duties, or the specific jobs they can perform. No user should be given responsibility for more than one related function. This limits the ability of a user to perform a malicious action and then cover up that action.
Reference: https://cloud.google.com/kms/docs/separation-of-duties
Mountkirk Games, A
Testlet 1
Company Overview
Mountkirk Games makes online, session-based, multiplayer games for the most popular 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 clous resources we use
* Reduce lateny to all customers
Technical Requirements
Requirements for Game Backend Platform
1. Dynamically scale up or down based on game activity
2. Connect to a managed NoSQL database service
3. Run customize Linux distro
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
CEO 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.
CTO Statement
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.
CFO Statement
We are not capturing enough user demographic data, usage metrics, and other KPIs. As a result, we do not engage the right users, we are not confident that our marketing is targeting the right users, and we are not selling enough premium Blast-Ups inside the games, which dramatically impacts our revenue.

NEW QUESTION # 94
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 Kubernetes Registry, Google Container Engine, Google HTTP(S) Load Balancer
B. Google Cloud Storage, Google Cloud Dataflow, Google Compute Engine
C. Google Cloud Functions, Google Cloud Pub/Sub, Google Cloud Deployment Manager
D. Google Cloud Storage, Google App Engine, Google Network Load Balancer

Answer: A

NEW QUESTION # 95
......

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