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Google Professional-Cloud-Architect Exam Syllabus Topics:

SectionWeightObjectives
Managing implementation12.5%- Guiding development and deployment teams
  • 1. Application and infrastructure deployment strategies
  • 2. CI/CD pipelines and automation
- Using Google Cloud tools and APIs programmatically
  • 1. Infrastructure as Code (Terraform, Deployment Manager)
  • 2. Cloud SDK, Cloud Shell, and Cloud Code
- Testing and validating solutions
  • 1. Disaster recovery and failover testing
  • 2. Functional, performance, and security testing
Ensuring solution and operations excellence12.5%- Planning for continuous improvement
  • 1. Technology updates and architecture evolution
  • 2. Feedback loops and optimization cycles
- Implementing monitoring, logging, and observability
  • 1. Alerting, dashboarding, and root cause analysis
  • 2. Cloud Monitoring, Logging, and Error Reporting
- Applying Well-Architected Framework principles
  • 1. Operational excellence, reliability, security, cost, and performance pillars
Managing and provisioning solution infrastructure15%- Configuring network topologies and connectivity
  • 1. Load balancing and CDN configuration
  • 2. VPC design, peering, and hybrid connectivity
- Managing storage and data services
  • 1. Cloud Storage, Filestore, Persistent Disk management
  • 2. Database deployment, replication, and backup
- Provisioning and managing compute resources
  • 1. VMs, GKE, App Engine, Cloud Run deployment and management
  • 2. Auto-scaling and resource management
Designing for security and compliance17.5%- 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
Analyzing and optimizing technical and business processes15%- Optimizing cost and resource efficiency
  • 1. Resource right-sizing and usage monitoring
  • 2. Committed use discounts and pricing models
- 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
Designing and planning a cloud solution architecture25%- 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
- Evaluating and selecting Google Cloud services
  • 1. Serverless and managed service adoption
  • 2. Compute, storage, database, and networking service selection
- Planning cloud migration and hybrid/multi-cloud environments
  • 1. Migration planning and execution
  • 2. Data transfer and synchronization
  • 3. Interoperability and integration design

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Google Certified Professional - Cloud Architect (GCP) Sample Questions (Q81-Q86):

NEW QUESTION # 81
Case Study: 1 - Mountkirk Games Case Study
Company Overview
Mountkirk Games makes online, session-based. multiplayer games for the most popular mobile platforms.
Company Background
Mountkirk Games builds all of their games with some server-side integration and has historically used cloud providers to lease physical servers. A few of their games were more popular than expected, and they had problems scaling their application servers, MySQL databases, and analytics tools.
Mountkirk's 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.
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 customized Linx 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, resuming 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 gams 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.
For this question, refer to the Mountkirk Games case study. Mountkirk Games wants to set up a real-time analytics platform for their new game. The new platform must meet their technical requirements. Which combination of Google technologies will meet all of their requirements?

Answer: A

Explanation:
Ingest millions of streaming events per second from anywhere in the world with Cloud Pub/Sub, powered by Google's unique, high-speed private network. Process the streams with Cloud Dataflow to ensure reliable, exactly-once, low-latency data transformation. Stream the transformed data into BigQuery, the cloud-native data warehousing service, for immediate analysis via SQL or popular visualization tools.
From scenario: They plan to deploy the game's backend on Google Compute Engine so they can capture streaming metrics, run intensive analytics.
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
References: https://cloud.google.com/solutions/big-data/stream-analytics/


NEW QUESTION # 82
You need to deploy an application to Google Cloud. The application receives traffic via TCP and reads and writes data to the filesystem. The application does not support horizontal scaling. The application process requires full control over the data on the file system because concurrent access causes corruption. The business is willing to accept a downtime when an incident occurs, but the application must be available 24/7 to support their business operations. You need to design the architecture of this application on Google Cloud.
What should you do?

Answer: D


NEW QUESTION # 83
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
-  20 TB
-  Complex table structure
-  Well maintained, clean data
-  Strong backup strategy
* PostgreSQL database stores user credentials
-  Single-homed in US West
-      No redundancy
-      Backed up every 12 hours
-  100% uptime service level agreement (SLA)
-  Authenticates all users
Compute
* 30 machines in US West Coast, each machine has:
-      Twin, dual core CPUs
-      32GB of RAM
-  Twin 250 GB HDD (RAID 1)
* 20 machines in US East Coast, each machine has:
-      Single dual-core CPU
-      24 GB of RAM
-  Twin 250 GB HDD (RAID 1)
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 has decided to migrate user profile storage to Google Cloud Datastore and the application servers to Google Compute Engine (GCE). During the migration, the existing infrastructure will need access to Datastore to upload the data. What service account key- management strategy should you recommend?

Answer: C

Explanation:
https://cloud.google.com/iam/docs/understanding-service-
accounts#migrating_data_to_google_cloud_platform
There are two types of service account keys:
GCP-managed keys. These keys are used by Cloud Platform services such as App Engine and Compute Engine. They cannot be downloaded, and are automatically rotated and used for signing for a maximum of two weeks. The rotation process is probabilistic; usage of the new key will gradually ramp up and down over the key's lifetime. We recommend caching the public key set for a service account for at most 24 hours to ensure that you always have access to the current key set.
User-managed keys. These keys are created, downloadable, and managed by users. They expire
10 years from creation, and cease authenticating successfully when they are deleted from the service account.


NEW QUESTION # 84
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 dat a. Which architecture should you recommend?
A)

B)

C)

D)

Answer: A

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/
The push endpoint can be a load balancer.
A container cluster can be used.
Cloud Pub/Sub for Stream Analytics

References: https://cloud.google.com/pubsub/
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 # 85
Your organization has a 3-tier web application deployed in the same network on Google Cloud Platform. Each tier (web, API, and database) scales independently of the others Network traffic should flow through the web to the API tier and then on to the database tier. Traffic should not flow between the web and the database tier. How should you configure the network?

Answer: C

Explanation:
Google Cloud Platform(GCP) enforces firewall rules through rules and tags. GCP rules and tags can be defined once and used across all regions.
References: https://cloud.google.com/docs/compare/openstack/
https://aws.amazon.com/it/blogs/aws/building-three-tier-architectures-with-security-groups/


NEW QUESTION # 86
......

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