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Google Professional-Cloud-Architect Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Designing and planning a cloud solution architecture25%- 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. Compliance and regulatory requirements consideration
  • 2. Cost optimization strategies
  • 3. Scalability, high availability, and fault tolerance design
Topic 2: Analyzing and optimizing technical and business processes15%- 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
- Improving reliability and performance
  • 1. Latency reduction and throughput optimization
  • 2. SLO, SLA, and error budgeting
Topic 3: Ensuring solution and operations excellence12.5%- 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
- Planning for continuous improvement
  • 1. Feedback loops and optimization cycles
  • 2. Technology updates and architecture evolution
Topic 4: Managing and provisioning solution infrastructure15%- Managing storage and data services
  • 1. Database deployment, replication, and backup
  • 2. Cloud Storage, Filestore, Persistent Disk management
- Configuring network topologies and connectivity
  • 1. VPC design, peering, and hybrid connectivity
  • 2. Load balancing and CDN configuration
- Provisioning and managing compute resources
  • 1. VMs, GKE, App Engine, Cloud Run deployment and management
  • 2. Auto-scaling and resource management
Topic 5: Designing for security and compliance17.5%- Securing data and communications
  • 1. Encryption at rest and in transit
  • 2. Key management and secret security
- Enforcing compliance and governance
  • 1. VPC Service Controls and security perimeters
  • 2. Security controls, auditing, and logging
- Implementing identity and access management
  • 1. Organizational policies and resource hierarchy
  • 2. IAM roles, permissions, and service accounts
Topic 6: Managing implementation12.5%- Testing and validating solutions
  • 1. Functional, performance, and security testing
  • 2. Disaster recovery and failover testing
- 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. Cloud SDK, Cloud Shell, and Cloud Code
  • 2. Infrastructure as Code (Terraform, Deployment Manager)

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Google Certified Professional - Cloud Architect (GCP) Sample Questions (Q315-Q320):

NEW QUESTION # 315
You are migrating third-party applications from optimized on-premises virtual machines to Google Cloud. You are unsure about the optimum CPU and memory options. The application have a consistent usage patterns across multiple weeks. You want to optimize resource usage for the lowest cost. What should you do?

Answer: D

Explanation:
Create a Compute engine instance with CPU and Memory options similar to your application's current on-premises virtual machine. Install the cloud monitoring agent, and deploy the third party application. Run a load with normal traffic levels on third party application and follow the Rightsizing Recommendations in the Cloud Console
https://cloud.google.com/migrate/compute-engine/docs/4.9/concepts/planning-a-migration/cloud-instance-rightsizing?hl=en


NEW QUESTION # 316
A few days after JencoMart migrates the user credentials database to Google Cloud Platform and shuts down the old server, the new database server stops responding to SSH connections. It is still serving database requests to the application servers correctly.
What three steps should you take to diagnose the problem? (Choose three.)

Answer: C,D,E

Explanation:
D: Handling "Unable to connect on port 22" error message
Possible causes include:
* There is no firewall rule allowing SSH access on the port. SSH access on port 22 is enabled on all Compute Engine instances by default. If you have disabled access, SSH from the Browser will not work. If you run sshd on a port other than 22, you need to enable the access to that port with a custom firewall rule.
* The firewall rule allowing SSH access is enabled, but is not configured to allow connections from GCP Console services. Source IP addresses for browser-based SSH sessions are dynamically allocated by GCP Console and can vary from session to session.
F: Handling "Could not connect, retrying..." error
You can verify that the daemon is running by navigating to the serial console output page and looking for output lines prefixed with the accounts-from-metadata: string. If you are using a standard image but you do not see these output prefixes in the serial console output, the daemon might be stopped. Reboot the instance to restart the daemon.
Reference:
https://cloud.google.com/compute/docs/ssh-in-browser
https://cloud.google.com/compute/docs/ssh-in-browser


NEW QUESTION # 317
You have been asked to select the storage system for the click-data of your company's large portfolio of websites. This data is streamed in from a custom website analytics package at a typical rate of 6,000 clicks per minute, with bursts of up to 8,500 clicks per second. It must been stored for future analysis by your data science and user experience teams. Which storage infrastructure should you choose?

Answer: D

Explanation:
Explanation
https://cloud.google.com/solutions/data-analytics-partner-ecosystem
https://zulily-tech.com/2015/08/10/leveraging-google-cloud-dataflow-for-clickstream-processing/ Google Cloud Bigtable is a scalable, fully-managed NoSQL wide-column database that is suitable for both real-time access and analytics workloads.
Good for:
* Low-latency read/write access
* High-throughput analytics
* Native time series support
* Common workloads:
* IoT, finance, adtech
* Personalization, recommendations
* Monitoring
* Geospatial datasets
* Graphs
Topic 5, Dress4Win Case 2
Company Overview
Dress4win is a web-based company that helps their users organize and manage their personal wardrobe using a website 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 collocated 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 # 318
For this question, refer to the TerramEarth case study
Your development team has created a structured API to retrieve vehicle data. They want to allow third parties to develop tools for dealerships that use this vehicle event data. You want to support delegated authorization against this data. What should you do?

Answer: B

Explanation:
Explanation
https://cloud.google.com/appengine/docs/flexible/go/authorizing-apps
https://cloud.google.com/docs/enterprise/best-practices-for-enterprise-organizations#delegate_application_autho Delegate application authorization with OAuth2 Cloud Platform APIs support OAuth 2.0, and scopes provide granular authorization over the methods that are supported. Cloud Platform supports both service-account and user-account OAuth, also called three-legged OAuth.
References:
https://cloud.google.com/docs/enterprise/best-practices-for-enterprise-organizations#delegate_application_autho
https://cloud.google.com/appengine/docs/flexible/go/authorizing-apps


NEW QUESTION # 319
You need to set up Microsoft SQL Server on GCP. Management requires that there's no downtime in case
of a data center outage in any of the zones within a GCP region. What should you do?

Answer: B

Explanation:
Explanation/Reference:
Reference: https://cloud.google.com/solutions/sql-server-always-on-compute-engine


NEW QUESTION # 320
......

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