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Google Professional-Cloud-Architect Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Managing and provisioning solution infrastructure15%- Provisioning and managing compute resources
  • 1. VMs, GKE, App Engine, Cloud Run deployment and management
  • 2. Auto-scaling and resource management
- Configuring network topologies and connectivity
  • 1. VPC design, peering, and hybrid connectivity
  • 2. Load balancing and CDN configuration
- Managing storage and data services
  • 1. Cloud Storage, Filestore, Persistent Disk management
  • 2. Database deployment, replication, and backup
Topic 2: Managing implementation12.5%- Guiding development and deployment teams
  • 1. CI/CD pipelines and automation
  • 2. Application and infrastructure deployment strategies
- Testing and validating solutions
  • 1. Disaster recovery and failover testing
  • 2. Functional, performance, and security testing
- Using Google Cloud tools and APIs programmatically
  • 1. Cloud SDK, Cloud Shell, and Cloud Code
  • 2. Infrastructure as Code (Terraform, Deployment Manager)
Topic 3: Ensuring solution and operations excellence12.5%- 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
- Implementing monitoring, logging, and observability
  • 1. Alerting, dashboarding, and root cause analysis
  • 2. Cloud Monitoring, Logging, and Error Reporting
Topic 4: 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. Organizational policies and resource hierarchy
  • 2. IAM roles, permissions, and service accounts
- Securing data and communications
  • 1. Encryption at rest and in transit
  • 2. Key management and secret security
Topic 5: Designing and planning a cloud solution architecture25%- Evaluating and selecting Google Cloud services
  • 1. Compute, storage, database, and networking service selection
  • 2. Serverless and managed service adoption
- Planning cloud migration and hybrid/multi-cloud environments
  • 1. Data transfer and synchronization
  • 2. Migration planning and execution
  • 3. Interoperability and integration design
- 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 6: 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

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Google Certified Professional - Cloud Architect (GCP) Sample Questions (Q268-Q273):

NEW QUESTION # 268
Case Study: 9 - Helicopter Racing League
Company overview
Helicopter Racing League (HRL) is a global sports league for competitive helicopter racing. Each year HRL holds the world championship and several regional league competitions where teams compete to earn a spot in the world championship. HRL offers a paid service to stream the races all over the world with live telemetry and predictions throughout each race.
Solution concept
HRL wants to migrate their existing service to a new platform to expand their use of managed AI and ML services to facilitate race predictions. Additionally, as new fans engage with the sport, particularly in emerging regions, they want to move the serving of their content, both real-time and recorded, closer to their users.
Existing technical environment
HRL is a public cloud-first company; the core of their mission-critical applications runs on their current public cloud provider. Video recording and editing is performed at the race tracks, and the content is encoded and transcoded, where needed, in the cloud. Enterprise-grade connectivity and local compute is provided by truck-mounted mobile data centers. Their race prediction services are hosted exclusively on their existing public cloud provider. Their existing technical environment is as follows:
- Existing content is stored in an object storage service on their existing public cloud provider.
- Video encoding and transcoding is performed on VMs created for each job.
- Race predictions are performed using TensorFlow running on VMs in the current public cloud
provider.
Business requirements
HRL's owners want to expand their predictive capabilities and reduce latency for their viewers in emerging markets. Their requirements are:
- Support ability to expose the predictive models to partners.
- Increase predictive capabilities during and before races:
*Race results
*Mechanical failures
*Crowd sentiment
- Increase telemetry and create additional insights.
- Measure fan engagement with new predictions.
- Enhance global availability and quality of the broadcasts.
- Increase the number of concurrent viewers.
- Minimize operational complexity.
- Ensure compliance with regulations.
- Create a merchandising revenue stream.
Technical requirements
- Maintain or increase prediction throughput and accuracy.
- Reduce viewer latency.
- Increase transcoding performance.
- Create real-time analytics of viewer consumption patterns and engagement.
- Create a data mart to enable processing of large volumes of race data.
Executive statement
Our CEO, S. Hawke, wants to bring high-adrenaline racing to fans all around the world. We listen to our fans, and they want enhanced video streams that include predictions of events within the race (e.g., overtaking). Our current platform allows us to predict race outcomes but lacks the facility to support real-time predictions during races and the capacity to process season-long results.
Helicopter Racing League (HRL) offers premium contents and, among their business requirements, has:
- To increase the number of concurrent viewers and
- To create a merchandising revenue stream
So, they want to offer service subscriptions for their and partner services and manage monetization, pay-as-use management, flat-use control, and rate-limiting. All the functionalities that can assure a managed revenue stream in the simplest way. Which is the best GCP Service to achieve that?

Answer: D


NEW QUESTION # 269
You work for a multinational company and are migrating an Oracle database to a multi-region Spanner cluster. You have to plan the migration activities and the DBAs have told you that the migration will be almost immediate because no non-standard ISO / IEC features or stored procedures are used. But you know that there is an element that will necessarily require some maintenance work. Which is this element?

Answer: B

Explanation:
With traditional SQL databases, it is advisable to use numerical primary keys in sequence. Oracle DB, for example, has an object type that creates progressive values, called a sequence.
Instead, it is important that distributed databases do not use progressive keys, because the tables are split among the nodes in primary key order and therefore all the inserts would take place only at one point, degrading performance.
This problem is called hotspotting.
A is wrong because Spanner handles secondary indexes.
C is wrong because Spanner automatically manages the distribution of data in the clusters.
D is wrong because we already know that the structuring of the tables follows the standards.


NEW QUESTION # 270
Your web application must comply with the requirements of the European Union's General Data Protection Regulation (GDPR). You are responsible for the technical architecture of your web application. What should you do?

Answer: C

Explanation:
Explanation/Reference: https://www.mobiloud.com/blog/gdpr-compliant-mobile-app/


NEW QUESTION # 271
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 3 answers.

Answer: A,D,F

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 # 272
TerramEarth's 20 million vehicles are scattered around the world. Based on the vehicle's location, its telemetry data is stored in a Google Cloud Storage (GCS) regional bucket (US, Europe, or Asia). The CTO has asked you to run a report on the raw telemetry data to determine why vehicles are breaking down after
100 K miles. You want to run this job on all the data.
What is the most cost-effective way to run this job?

Answer: D


NEW QUESTION # 273
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