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Google Professional-Cloud-Architect Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: 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. Functional, performance, and security testing
  • 2. Disaster recovery and failover testing
- Using Google Cloud tools and APIs programmatically
  • 1. Infrastructure as Code (Terraform, Deployment Manager)
  • 2. Cloud SDK, Cloud Shell, and Cloud Code
Topic 2: Designing and planning a cloud solution architecture25%- 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
- 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. Compute, storage, database, and networking service selection
  • 2. Serverless and managed service adoption
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
- Planning for continuous improvement
  • 1. Technology updates and architecture evolution
  • 2. Feedback loops and optimization cycles
- Applying Well-Architected Framework principles
  • 1. Operational excellence, reliability, security, cost, and performance pillars
Topic 4: Designing for security and compliance17.5%- Implementing identity and access management
  • 1. IAM roles, permissions, and service accounts
  • 2. Organizational policies and resource hierarchy
- Enforcing compliance and governance
  • 1. Security controls, auditing, and logging
  • 2. VPC Service Controls and security perimeters
- Securing data and communications
  • 1. Key management and secret security
  • 2. Encryption at rest and in transit
Topic 5: 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. Change management and incident response
  • 2. Stakeholder communication and alignment
- Improving reliability and performance
  • 1. SLO, SLA, and error budgeting
  • 2. Latency reduction and throughput optimization
Topic 6: Managing and provisioning solution infrastructure15%- Provisioning and managing compute resources
  • 1. Auto-scaling and resource management
  • 2. VMs, GKE, App Engine, Cloud Run deployment and management
- 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

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Google Certified Professional - Cloud Architect (GCP) Sample Questions (Q185-Q190):

NEW QUESTION # 185
For this question, refer to the EHR Healthcare case study. You need to define the technical architecture for hybrid connectivity between EHR's on-premises systems and Google Cloud. You want to follow Google's recommended practices for production-level applications. Considering the EHR Healthcare business and technical requirements, what should you do?

Answer: D

Explanation:
Reference:
based on the requirement of secure and high-performance connection between on-premises systems to Google Cloud


NEW QUESTION # 186
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

Explanation:
Storageguarantees 2 replicates which are geo diverse (100 miles apart) which can get better remote latency and availability.
More importantly, is that multiregional heavily leverages Edge caching and CDNs to provide the content to the end users.
All this redundancy and caching means that Multiregional comes with overhead to sync and ensure consistency between geo-diverse areas. As such, it's much better for write-once-read-many scenarios. This means frequently accessed (e.g. "hot" objects) around the world, such as website content, streaming videos, gaming or mobile applications.
References: https://medium.com/google-cloud/google-cloud-storage-what-bucket-class-for-the-best- performance-5c847ac8f9f2


NEW QUESTION # 187
For this question, refer to the Mountkirk Games case study. Which managed storage option meets
Mountkirk's technical requirement for storing game activity in a time series database service?

Answer: D


NEW QUESTION # 188
Your company has an application running as a Deployment in a Google Kubernetes Engine (GKE) cluster When releasing new versions of the application via a rolling deployment, the team has been causing outages The root cause of the outages is misconfigurations with parameters that are only used in production You want to put preventive measures for this in the platform to prevent outages What should you do?

Answer: D

Explanation:
This option can help prevent outages caused by misconfigurations with parameters that are only used in production. Liveness and readiness probes are mechanisms to check the health and availability of the Pods and containers in a GKE cluster. Liveness probes determine if a container is still running, and if not, restart it.
Readiness probes determine if a container is ready to serve requests, and if not, remove it from the load balancer. By configuring liveness and readiness probes in the Pod specification, you can ensure that your application can handle traffic and recover from failures gracefully during a rolling update. The other options are not optimal for this scenario, because they either do not prevent outages, but only alert or monitor them (B, C), or do not apply to GKE clusters, but to Compute Engine instances (D). References:
* https://cloud.google.com/kubernetes-engine/docs/how-to/updating-apps
* https://cloud.google.com/blog/products/containers-kubernetes/kubernetes-best-practices-setting-up- health-checks-with-readiness-and-liveness-probes


NEW QUESTION # 189
You want to enable your running Google Container Engine cluster to scale as demand for your application changes.
What should you do?

Answer: A

Explanation:
https://cloud.google.com/kubernetes-engine/docs/concepts/cluster-autoscaler To enable autoscaling for an existing node pool, run the following command: gcloud container clusters update
[CLUSTER_NAME] --enable-autoscaling \--min-nodes 1 -- max-nodes 10 --zone [COMPUTE_ZONE] -- nodepool default-pool


NEW QUESTION # 190
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