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Google Professional-Cloud-Architect Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Managing and provisioning solution infrastructure	15%	- Configuring network topologies and connectivity 1. VPC design, peering, and hybrid connectivity 2. Load balancing and CDN configuration - Managing storage and data services 1. Database deployment, replication, and backup 2. Cloud Storage, Filestore, Persistent Disk management - Provisioning and managing compute resources 1. VMs, GKE, App Engine, Cloud Run deployment and management 2. Auto-scaling and resource management
Topic 2: Designing for security and compliance	17.5%	- 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 - Implementing identity and access management 1. IAM roles, permissions, and service accounts 2. Organizational policies and resource hierarchy
Topic 3: Managing implementation	12.5%	- 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 - Guiding development and deployment teams 1. Application and infrastructure deployment strategies 2. CI/CD pipelines and automation
Topic 4: Analyzing and optimizing technical and business processes	15%	- Improving reliability and performance 1. Latency reduction and throughput optimization 2. SLO, SLA, and error budgeting - Streamlining operational workflows 1. Change management and incident response 2. Stakeholder communication and alignment - Optimizing cost and resource efficiency 1. Committed use discounts and pricing models 2. Resource right-sizing and usage monitoring
Topic 5: Ensuring solution and operations excellence	12.5%	- Applying Well-Architected Framework principles 1. Operational excellence, reliability, security, cost, and performance pillars - Implementing monitoring, logging, and observability 1. Alerting, dashboarding, and root cause analysis 2. Cloud Monitoring, Logging, and Error Reporting - Planning for continuous improvement 1. Feedback loops and optimization cycles 2. Technology updates and architecture evolution
Topic 6: Designing and planning a cloud solution architecture	25%	- 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 (Q215-Q220):

NEW QUESTION # 215
For this question, refer to the EHR Healthcare case study. You are responsible for designing the Google Cloud network architecture for Google Kubernetes Engine. You want to follow Google best practices. Considering the EHR Healthcare business and technical requirements, what should you do to reduce the attack surface?

A. Use a public cluster with master authorized networks enabled and firewall rules.
B. Use a private cluster with a public endpoint with master authorized networks configured.
C. Use a public cluster with firewall rules and Virtual Private Cloud (VPC) routes.
D. Use a private cluster with a private endpoint with master authorized networks configured.

Answer: A

NEW QUESTION # 216
Google Cloud Platform resources are managed hierarchically using organization, folders, and projects. When Cloud Identity and Access Management (IAM) policies exist at these different levels, what is the effective policy at a particular node of the hierarchy?

A. The effective policy is the union of the policy set at the node and policies inherited from its ancestors
B. The effective policy is the intersection of the policy set at the node and policies inherited from its ancestors
C. The effective policy is the policy set at the node and restricted by the policies of its ancestors
D. The effective policy is determined only by the policy set at the node

Answer: A

NEW QUESTION # 217
One of your primary business objectives is being able to trust the data stored in your application. You want to log all changes to the application data. How can you design your logging system to verify authenticity of your logs?

A. Use a SQL database and limit who can modify the log table.
B. Write the log concurrently in the cloud and on premises.
C. Digitally sign each timestamp and log entry and store the signature.
D. Create a JSON dump of each log entry and store it in Google Cloud Storage.

Answer: C

Explanation:
Explanation
https://cloud.google.com/storage/docs/access-logs
References: https://cloud.google.com/logging/docs/reference/tools/gcloud-logging

NEW QUESTION # 218
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. Cloud Spanner
B. Google Cloud Datastore
C. Google Cloud SQL
D. Google BigQuery

Answer: B

Explanation:
https://cloud.google.com/datastore/docs/concepts/overview
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 # 219
Case Study: 7 - Mountkirk Games
Company Overview
Mountkirk Games makes online, session-based, multiplayer games for 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 cloud resources we use.
- Reduce latency to all customers.
Technical Requirements
Requirements for Game Backend Platform
- Dynamically scale up or down based on game activity.
- Connect to a transactional database service to manage user profiles and game state.
- Store game activity in a timeseries database service for future analysis.
- As the system scales, ensure that data is not lost due to processing backlogs.
- Run hardened Linux distro.
Requirements for Game Analytics Platform
- Dynamically scale up or down based on game activity
- Process incoming data on the fly directly from the game servers
- Process data that arrives late because of slow mobile networks
- Allow queries to access at least 10 TB of historical data
- Process files that are regularly uploaded by users' mobile devices
Executive 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.
Additionally, 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.
For this question, refer to the Mountkirk Games case study. Mountkirk Games wants you to design a way to test the analytics platform's resilience to changes in mobile network latency.
What should you do?

A. Add the ability to introduce a random amount of delay before beginning to process analytics files uploaded from mobile devices.
B. Create an opt-in beta of the game that runs on players' mobile devices and collects response times from analytics endpoints running in Google Cloud Platform regions all over the world.
C. Build a test client that can be run from a mobile phone emulator on a Compute Engine virtual machine, and run multiple copies in Google Cloud Platform regions all over the world to generate realistic traffic.
D. Deploy failure injection software to the game analytics platform that can inject additional latency to mobile client analytics traffic.

Answer: D

Explanation:
If you're using a service mesh like Istio to manage your app services, you can inject faults at the application layer instead of killing pods or machines, or you can inject corrupting packets at the TCP layer. You can introduce delays to simulate network latency or an overloaded upstream system. You can also introduce aborts, which mimic failures in upstream systems.
https://cloud.google.com/solutions/scalable-and-resilient-apps

NEW QUESTION # 220
......

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