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Google Professional-Cloud-Architect Exam Syllabus Topics:

Section	Objectives
Designing for security and compliance	- Designing for compliance 1. Regulatory and compliance requirements 2. Data residency and sovereignty 3. Audit logging and monitoring - Designing for security 1. Application security 2. Identity and Access Management (IAM) 3. Network security 4. Data security and encryption
Ensuring solution and operations reliability	- Deployment and release management 1. Release management and versioning 2. Deployment strategies and rollback - Monitoring/logging/profiling/alerting solution 1. Cloud Monitoring and Cloud Logging 2. Error reporting and alerting 3. Performance profiling and tracing - Evaluating quality control measures - Assisting with support 1. Incident response and troubleshooting 2. Capacity planning and scaling
Managing and provisioning a solution infrastructure	- Configuring network topologies 1. Private access and VPN configuration 2. Hybrid and multi-cloud connectivity 3. VPC design and peering - Configuring individual storage systems 1. Datastore and Bigtable 2. Cloud SQL and Spanner 3. Cloud Storage configuration - Configuring compute systems 1. Compute Engine configuration 2. GKE configuration and management 3. Cloud Run and Cloud Functions
Designing and planning a cloud solution architecture	- Creating a migration plan 1. Identifying workloads for migration 2. Planning data migration 3. Refactoring and rearchitecting applications - Enabling future cloud technology 1. Designing for scalability and elasticity 2. Implementing future-proof architectures - Designing solution infrastructure that meets business requirements 1. Cost optimization 2. Networking and compute resources 3. Integration with existing systems 4. Migration planning 5. Data and storage architecture 6. Business use cases and product strategy - Designing network, storage, and compute resources 1. Storage options and data lifecycle management 2. Network design including load balancing and firewall rules 3. GKE cluster and workload design 4. Compute engine selection and configuration
Analyzing and optimizing technical and business processes	- Analyzing and defining business processes 1. Cost management and optimization 2. Business KPIs and metrics 3. Stakeholder communication - Analyzing and defining technical processes 1. Incident management and troubleshooting 2. Software development lifecycle (SDLC) 3. CI/CD pipeline design
Managing implementation	- Interacting with Google Cloud programmatically 1. Infrastructure as Code (IaC) 2. APIs and client libraries 3. Cloud SDK and gcloud CLI - Advising development/operation team(s) to ensure successful deployment 1. Testing and validation 2. Deployment strategies 3. Application development best practices

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Google Certified Professional - Cloud Architect (GCP) Professional-Cloud-Architect Prüfungsfragen mit Lösungen (Q212-Q217):

212. Frage
You are designing a large distributed application with 30 microservices. Each of your distributed microservices needs to connect to a database back-end. You want to store the credentials securely. Where should you store the credentials?

A. In an environment variable
B. In a secret management system
C. In a config file that has restricted access through ACLs
D. In the source code

Antwort: B

Begründung:
Reference:
https://cloud.google.com/docs/authentication/production#providing_credentials_to_your_application

213. Frage
For this question, refer to the EHR Healthcare case study. You are a developer on the EHR customer portal team. Your team recently migrated the customer portal application to Google Cloud. The load has increased on the application servers, and now the application is logging many timeout errors. You recently incorporated Pub/Sub into the application architecture, and the application is not logging any Pub/Sub publishing errors.
You want to improve publishing latency. What should you do?

A. Move from a Pub/Sub subscriber pull model to a push model.
B. Create a backup Pub/Sub message queue.
C. Turn off Pub/Sub message batching.
D. Increase the Pub/Sub Total Timeout retry value.

Antwort: C

Begründung:
Explanation
https://cloud.google.com/pubsub/docs/publisher?hl=en#batching

214. Frage
For this question, refer to the EHR Healthcare case study. In the past, configuration errors put public IP addresses on backend servers that should not have been accessible from the Internet. You need to ensure that no one can put external IP addresses on backend Compute Engine instances and that external IP addresses can only be configured on frontend Compute Engine instances. What should you do?

A. Create a custom Identity and Access Management (IAM) role named GCE_FRONTEND with the compute.addresses.create permission.
B. Revoke the compute.networkAdmin role from all users in the project with front end instances.
C. Create an Organizational Policy with a constraint to allow external IP addresses only on the frontend Compute Engine instances.
D. Create an Identity and Access Management (IAM) policy that maps the IT staff to the compute.
networkAdmin role for the organization.

Antwort: C

Begründung:
https://cloud.google.com/compute/docs/ip-addresses/reserve-static-external-ip-address#disableexternalip

215. Frage
Your customer runs a web service used by e-commerce sites to offer product recommendations to users. the company has begun experimenting with a machine learning model on Google Cloud Platform to improve the quality of results.
What should the customer do to improve their model's results over time?

A. Build a roadmap to move the machine learning model training from Cloud GPUs to Cloud TPUs, which offer better results.
B. Monitor Compute Engine announcements for availability of newer CPU architectures, and deploy the model to them as soon as they are available for additional performance.
C. Save a history of recommendations and results of the recommendations in BigQuery, to be used as training data.
D. Export Cloud Machine Learning Engine performance metrics from Stackdriver to BigQuery, to be used to analyze the efficiency of the model.

Antwort: C

Begründung:
BigQuery need data to be applied in AI.

216. Frage
Your company wants to track whether someone is present in a meeting room reserved for a scheduled meeting. There are 1000 meeting rooms across 5 offices on 3 continents. Each room is equipped with a motion sensor that reports its status every second. You want to support the data upload and collection needs of this sensor network. The receiving infrastructure needs to account for the possibility that the devices may have inconsistent connectivity. Which solution should you design?

A. Have devices poll for connectivity to Cloud Pub/Sub and publish the latest messages on a regular interval to a shared topic for all devices.
B. Have devices create a persistent connection to an App Engine application fronted by Cloud Endpoints, which ingest messages and write them to Cloud Datastore.
C. Have each device create a persistent connection to a Compute Engine instance and write messages to a custom application.
D. Have devices poll for connectivity to Cloud SQL and insert the latest messages on a regular interval to a device specific table.

Antwort: A

Begründung:
A is not correct because having a persistent connection does not handle the case where the device is disconnected.
B is not correct because Cloud SQL is a relational database and not the best fit for sensor data.
Additionally, the frequency of the writes has the potential to exceed the supported number of concurrent connections.
C is correct because Cloud Pub/Sub can handle the frequency of this data, and consumers of the data can pull from the shared topic for further processing.
D is not correct because having a persistent connection does not handle the case where the device is disconnected.
https://cloud.google.com/sql/
https://cloud.google.com/pubsub/

217. Frage
......

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