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Google Professional-Cloud-Architect Exam Syllabus Topics:

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

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Google Certified Professional - Cloud Architect (GCP) Sample Questions (Q288-Q293):

NEW QUESTION # 288
You have a Python web application with many dependencies that requires 0.1 CPU cores and
128 MB of memory to operate in production. You want to monitor and maximize machine utilization. You also to reliably deploy new versions of the application. Which set of steps should you take?

A. Perform the following:
1. Create a Kubernetes Engine cluster with n1-standard-4 type machines.
2. Build a Docker image from the master branch will all of the dependencies, and tag it with
"latest".
3. Create a Kubernetes Deployment in the default namespace with the imagePullPolicy set to
"Always". Restart the pods to automatically deploy new production releases.
B. Perform the following:
1. Create a managed instance group with n1-standard-1 type machines.
2. Build a Compute Engine image from the production branch that contains all of the dependencies and automatically starts the Python app.
3. Rebuild the Compute Engine image, and update the instance template to deploy new production releases.
C. Perform the following:
1. Create a managed instance group with f1-micro type machines.
2. Use a startup script to clone the repository, check out the production branch, install the dependencies, and start the Python app.
3. Restart the instances to automatically deploy new production releases.
D. Perform the following:
1. Create a Kubernetes Engine cluster with n1-standard-1 type machines.
2. Build a Docker image from the production branch with all of the dependencies, and tag it with the version number.
3. Create a Kubernetes Deployment with the imagePullPolicy set to "IfNotPresent" in the staging namespace, and then promote it to the production namespace after testing.

Answer: D

NEW QUESTION # 289
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?

A. Ensure that your web application only uses native features and services of Google Cloud Platform, because Google already has various certifications and provides "pass-on" compliance when you use native features.
B. Ensure that Cloud Security Scanner is part of your test planning strategy in order to pick up any compliance gaps.
C. Define a design for the security of data in your web application that meets GDPR requirements.
D. Enable the relevant GDPR compliance setting within the GCPConsole for each of the services in use within your application.

Answer: C

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

NEW QUESTION # 290
You have a Python web application with many dependencies that requires 0.1 CPU cores and 128 MB of memory to operate in production. You want to monitor and maximize machine utilization. You also want to reliably deploy new versions of the application. Which set of steps should you take?

A. Perform the following:
1. Create a Google Kubernetes Engine (GKE) cluster with n1-standard-1 type machines.
2. Build a Docker image from the production branch with all of the dependencies, and tag it with the version number.
3. Create a Kubernetes Deployment with the imagePullPolicy set to 'IfNotPresent' in the staging namespace, and then promote it to the production namespace after testing.
B. Perform the following:
1. Create a managed instance group with n1-standard-1 type machines.
2. Build a Compute Engine image from the production branch that contains all of the dependencies and automatically starts the Python app.
3. Rebuild the Compute Engine image, and update the instance template to deploy new production releases.
C. Perform the following:
1. Create a managed instance group with f1-micro type machines.
2. Use a startup script to clone the repository, check out the production branch, install the dependencies, and start the Python app.
3. Restart the instances to automatically deploy new production releases.
D. Perform the following:
1. Create a GKE cluster with n1-standard-4 type machines.
2. Build a Docker image from the master branch with all of the dependencies, and tag it with 'latest'.
3. Create a Kubernetes Deployment in the default namespace with the imagePullPolicy set to 'Always'.
Restart the pods to automatically deploy new production releases.

Answer: B

NEW QUESTION # 291
Your company has a networking team and a development team. The development team runs applications on Compute Engine instances that contain sensitive dat a. The development team requires administrative permissions for Compute Engine. Your company requires all network resources to be managed by the networking team. The development team does not want the networking team to have access to the sensitive data on the instances. What should you do?

A. 1. Create a project with a Shared VPC and assign the Network Admin role to the networking team.
2. Create a second project without a VPC, configure it as a Shared VPC service project, and assign the Compute Admin role to the development team.
B. 1. Create a project with a standalone VPC and assign the Network Admin role to the networking team.
2. Create a second project with a standalone VPC and assign the Compute Admin role to the development team.
3. Use VPC Peering to join the two VPCs.
C. 1. Create a project with a standalone VPC and assign the Network Admin role to the networking team.
2. Create a second project with a standalone VPC and assign the Compute Admin role to the development team.
3. Use Cloud VPN to join the two VPCs.
D. 1. Create a project with a standalone Virtual Private Cloud (VPC), assign the Network Admin role to the networking team, and assign the Compute Admin role to the development team.

Answer: A

Explanation:
In this scenario, a large organization has a central team that manages security and networking controls for the entire organization. Developers do not have permissions to make changes to any network or security settings defined by the security and networking team but they are granted permission to create resources such as virtual machines in shared subnets. To facilitate this the organization makes use of a shared VPC (Virtual Private Cloud). A shared VPC allows creation of a VPC network of RFC 1918 IP spaces that associated projects (service projects) can then use. Developers using the associated projects can create VM instances in the shared VPC network spaces. The organization's network and security admins can create subnets, VPNs, and firewall rules usable by all the projects in the VPC network. https://cloud.google.com/iam/docs/job-functions/networking#single_team_manages_security_network_for_organization

NEW QUESTION # 292
For this question, refer to the TerramEarth case study
You analyzed TerramEarth's business requirement to reduce downtime, and found that they can achieve a majority of time saving by reducing customers' wait time for parts You decided to focus on reduction of the 3 weeks aggregate reporting time Which modifications to the company's processes should you recommend?

A. Migrate from FTP to streaming transport, migrate from CSV to binary format, and develop machine learning analysis of metrics.
B. Increase fleet cellular connectivity to 80%, migrate from FTP to streaming transport, and develop machine learning analysis of metrics.
C. Migrate from CSV to binary format, migrate from FTP to SFTP transport, and develop machine learning analysis of metrics.
D. Migrate from FTP to SFTP transport, develop machine learning analysis of metrics, and increase dealer local inventory by a fixed factor.

Answer: B

Explanation:
Explanation
The Avro binary format is the preferred format for loading compressed data. Avro data is faster to load because the data can be read in parallel, even when the data blocks are compressed.
Cloud Storage supports streaming transfers with the gsutil tool or boto library, based on HTTP chunked transfer encoding. Streaming data lets you stream data to and from your Cloud Storage account as soon as it becomes available without requiring that the data be first saved to a separate file. Streaming transfers are useful if you have a process that generates data and you do not want to buffer it locally before uploading it, or if you want to send the result from a computational pipeline directly into Cloud Storage.
References: https://cloud.google.com/storage/docs/streaming
https://cloud.google.com/bigquery/docs/loading-data

NEW QUESTION # 293
......

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