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Google Professional-Cloud-Architect Exam Syllabus Topics:

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

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Google Certified Professional - Cloud Architect (GCP) Sample Questions (Q219-Q224):

NEW QUESTION # 219
Your company has sensitive data in Cloud Storage buckets. Data analysts have Identity Access Management (IAM) permissions to read the buckets. You want to prevent data analysts from retrieving the data in the buckets from outside the office network. What should you do?

A. 1. Create a Cloud Function to remove IAM permissions from the buckets, and another Cloud Function to add IAM permissions to the buckets.
2. Schedule the Cloud Functions with Cloud Scheduler to add permissions at the start of business and remove permissions at the end of business.
B. 1. Create a VPC Service Controls perimeter that includes the projects with the buckets.
2. Create an access level with the CIDR of the office network.
C. 1. Create a Cloud VPN to the office network.
2. Configure Private Google Access for on-premises hosts.
D. 1. Create a firewall rule for all instances in the Virtual Private Cloud (VPC) network for source range.
2. Use the Classless Inter-domain Routing (CIDR) of the office network.

Answer: B

NEW QUESTION # 220
Your company is running its application workloads on Compute Engine. The applications have been deployed in production, acceptance, and development environments. The production environment is business-critical and is used 24/7, while the acceptance and development environments are only critical during office hours.
Your CFO has asked you to optimize these environments to achieve cost savings during idle times . What should you do?

A. Use Instance Schedules to stop the development and acceptance environments after office hours, and start them just before office hours.
B. Deploy the development and acceptance applications on a managed instance group and enable autoscaling.
C. Create a shell script that uses the gcloud command to change the machine type of the development and acceptance instances to a smaller machine type outside of office hours. Schedule the shell script on one of the production instances to automate the task.
D. Use regular Compute Engine instances for the production environment, and use Spot VMs for the acceptance and development environments.

Answer: A

Explanation:
Comprehensive and Detailed Explanation From Exact Extract: The most effective way to achieve significant cost savings for non-production environments that are only needed during business hours is to stop the instances when they are idle. When an instance is stopped, you are only charged for the persistent disks and not for the CPU/RAM.
Instance Schedules are the native, managed Google Cloud feature designed specifically for this purpose:
automating the starting and stopping of Compute Engine instances on a recurring schedule.
* Option D (Use Instance Schedules to stop the development and acceptance environments after office hours, and start them just before office hours) directly addresses the need for cost optimization during idle times with the recommended native solution.
* Option A (Spot VMs) are cheap but can be preempted at any time, which isn ' t suitable for critical during office hours environments.
* Option B (Autoscaling) scales down when demand is low, but typically won ' t scale completely to zero instances, and will still incur minimum running costs.
* Option C (Custom Shell Script) is a manual, non-native solution that requires maintenance and is more complex than the built-in Instance Schedules.
Exact Extract Principle:
From the Google Cloud documentation on Compute Engine Cost Optimization :
" Instance schedules allow you to schedule when Compute Engine virtual machine instances start and stop.
Use instance schedules to automatically start and stop your instances at predefined times. This is a highly recommended practice for cost optimization of non-production environments (development, testing, or staging) that are not needed 24/7, as you are not billed for the instance ' s machine type when it is stopped. " Reference: Google Cloud Compute Engine Instance Schedules Documentation and Compute Engine Pricing
/Cost Optimization Guide.

NEW QUESTION # 221
Case Study: 6 - TerramEarth
Company Overview
TerramEarth manufactures heavy equipment for the mining and agricultural industries. About
80% of their business is from mining and 20% from agriculture. They currently have over 500 dealers and service centers in 100 countries. Their mission is to build products that make their customers more productive.
Solution Concept
There are 20 million TerramEarth vehicles in operation that collect 120 fields of data per second.
Data is stored locally on the vehicle and can be accessed for analysis when a vehicle is serviced.
The data is downloaded via a maintenance port. This same port can be used to adjust operational parameters, allowing the vehicles to be upgraded in the field with new computing modules.
Approximately 200,000 vehicles are connected to a cellular network, allowing TerramEarth to collect data directly. At a rate of 120 fields of data per second with 22 hours of operation per day, TerramEarth collects a total of about 9 TB/day from these connected vehicles.
Existing Technical Environment
TerramEarth's existing architecture is composed of Linux and Windows-based systems that reside in a single U.S. west coast based data center. These systems gzip CSV files from the field and upload via FTP, and place the data in their data warehouse. Because this process takes time, aggregated reports are based on data that is 3 weeks old.
With this data, TerramEarth has been able to preemptively stock replacement parts and reduce unplanned downtime of their vehicles by 60%. However, because the data is stale, some customers are without their vehicles for up to 4 weeks while they wait for replacement parts.
Business Requirements
Decrease unplanned vehicle downtime to less than 1 week.

Support the dealer network with more data on how their customers use their equipment to better

position new products and services
Have the ability to partner with different companies - especially with seed and fertilizer suppliers

in the fast-growing agricultural business - to create compelling joint offerings for their customers.
Technical Requirements
Expand beyond a single datacenter to decrease latency to the American Midwest and east

coast.
Create a backup strategy.

Increase security of data transfer from equipment to the datacenter.

Improve data in the data warehouse.

Use customer and equipment data to anticipate customer needs.

Application 1: Data ingest
A custom Python application reads uploaded datafiles from a single server, writes to the data warehouse.
Compute:
Windows Server 2008 R2

- 16 CPUs
- 128 GB of RAM
- 10 TB local HDD storage
Application 2: Reporting
An off the shelf application that business analysts use to run a daily report to see what equipment needs repair. Only 2 analysts of a team of 10 (5 west coast, 5 east coast) can connect to the reporting application at a time.
Compute:
Off the shelf application. License tied to number of physical CPUs

- Windows Server 2008 R2
- 16 CPUs
- 32 GB of RAM
- 500 GB HDD
Data warehouse:
A single PostgreSQL server

- RedHat Linux
- 64 CPUs
- 128 GB of RAM
- 4x 6TB HDD in RAID 0
Executive Statement
Our competitive advantage has always been in the manufacturing process, with our ability to build better vehicles for lower cost than our competitors. However, new products with different approaches are constantly being developed, and I'm concerned that we lack the skills to undergo the next wave of transformations in our industry. My goals are to build our skills while addressing immediate market needs through incremental innovations.
For this question, refer to the TerramEarth case study. To be compliant with European GDPR regulation, TerramEarth is required to delete data generated from its European customers after a period of 36 months when it contains personal data. In the new architecture, this data will be stored in both Cloud Storage and BigQuery. What should you do?

A. Create a BigQuery table for the European data, and set the table retention period to 36 months.
For Cloud Storage, use gsutil to create a SetStorageClass to NONE action when with an Age condition of 36 months.
B. Create a BigQuery time-partitioned table for the European data, and set the partition period to 36 months. For Cloud Storage, use gsutil to create a SetStorageClass to NONE action with an Age condition of 36 months.
C. Create a BigQuery time-partitioned table for the European data, and set the partition expiration period to 36 months. For Cloud Storage, use gsutil to enable lifecycle management using a DELETE action with an Age condition of 36 months.
D. Create a BigQuery table for the European data, and set the table retention period to 36 months.
For Cloud Storage, use gsutil to enable lifecycle management using a DELETE action with an Age condition of 36 months.

Answer: C

NEW QUESTION # 222
Your company has an application running on App Engine that allows users to upload music files and share them with other people. You want to allow users to upload files directly into Cloud Storage from their browser session. The payload should not be passed through the backend. What should you do?

A. 1. Assign the Cloud Storage WRITER role to users who upload files.
2. Use App Engine default credentials to sign requests against Cloud Storage.
B. 1. Set a CORS configuration in the target Cloud Storage bucket where the base URL of the App Engine application is an allowed origin.
2. Assign the Cloud Storage WRITER role to users who upload files.
C. 1. Use the Cloud Storage Signed URL feature to generate a POST URL.
2. Use App Engine default credentials to sign requests against Cloud Storage.
D. 1. Set a CORS configuration in the target Cloud Storage bucket where the base URL of the App Engine application is an allowed origin.
2. Use the Cloud Storage Signed URL feature to generate a POST URL.

Answer: B

NEW QUESTION # 223
Auditors visit your teams every 12 months and ask to review all the Google Cloud Identity and Access Management (Cloud IAM) policy changes in the previous 12 months. You want to streamline and expedite the analysis and audit process. What should you do?

A. Enable Google Cloud Storage (GCS) log export to audit logs Into a GCS bucket and delegate access to the bucket.
B. Enable Logging export to Google BigQuery and use ACLs and views to scope the data shared with the auditor.
C. Use cloud functions to transfer log entries to Google Cloud SQL and use ACLS and views to limit an auditor's view.
D. Create custom Google Stackdriver alerts and send them to the auditor.

Answer: A

NEW QUESTION # 224
......

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