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Google Professional-Cloud-Architect Exam Syllabus Topics:

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

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Google Certified Professional - Cloud Architect (GCP) Sample Questions (Q48-Q53):

NEW QUESTION # 48
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-1 type machines.
2) Build a Docker image from the production branch with all of the dependencies, and tag it with the
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 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.
C. Perform the following:
1) Create a Kubernetes Engine (GKE) 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.
D. 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.

Answer: C

Explanation:
Reference:
https://cloud.google.com/compute/docs/instance-templates

NEW QUESTION # 49
Your company is building a new architecture to support its data-centric business focus. You are responsible for setting up the network. Your company's mobile and web-facing applications will be deployed on-premises, and all data analysis will be conducted in GCP. The plan is to process and load 7 years of archived .csv files totaling
900 TB of data and then continue loading 10 TB of data daily. You currently have an existing 100-MB internet connection.
What actions will meet your company's needs?

A. Lease a Transfer Appliance, upload archived files to it, and send it to Google to transfer archived data to Cloud Storage. Establish a connection with Google using a Dedicated Interconnect or Direct Peering connection and use it to upload files daily.
B. Compress and upload both archived files and files uploaded daily using the gsutil -moption.
C. Lease a Transfer Appliance, upload archived files to it, and send it to Google to transfer archived data to Cloud Storage. Establish one Cloud VPN Tunnel to VPC networks over the public internet, and compress and upload files daily using the gsutil-m option.
D. Lease a Transfer Appliance, upload archived files to it, and send it to Google to transfer archived data to Cloud Storage. Establish a Cloud VPN Tunnel to VPC networks over the public internet, and compress and upload files daily.

Answer: A

Explanation:
Explanation/Reference:

NEW QUESTION # 50
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 dat a. 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 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.
D. 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.

Answer: D

Explanation:
Reference:
https://cloud.google.com/bigquery/docs/managing-partitioned-tables#partition-expiration
https://cloud.google.com/storage/docs/lifecycle
Topic 5, Mountkrik Games Case 2
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.

NEW QUESTION # 51
Case Study: 4 - Dress4Win case study
Company Overview
Dress4win is a web-based company that helps their users organize and manage their personal wardrobe using a website and mobile application. The company also cultivates an active social network that connects their users with designers and retailers. They monetize their services through advertising, e-commerce, referrals, and a freemium app model.
Company Background
Dress4win's application has grown from a few servers in the founder's garage to several hundred servers and appliances in a colocated data center. However, the capacity of their infrastructure is now insufficient for the application's rapid growth. Because of this growth and the company's desire to innovate faster, Dress4win is committing to a full migration to a public cloud.
Solution Concept
For the first phase of their migration to the cloud, Dress4win is considering moving their development and test environments. They are also considering building a disaster recovery site, because their current infrastructure is at a single location. They are not sure which components of their architecture they can migrate as is and which components they need to change before migrating them.
Existing Technical Environment
The Dress4win application is served out of a single data center location.
Databases:
MySQL - user data, inventory, static data
* Redis - metadata, social graph, caching
* Application servers:
Tomcat - Java micro-services
* Nginx - static content
* Apache Beam - Batch processing
* Storage appliances:
iSCSI for VM hosts
* Fiber channel SAN - MySQL databases
* NAS - image storage, logs, backups
* Apache Hadoop/Spark servers:
Data analysis
* Real-time trending calculations
* MQ servers:
Messaging
* Social notifications
* Events
* Miscellaneous servers:
Jenkins, monitoring, bastion hosts, security scanners
* Business Requirements
* Build a reliable and reproducible environment with scaled parity of production. Improve security by defining and adhering to a set of security and Identity and Access Management (IAM) best practices for cloud.
Improve business agility and speed of innovation through rapid provisioning of new resources.
Analyze and optimize architecture for performance in the cloud. Migrate fully to the cloud if all other requirements are met.
Technical Requirements
Evaluate and choose an automation framework for provisioning resources in cloud. Support failover of the production environment to cloud during an emergency. Identify production services that can migrate to cloud to save capacity.
Use managed services whenever possible.
Encrypt data on the wire and at rest.
Support multiple VPN connections between the production data center and cloud environment.
CEO Statement
Our investors are concerned about our ability to scale and contain costs with our current infrastructure. They are also concerned that a new competitor could use a public cloud platform to offset their up-front investment and freeing them to focus on developing better features.
CTO Statement
We have invested heavily in the current infrastructure, but much of the equipment is approaching the end of its useful life. We are consistently waiting weeks for new gear to be racked before we can start new projects. Our traffic patterns are highest in the mornings and weekend evenings; during other times, 80% of our capacity is sitting idle.
CFO Statement
Our capital expenditure is now exceeding our quarterly projections. Migrating to the cloud will likely cause an initial increase in spending, but we expect to fully transition before our next hardware refresh cycle. Our total cost of ownership (TCO) analysis over the next 5 years puts a cloud strategy between 30 to 50% lower than our current model.
For this question, refer to the Dress4Win case study.
Dress4Win has asked you for advice on how to migrate their on-premises MySQL deployment to the cloud. They want to minimize downtime and performance impact to their on-premises solution during the migration. Which approach should you recommend?

A. Setup a MySQL replica server/slave in the cloud environment, and configure it for asynchronous replication from the MySQL master server on-premises until cutover.
B. Create a new MySQL cluster in the cloud, configure applications to begin writing to both on- premises and cloud MySQL masters, and destroy the original cluster at cutover.
C. Create a dump of the MySQL replica server into the cloud environment, load it into: Google Cloud Datastore, and configure applications to read/write to Cloud Datastore at cutover.
D. Create a dump of the on-premises MySQL master server, and then shut it down, upload it to the cloud environment, and load into a new MySQL cluster.

Answer: A

NEW QUESTION # 52
Your organization wants to control IAM policies for different departments independently, but centrally.
Which approach should you take?

A. Multiple Organizations, one for each department
B. A single Organization with Folder for each department
C. A single Organization with multiple projects, each with a central owner
D. Multiple Organizations with multiple Folders

Answer: B

Explanation:
Explanation
Folders are nodes in the Cloud Platform Resource Hierarchy. A folder can contain projects, other folders, or a combination of both. You can use folders to group projects under an organization in a hierarchy. For example, your organization might contain multiple departments, each with its own set of GCP resources. Folders allow you to group these resources on a per-department basis. Folders are used to group resources that share common IAM policies. While a folder can contain multiple folders or resources, a given folder or resource can have exactly one parent.
References: https://cloud.google.com/resource-manager/docs/creating-managing-folders

NEW QUESTION # 53
......

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