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Google Professional-Cloud-Architect Exam Syllabus Topics:

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

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Google Certified Professional - Cloud Architect (GCP) Sample Questions (Q113-Q118):

NEW QUESTION # 113
A few days after JencoMart migrates the user credentials database to Google Cloud Platform and shuts
down the old server, the new database server stops responding to SSH connections. It is still serving
database requests to the application servers correctly.
What three steps should you take to diagnose the problem? Choose 3 answers.

Answer: C,E,F

Explanation:
Explanation/Reference:
Explanation:
D: Handling "Unable to connect on port 22" error message
Possible causes include:
There is no firewall rule allowing SSH access on the port. SSH access on port 22 is enabled on all

Compute Engine instances by default. If you have disabled access, SSH from the Browser will not
work. If you run sshd on a port other than 22, you need to enable the access to that port with a custom
firewall rule.
The firewall rule allowing SSH access is enabled, but is not configured to allow connections from GCP

Console services. Source IP addresses for browser-based SSH sessions are dynamically allocated by
GCP Console and can vary from session to session.
F: Handling "Could not connect, retrying..." error
You can verify that the daemon is running by navigating to the serial console output page and looking for
output lines prefixed with the accounts-from-metadata: string. If you are using a standard image but you do
not see these output prefixes in the serial console output, the daemon might be stopped. Reboot the
instance to restart the daemon.
References:
https://cloud.google.com/compute/docs/ssh-in-browser
https://cloud.google.com/compute/docs/ssh-in-browser


NEW QUESTION # 114
You are deploying a PHP App Engine Standard service with SQL as the backend. You want to minimize the number of queries to the database.
What should you do?

Answer: B

Explanation:
https://cloud.google.com/appengine/docs/standard/php/memcache/using


NEW QUESTION # 115
Your agricultural division is experimenting with fully autonomous vehicles. You want your architecture to promote strong security during vehicle operation.
Which two architectures should you consider? (Choose two.)

Answer: D,F


NEW QUESTION # 116
For this question, refer to the Helicopter Racing League (HRL) case study. Your team is in charge of creating a payment card data vault for card numbers used to bill tens of thousands of viewers, merchandise consumers, and season ticket holders. You need to implement a custom card tokenization service that meets the following requirements:
* It must provide low latency at minimal cost.
* It must be able to identify duplicate credit cards and must not store plaintext card numbers.
* It should support annual key rotation.
Which storage approach should you adopt for your tokenization service?

Answer: D

Explanation:
Topic 10, EHR Health Care
Company overview
EHR Healthcare is a leading provider of electronic health record software to the medical industry. EHR Healthcare provides their software as a service to multi-national medical offices, hospitals, and insurance providers.
Solution concept
Due to rapid changes in the healthcare and insurance industry, EHR Healthcare's business has been growing exponentially year over year. They need to be able to scale their environment, adapt their disaster recovery plan, and roll out new continuous deployment capabilities to update their software at a fast pace. Google Cloud has been chosen to replace their current colocation facilities.
Existing technical environment
EHR's software is currently hosted in multiple colocation facilities. The lease on one of the data centers is about to expire.
Customer-facing applications are web-based, and many have recently been containerized to run on a group of Kubernetes clusters. Data is stored in a mixture of relational and NoSQL databases (MySQL, MS SQL Server, Redis, and MongoDB).
EHR is hosting several legacy file- and API-based integrations with insurance providers on-premises. These systems are scheduled to be replaced over the next several years. There is no plan to upgrade or move these systems at the current time.
Users are managed via Microsoft Active Directory. Monitoring is currently being done via various open source tools. Alerts are sent via email and are often ignored.
Business requirements
* On-board new insurance providers as quickly as possible.
* Provide a minimum 99.9% availability for all customer-facing systems.
* Provide centralized visibility and proactive action on system performance and usage.
* Increase ability to provide insights into healthcare trends.
* Reduce latency to all customers.
* Maintain regulatory compliance.
* Decrease infrastructure administration costs.
* Make predictions and generate reports on industry trends based on provider data.
Technical requirements
* Maintain legacy interfaces to insurance providers with connectivity to both on-premises systems and cloud providers.
* Provide a consistent way to manage customer-facing applications that are container-based.
* Provide a secure and high-performance connection between on-premises systems and Google Cloud.
* Provide consistent logging, log retention, monitoring, and alerting capabilities.
* Maintain and manage multiple container-based environments.
* Dynamically scale and provision new environments.
* Create interfaces to ingest and process data from new providers.
Executive statement
Our on-premises strategy has worked for years but has required a major investment of time and money in training our team on distinctly different systems, managing similar but separate environments, and responding to outages. Many of these outages have been a result of misconfigured systems, inadequate capacity to manage spikes in traffic, and inconsistent monitoring practices. We want to use Google Cloud to leverage a scalable, resilient platform that can span multiple environments seamlessly and provide a consistent and stable user experience that positions us for future growth.


NEW QUESTION # 117
Your company just finished a rapid lift and shift to Google Compute Engine for your compute needs. You have another 9 months to design and deploy a more cloud-native solution. Specifically, you want a system that is no-ops and auto-scaling. Which two compute products should you choose? Choose 2 answers

Answer: B,D

Explanation:
B: With Container Engine, Google will automatically deploy your cluster for you, update, patch, secure the nodes.
Kubernetes Engine's cluster autoscaler automatically resizes clusters based on the demands of the workloads you want to run.
C: Solutions like Datastore, BigQuery, AppEngine, etc are truly NoOps.
App Engine by default scales the number of instances running up and down to match the load, thus providing consistent performance for your app at all times while minimizing idle instances and thus reducing cost.
Note: At a high level, NoOps means that there is no infrastructure to build out and manage during usage of the platform. Typically, the compromise you make with NoOps is that you lose control of the underlying infrastructure.


NEW QUESTION # 118
......

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