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Google Professional-Cloud-Architect Exam Syllabus Topics:

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

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Google Certified Professional - Cloud Architect (GCP) Sample Questions (Q298-Q303):

NEW QUESTION # 298
Your company has an application deployed on Anthos clusters (formerly Anthos GKE) that is running multiple microservices. The cluster has both Anthos Service Mesh and Anthos Config Management configured. End users inform you that the application is responding very slowly. You want to identify the microservice that is causing the delay. What should you do?

Answer: C

Explanation:
The Anthos Service Mesh pages in the Google Cloud Console provide both summary and in-depth metrics, charts, and graphs that enable you to observe service behavior. You can monitor the overall health of your services, or drill down on a specific service to set a service level objective (SLO) or troubleshoot an issue.
https://cloud.google.com/service-mesh/docs/observability/explore-dashboard
https://cloud.google.com/anthos/service-mesh


NEW QUESTION # 299
Your team is developing a web application that will be deployed on Google Kubernetes Engine (GKE). Your CTO expects a successful launch and you need to ensure your application can handle the expected load of tens of thousands of users. You want to test the current deployment to ensure the latency of your application stays below a certain threshold. What should you do?

Answer: A

Explanation:
The question focuses more on the current infra and ensuring if the current setup will ensure a latency target. An only a load test can do that. Autoscaling is no need of the hour and may require in the future and that totally depends on the test results. It might be an overkill to have everything in advance even App is fine with current configs.


NEW QUESTION # 300
Your company's test suite is a custom C++ application that runs tests throughout each day on Linux virtual machines. The full test suite takes several hours to complete, running on a limited number of on premises servers reserved for testing. Your company wants to move the testing infrastructure to the cloud, to reduce the amount of time it takes to fully test a change to the system, while changing the tests as little as possible.
Which cloud infrastructure should you recommend?

Answer: D

Explanation:
https://cloud.google.com/compute/docs/instance-groups/
Google Compute Engine enables users to launch virtual machines (VMs) on demand. VMs can be launched from the standard images or custom images created by users.
Managed instance groups offer autoscaling capabilities that allow you to automatically add or remove instances from a managed instance group based on increases or decreases in load. Autoscaling helps your applications gracefully handle increases in traffic and reduces cost when the need for resources is lower.


NEW QUESTION # 301
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?

Answer: D

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 # 302
For this question, refer to the TerramEarth case study.
TerramEarth has equipped unconnected trucks with servers and sensors to collet telemetry data. Next year they want to use the data to train machine learning models. They want to store this data in the cloud while reducing costs. What should they do?

Answer: A

Explanation:
Coldline Storage is the best choice for data that you plan to access at most once a year, due to its slightly lower availability, 90-day minimum storage duration, costs for data access, and higher per-operation costs. For example:
Cold Data Storage - Infrequently accessed data, such as data stored for legal or regulatory reasons, can be stored at low cost as Coldline Storage, and be available when you need it.
Disaster recovery - In the event of a disaster recovery event, recovery time is key. Cloud Storage provides low latency access to data stored as Coldline Storage.
References:
https://cloud.google.com/storage/docs/storage-classes
Topic 3, JencoMart Case Study
Company Overview
JencoMart is a global retailer with over 10,000 stores in 16 countries. The stores carry a range of goods, such as groceries, tires, and jewelry. One of the company's core values is excellent customer service. In addition, they recently introduced an environmental policy to reduce their carbon output by 50% over the next 5 years.
Company Background
JencoMart started as a general store in 1931, and has grown into one of the world's leading brands known for great value and customer service. Over time, the company transitioned from only physical stores to a stores and online hybrid model, with 25% of sales online. Currently, JencoMart has little presence in Asia, but considers that market key for future growth.
Solution Concept
JencoMart wants to migrate several critical applications to the cloud but has not completed a technical review to determine their suitability for the cloud and the engineering required for migration. They currently host all of these applications on infrastructure that is at its end of life and is no longer supported.
Existing Technical Environment
JencoMart hosts all of its applications in 4 data centers: 3 in North American and 1 in Europe, most applications are dual-homed.
JencoMart understands the dependencies and resource usage metrics of their on-premises architecture.
Application Customer loyalty portal
LAMP (Linux, Apache, MySQL and PHP) application served from the two JencoMart-owned U.S. data centers.
Database
* Oracle Database stores user profiles
* 20 TB
* Complex table structure
* Well maintained, clean data
* Strong backup strategy
* PostgreSQL database stores user credentials
* Single-homed in US West
o No redundancy
o Backed up every 12 hours
* 100% uptime service level agreement (SLA)
* Authenticates all users
Compute
* 30 machines in US West Coast, each machine has:
o Twin, dual core CPUs
o 32GB of RAM
* Twin 250 GB HDD (RAID 1)
* 20 machines in US East Coast, each machine has:
o Single dual-core CPU
o 24 GB of RAM
* Twin 250 GB HDD (RAID 1)
Storage
* Access to shared 100 TB SAN in each location
* Tape backup every week
Business Requirements
* Optimize for capacity during peak periods and value during off-peak periods
* Guarantee service availably and support
* Reduce on-premises footprint and associated financial and environmental impact.
* Move to outsourcing model to avoid large upfront costs associated with infrastructure purchase
* Expand services into Asia.
Technical Requirements
* Assess key application for cloud suitability.
* Modify application for the cloud.
* Move applications to a new infrastructure.
* Leverage managed services wherever feasible
* Sunset 20% of capacity in existing data centers
* Decrease latency in Asia
CEO Statement
JencoMart will continue to develop personal relationships with our customers as more people access the web. The future of our retail business is in the global market and the connection between online and in-store experiences. As a large global company, we also have a responsibility to the environment through 'green' initiatives and polices.
CTO Statement
The challenges of operating data centers prevents focus on key technologies critical to our long-term success. Migrating our data services to a public cloud infrastructure will allow us to focus on big data and machine learning to improve our service customers.
CFO Statement
Since its founding JencoMart has invested heavily in our data services infrastructure. However, because of changing market trends, we need to outsource our infrastructure to ensure our long-term success. This model will allow us to respond to increasing customer demand during peak and reduce costs.


NEW QUESTION # 303
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