Oreilly – Google Cloud Platform Professional Cloud Architect 2023-1

در تاریخ: 1403/02/26 3:40:40

توضیحات

دوره Google Cloud Platform Professional Cloud Architect. این دوره آموزشی ویدیویی جامع، با بیش از 10 ساعت محتوا، شما را برای قبولی در آزمون معمار حرفه‌ای کلود گوگل (Cloud Platform Professional Cloud Architect) کاملا آماده می‌کند. دوره مذکور، یک منبع آموزشی کامل برای کمک به ارتقاء مهارت‌های مورد نیاز شما در مسیر قبولی در آزمون است. تمامی سرفصل‌های آزمون را پوشش می‌دهد و به شما می‌آموزد که چگونه یک معماری راه‌حل ابری مستحکم بر روی پلتفرم Google Cloud طراحی کنید. ویکتور دانتاس، مدرس، نویسنده و متخصص کلود، با استفاده از دموی هدفمند، تحلیل نمونه سوالات امتحانی و بررسی نمونه مطالعات موردی، اطمینان حاصل می‌کند که شما کاملا برای آزمون آماده هستید. این دوره آموزشی به موارد زیر می‌پردازد:

تضمین قابلیت اطمینان راه‌حل و عملیات
طراحی برای امنیت و انطباق
مدیریت و تامین زیرساخت راه‌حل ابری
تجزیه و تحلیل و بهینه‌سازی فرآیندهای فنی و تجاری با Google Cloud

علاوه بر این، بهترین شیوه‌ها برای استقرارهای موفق و نحوه طراحی منابع شبکه، ذخیره‌سازی و محاسبات را فرا خواهید گرفت.

آنچه فرا خواهید گرفت:

طراحی و برنامه ریزی معماری راه‌حل ابری
مدیریت و تامین زیرساخت راه‌حل
طراحی برای امنیت و انطباق
تجزیه و تحلیل و بهینه‌سازی فرآیندهای فنی و تجاری
مدیریت پیاده‌سازی
تضمین قابلیت اطمینان راه‌حل و عملیات

این دوره مناسب افرادی است که:

متخصصان IT با حداقل ۳ سال تجربه در صنعت، به همراه حداقل یک سال سابقه طراحی و مدیریت راه‌حل با استفاده از Google Cloud
معماران راه‌حل یا کلود بدون تجربه با Google Cloud اما با تجربه در سایر پلتفرم‌های ابری
مهندسان کلود که به دنبال تعمیق مهارت‌های خود در طراحی راه‌حل‌های Google Cloud هستند

مشخصات دوره

ناشر: Oreilly
مدرس: Victor Dantas
سطح آموزش: مبتدی تا پیشرفته
مدت زمان آموزش: 10 ساعت 5 دقیقه

سرفصل های دوره

Introduction
1. Google Cloud Platform Professional Cloud Architect: Introduction
Module 1: Professional Cloud Architect Certification overview
1. Module introduction
Lesson 1: Exam Overview
1. Learning objectives
2. 1.1 Exam Guide
3. 1.2 Exam Case Study: Medical Software
4. 1.3 Exam Case Study: Live Streaming with Predictive Modeling
5. 1.4 Exam Case Study: Industrial IoT
6. 1.5 Exam Case Study: Mobile Gaming Platforms
Module 2: Designing and planning a cloud solution architecture
1. Module introduction
Lesson 2: Designing a solution infrastructure that meets business requirements
1. Learning objectives
2. 2.1 Business use cases and strategies
3. 2.2 Success measurements
4. 2.3 Design decision trade-offs
5. 2.4 Build, buy, modify, or deprecate
6. 2.5 Integration with external systems
7. 2.6 Movement of data
8. 2.7 Supporting the application design
9. 2.8 Cost optimization
10. 2.9 Compliance on GCP
11. 2.10 Questions breakdown
Lesson 3: Designing a solution infrastructure that meets technical requirements
1. Learning objectives
2. 3.1 Designing for high availability and failover
3. 3.2 Case Study: Designing for high availability and failover
4. 3.3 Elasticity of cloud resources, quotas and limits
5. 3.4 Designing for scalability to meet growth requirements
6. 3.5 Designing for performance
7. 3.6 Case Study: Designing for scalability
8. 3.7 Questions breakdown
Lesson 4: Designing network, storage, and compute resources
1. Learning objectives
2. 4.1 Integration with on-premises
3. 4.2 Multicloud environments
4. 4.3 Case Study: Integration with on-premises
5. 4.4 Cloud-native networking
6. 4.5 Choosing data processing technologies
7. 4.6 Choosing appropriate storage types
8. 4.7 Choosing compute resources
9. 4.8 Mapping compute needs to platform products
10. 4.9 Questions breakdown
Lesson 5: Creating a migration plan
1. Learning objectives
2. 5.1 Integrating solutions with existing systems
3. 5.2 Migrating systems and data
4. 5.3 Software license mapping
5. 5.4 Network planning
6. 5.5 Testing and proofs of concept
7. 5.6 Dependency management
8. 5.7 Envisioning future solution improvements
9. 5.8 Questions breakdown
Module 3: Managing and provisioning a solution infrastructure
1. Module introduction
Lesson 6: Configuring network topologies
1. Learning objectives
2. 6.1 Hybrid and multicloud networking
3. 6.2 Securing networks
4. 6.3 Demo: Securing networks
5. 6.4 Common network topologies
6. 6.5 Lab: configuring and securing a network
7. 6.6 Questions breakdown
Lesson 7: Configuring storage systems
1. Learning objectives
2. 7.1 Data storage allocation
3. 7.2 Data processing and compute provisioning
4. 7.3 Demo: Data processing and compute provisioning
5. 7.4 Data security and access management
6. 7.5 Network configuration for data transfer and latency
7. 7.6 Data retention and data lifecycle management
8. 7.7 Demo: Data retention and data lifecycle management
9. 7.8 Data growth planning
10. 7.9 Questions breakdown
Lesson 8: Configuring compute systems
1. Learning objectives
2. 8.1 Compute resource provisioning
3. 8.2 Compute volatility configuration
4. 8.3 Demo: Configuring preemptible instances
5. 8.4 Network configuration for compute resources
6. 8.5 Compute infrastructure orchestration
7. 8.6 Resource configuration and patch management
8. 8.7 Container orchestration with Kubernetes (part 1)
9. 8.8 Container orchestration with Kubernetes (part 2)
10. 8.9 Lab: Container orchestration with Kubernetes
11. 8.10 Questions breakdown
Module 4: Designing for security and compliance
1. Module introduction
Lesson 9: Designing for security
1. Learning objectives
2. 9.1 Identity and Access Management (IAM)
3. 9.2 Resource hierarchy on GCP
4. 9.3 Data security at rest
5. 9.4 Data security in transit
6. 9.5 Case Study: Data security in transit
7. 9.6 Separation of Duties (SoD)
8. 9.7 Security controls
9. 9.8 Managing your own encryption keys
10. 9.9 Remote access
11. 9.10 Questions breakdown
Lesson 10: Designing for compliance
1. Learning objectives
2. 10.1 Legislation considerations
3. 10.2 Commercial considerations
4. 10.3 Industry certifications
5. 10.4 Audits and logs
6. 10.5 Questions breakdown
Module 5: Analyzing and optimizing technical and business processes
1. Module introduction
Lesson 11: Analyzing and defining technical processes
1. Learning objectives
2. 11.1 Software development life cycle (SDLC)
3. 11.2 Continuous integration / continuous deployment (CI/CD)
4. 11.3 Troubleshooting root cause analysis best practices
5. 11.4 Testing and validation of software and infrastructure
6. 11.5 Service catalog and provisioning
7. 11.6 Business continuity and disaster recovery
8. 11.7 Case study: Infrastructure-as-Code
9. 11.8 Questions breakdown
Lesson 12: Analyzing and defining business processes
1. Learning objectives
2. 12.1 Stakeholder management
3. 12.2 Change management
4. 12.3 Team assessment and skills readiness
5. 12.4 Decision-making processes
6. 12.5 Customer success management
7. 12.6 Cost and resource optimization
8. 12.7 Developing procedures to ensure reliability of solutions
9. 12.8 Questions breakdown
Module 6: Managing implementation
1. Module introduction
Lesson 13: Best practices for successful deployments
1. Learning objectives
2. 13.1 Application development
3. 13.2 API best practices
4. 13.3 Case study: API design
5. 13.4 Testing frameworks
6. 13.5 Migration and management tooling
7. 13.6 Interacting with Google Cloud programmatically
8. 13.7 Demo: Interacting with Google Cloud programmatically
9. 13.8 Questions breakdown
Module 7: Ensuring solution and operations reliability
1. Module introduction
Lesson 14: Monitoring, logging, profiling, and alerting
1. Learning objectives
2. 14.1 Monitoring infrastructure and applications
3. 14.2 Logging
4. 14.3 Demo: Monitoring charts and dashboards
5. 14.4 Debugging applications
6. 14.5 Profiling applications
7. 14.6 Monitoring alerts and incidence response
8. 14.7 Lab: Monitoring alerts
9. 14.8 Questions breakdown
Lesson 15: Deployment and release management
1. Learning objectives
2. 15.1 Automating infrastructure and application deployments
3. 15.2 Demo: Automating infrastructure deployment
4. 15.3 Testing and validating deployments
5. 15.4 Assisting with the support of deployed solutions
6. 15.5 Lab: Automating application deployment
7. 15.6 Questions breakdown
Summary
1. Google Cloud Platform Professional Cloud Architect: Summary

پیشنیاز های دوره

Knowledge of cloud infrastructure foundations: storage, compute, databases, networking, and security.
Basic familiarity with the Google Cloud Platform.
Foundational system design knowledge.
Basic proficiency in one programming language, although not required, is recommended.