Google Cloud Fundamentals: Core Infrastructure | Pós-laboral
Virtual Learning: 550€ + IVA
REF: GCF-CIpl Catálogo: Google Cloud, Formação Pós Laboral Área: Fundamentals, Pós-laboral
Duração:
2 dias (3h/dia)
Próxima Data:
Consulte-nos
Local:
Online
Descrição
Google Cloud Fundamentals: Core Infrastructure introduces important concepts and terminology for working with Google Cloud. Through videos and hands-on labs, this course presents and compares many of Google Cloud's computing and storage services, along with important resource and policy management tools.
This course is part of the following Certifications:
- Google Cloud Certified Associate Cloud Engineer (ACE)
- Google Cloud Certified Professional Cloud Network Engineer (PCNE)
- Google Cloud Certified Professional Cloud Architect (PCA)
- Google Cloud Certified Professional Cloud Developer (PCD)
- Google Cloud Certified Professional Cloud Security Engineer (PCSE)
*PVP por participante. A realização do curso nas datas apresentadas está sujeita a um quórum mínimo de inscrições.
Destinatários
- Individuals planning to deploy applications and create application environments on Google Cloud.
- Developers, systems operations professionals, and solution architects getting started with Google Cloud.
- Executives and business decision makers evaluating the potential of Google Cloud to address their business needs.
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Área: Google CloudFormação Pós Laboral
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Certificação Associada: This course is part of Google Cloud Certified: ACE; PCNE; PCA; PCD; PCSE
Programa:
Module 1: Introducing Google Cloud
This section identifies some of the key benefits of using Google Cloud. It's here that we introduce the components of the Google network infrastructure, and explore the differences between infrastructure as a service (IaaS) and platform as a service (PaaS).
Lessons:
- Cloud computing overview
- IaaS and PaaS
- The Google Cloud network
- Environmental impact
- Security
- Open source ecosystems
- Pricing and billing
Module 2: Resources and Access in the Cloud
This section explores how resources get organized with projects, and how access to those resources gets shared with the right part of a workforce through a tool called Identity and Access Management (IAM). It's also in this section that we identify different ways to interact with Google Cloud.
Lessons:
- Google Cloud resource hierarchy
- Identity and Access Management (IAM)
- Service accounts
- Cloud Identity
- Interacting with Google Cloud
- Lab: Google Cloud Fundamentals: Getting Started with Cloud Marketplace
Module 3: Virtual Machines and Networks in the Cloud
This section of the course explores how Google Compute Engine works, with a focus on virtual networking.
Lessons:
- Virtual Private Cloud networking
- Compute Engine
- Scaling virtual machines
- Important VPC compatibilities
- Cloud Load Balancing
- Cloud DNS and Cloud CDN
- Connecting networks to Google VPC
- Lab: Getting Started with VPC Networking and Google Compute Engine
Module 4: Storage in the Cloud
his section of the course showcases five core Google Cloud storage products: Cloud Storage, Bigtable, Cloud SQL, Spanner, and Firestore.
Lessons:
- Google Cloud storage options
- Cloud Storage
- Cloud Storage: Storage classes and data transfer
- Cloud SQL
- Spanner
- Firestore
- Bigtable
- Comparing storage options
- Lab: Google Cloud Fundamentals: Getting Started with Cloud Storage and Cloud SQL
Module 5: Containers in the Cloud
This section of the course explores containers and how they can be managed with Kubernetes and Google Kubernetes Engine.
Lessons:
- Introduction to containers
- Kubernetes
- Google Kubernetes Engine
Module 6: Applications in the Cloud
The focus of this section of the course is developing applications in the cloud. It's here that we'll explore Cloud Run and Cloud Run functions.
Lessons:
- Cloud Run
- Development in the cloud
- Lab: Hello Cloud Run
Module 7: Prompt Engineering
This section looks at generative AI tools, how they work. We'll explore how to combine Google Cloud knowledge with prompt engineering to improve Gemini responses.
Lessons:
- Prompt Engineering
Pré-requisitos:
Familiarity with application development, systems operations, Linux operating systems, and data analytics/machine learning is helpful in understanding the technologies covered.
Partilha:
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