Deploying and Managing Windows Workloads on Google Cloud

Duración del curso

7 horas

Lugar de impartición

Madrid / Online

Modalidad

Aula Virtual, Presencial

Fecha de inicio

Próximamente

Calendario

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Acerca del curso

Learn how to design, develop, and deploy applications that seamlessly integrate components from the Google Cloud ecosystem. This course uses lectures, demos, and hands-on labs to show you how to use Google Cloud services and pretrained machine learning APIs to build secure, scalable, and intelligent cloud-native applications.

Use best practices for application development
Choose the appropriate data storage option for application data
Implement federated identity management
Develop loosely coupled application components or
microservices
Integrate application components and data sources
Debug, trace, and monitor applications
Perform repeatable deployments with containers and
deployment services
Choose the appropriate application runtime environment

Completed Google Cloud Fundamentals: Core Infrastructure or have equivalent experience
Working knowledge of Node.js, Python, or Java
Basic proficiency with command-line tools and Linux operating system
environments

Modulo 1: Best Practices for Application Development

Code and environment management
Design and development of secure, scalable, reliable, loosely coupled application components and microservices
Continuous integration and delivery
Re-architecting applications for the cloud

Modulo 2: Getting Started with Google Cloud Development

Overview of Google Cloud services for apps and scripts:
- Google Cloud APIs
- Cloud SDK
- Cloud Client Libraries
- Cloud Shell
- Cloud Code

Modulo 3: Overview of Data Storage Options

Overview of options to store application data
Use cases for Cloud Storage, Firestore, Cloud Bigtable, Cloud SQL, and Cloud Spanner
Demo: Connecting Securely to a Cloud SQL Database

Modulo 4: Best Practices for Using Datastore

Queries
Built-in and composite indexes
Inserting and deleting data (batch operations)
Transactions
Error handling

Modulo 5: Performing Operations on Buckets and Objects

Cloud Storage concepts
Consistency model
Demo: Explore Cloud Storage
Request endpoints
Composite objects and parallel uploads
Truncated exponential backoff
Demo: Enable CORS Configuration in Cloud Storage

Modulo 6: Best Practices for Using Cloud Storage

Naming buckets for static websites and other uses
Naming objects (from an access distribution perspective)
Performance considerations
Lab: Storing Image and Video Files in Cloud Storage

Modulo 7: Handling Authentication and Authorization

Identity and Access Management (IAM) roles and service accounts
User authentication by using Firebase Authentication
User authentication and authorization by using Identity-Aware Proxy
Lab: Adding User Authentication to your Application

Modulo 8: Using Pub/Sub to Integrate Components of Your Application

Topics, publishers, and subscribers
Pull and push subscriptions
Use cases for Pub/Sub
Lab: Developing a Backend Service

Modulo 9: Adding Intelligence to Your Application

Overview of pre-trained machine learning APIs such as the Vision API and the Cloud Natural Language Processing API

Modulo 10: Using Cloud Functions for Event-Driven Processing

Key concepts such as triggers, background functions, HTTP functions
Use cases
Developing and deploying functions
Logging, error reporting, and monitoring
Demo: Invoke Cloud Functions Through Direct Request-response
Lab: Processing Pub/Sub Data using Cloud Functions

Modulo 11: Managing APIs with Cloud Endpoints

Open API deployment configuration
Lab: Deploying an API for the Quiz Application

Modulo 12: Deploying Applications

Creating and storing container images
Repeatable deployments with deployment configuration and templates
Demo: Exploring Cloud Build and Cloud Container Registry
Lab: Deploying the Application into Kubernetes Engine

Modulo 13: Compute Options for Your Application

Considerations for choosing a compute option for your application or service:
- Compute Engine
- Google Kubernetes Engine (GKE)
- Cloud Run
- Cloud Functions
Platform comparisons
Comparing App Engine and Cloud Run

Modulo 14: Debugging, Monitoring, and Tuning Performance

Google Cloud’s operations suite
Managing performance
Lab: Debugging Application Errors
Logging
Monitoring and tuning performance
Identifying and troubleshooting performance issues
Lab: Harnessing Cloud Trace and Cloud Monitoring

Documentación Oficial de Google Cloud - Deploying and Managing Windows Workloads on Google Cloud

Formador Certificado por GCP
Más de 5 años de experiencia profesional
Más de 4 años de experiencia docente
Profesional activo en empresas del sector IT

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