At Matza Education, each training course is designed to offer practical and relevant knowledge, connecting theory and application in real-life scenarios. Our aim is to prepare professionals for the challenges of the market, strengthening technical and strategic skills in different areas of technology and management.
By taking part in one of our programs, you will have access to up-to-date content, experienced instructors and a results-oriented methodology. Regardless of the format - face-to-face or online - we aim to create a dynamic, accessible and high-impact learning experience.
More than just a course, each training is an opportunity for professional and personal development, helping you to gain certifications, expand your skills and stand out in an increasingly competitive market.
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Application developers who want to create cloud-native applications or redesign applications that will run on Google Cloud Platform.
- Use best practices for application development
- Choose the appropriate data storage option for the application data
- Implement federated identity management
- Develop lightly coupled application components or microservices
- Integrate application components and data sources
- Debug, track and monitor applications
- Perform repeatable deployments with containers and deployment services
- Choosing the appropriate application runtime environment, using Google Kubernetes Engine and then switching to a standalone environment solution with Google App Engine Flex
- Completion of Google Cloud Platform Fundamentals or equivalent experience
- Practical knowledge of Node.js
- Basic proficiency with command line tools and Linux operating system environments
3 days - 24 hours - Live online or in person in São Paulo
- Module 1: Best practices for application development
- Code and environment management
- Design and development of loosely coupled, secure, scalable and reliable application components and microservices
- Continuous integration and delivery
- Rearchitecting applications for the cloud
- Module 2: Google Cloud client libraries, Google Cloud SDK and Google Firebase SDK
- Configuration and use of the Google Cloud client libraries, Google Cloud SDK and Google Firebase SDK
- Lab: Configure the Google client libraries, Google Cloud SDK and Firebase SDK on Linux instances and configure the application credentials
- Module 3: Overview of data storage options
- Overview of the options for storing application data
- Use cases for Google Cloud Storage, Google Cloud Datastore, Cloud Bigtable, Google Cloud SQL and Cloud Spanner
- Module 4: Best practices for using Google Cloud Datastore
- Consultations
- Integrated and composite indices
- Inserting and deleting data (batch operations)
- Transactions
- Error handling
- Mass loading data in the Cloud Datastore with Google Cloud Dataflow
- Lab: Storing application data in the Cloud Datastore
- Module 5: Performing operations on intervals and objects
- Operations that can be performed on ranges and objects
- Consistency model
- Error handling
- Module 6: Best practices for using Google Cloud Storage
- Naming ranges for static sites and other uses
- Naming objects (from an access distribution perspective)
- Performance considerations
- Defining and debugging CORS settings at intervals
- Lab: Storing files in Cloud Storage
- Module 7: Processing authentications and authorizations
- Cloud Identity and Access Management (IAM) roles and service accounts
- User authentication with Firebase Authentication
- User authentication and authorization with Cloud Identity-Aware Proxy
- Lab: Authenticating users with Firebase Authentication
- Module 8: Using Google Cloud Pub/Sub to integrate components of your application
- Topics, editors and subscribers
- Pull and push registrations
- Use cases for Cloud Pub/Sub
- Lab: Developing back-end services to process queued messages
- Module 9: Inserting intelligence into your application
- Overview of pre-trained machine learning APIs, such as Cloud Vision API and Cloud Natural Language Processing API
- Module 10: Using Google Cloud Functions for event-driven processing
- Key concepts such as triggers, background functions, HTTP functions
- Use cases
- Development and implementation of functions
- Log generation, error reporting and monitoring
- Module 11: Managing APIs with Google Cloud Endpoints
- Open API deployment configuration
- Lab: Implementing an API for your application
- Module 12: Deploying applications using Google Cloud, Cloud Build, Google Cloud Container Registry and Google Cloud Deployment Manager
- Creating and storing container images
- Repeatable deployments with configuration and deployment templates
- Lab: Using Deployment Manager to deploy a web application in Google App Engine's flexible test and production environments
- Module 13: Execution environments for your application
- Considerations for choosing execution environments for your application or service:
- Google Compute Engine
- Kubernetes Engine
- Flexible App Engine environment
- Cloud Functions
- Cloud Dataflow
- Lab: How to deploy your application in the flexible App Engine environment
- Considerations for choosing execution environments for your application or service:
- Module 14: Debugging, monitoring and performance tuning using Google Stackdriver
- Stackdriver Debugger
- Stackdriver Error Reporting
- Lab: How to debug application errors with Stackdriver Debugger and Error Reporting
- Stackdriver Logging
- Main concepts related to Stackdriver Trace and Stackdriver Monitoring
- Lab: use Stackdriver Monitoring and Stackdriver Trace to trace a request to services, observe and optimize performance