Developing Applications with GCP Overview
This Developing Applications with Google Cloud Platform (GCP) training course teaches application developers how to design, develop, and deploy applications that seamlessly integrate components from the Google Cloud ecosystem. Participants learn how to use GCP services and pre-trained machine learning APIs to build secure, scalable, and intelligent cloud-native applications.
Location and Pricing
This course is taught as a private, live online class for teams of 3 or more. All our courses are hands-on, instructor-led, and tailored to fit your group’s goals and needs. Most Accelebrate classes can be flexibly scheduled for your group, including delivery in half-day segments across a week or set of weeks. To receive a customized proposal and price quote for online corporate training, please contact us.
In addition, some courses are available as live, instructor-led training from one of our partners.
Objectives
- 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; use Google Kubernetes Engine as a runtime environment and later switch to a no-ops solution with Google App Engine Flex
Prerequisites
- Completed the Google Cloud Fundamentals course or have equivalent experience
- A working knowledge of Node.js
- Basic proficiency with command-line tools and Linux operating system environments
Outline
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Introduction
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
Google Cloud Client Libraries, Google Cloud SDK, and Google Firebase SDK
Overview of Data Storage Options
- Overview of options to store application data
- Use cases for Google Cloud Storage, Google Cloud Datastore, Cloud Bigtable, Google Cloud SQL, and Cloud Spanner
Best Practices for Using Google Cloud Datastore
- Best practices related to the following: Queries, Built-in and composite indexes, Inserting and deleting data (batch operations), Transactions, Error handling
- Bulk-loading data into Cloud Datastore by using Google Cloud Dataflow
Performing Operations on Buckets and Objects
- Operations that can be performed on buckets and objects
- Consistency model
- Error handling
Best Practices for Using Google Cloud Storage
- Naming buckets for static websites and other uses
- Naming objects (from an access distribution perspective)
- Performance considerations
- Setting up and debugging a CORS configuration on a bucket
Handling Authentication and Authorization
- Cloud Identity and Access Management (IAM) roles and service accounts
- User authentication by using Firebase Authentication
- User authentication and authorization by using Cloud Identity-Aware Proxy
Using Google Cloud Pub/Sub to Integrate Components of Your Application
- Topics, publishers, and subscribers
- Pull and push subscriptions
- Use cases for Cloud Pub/Sub
Adding Intelligence to Your Application
- Overview of pre-trained machine learning APIs such as Cloud Vision API and Cloud Natural Language Processing API
Using Google 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
Managing APIs with Google Cloud Endpoints
- Open API deployment configuration
Deploying an Application by Using Google Cloud Cloud Build, Google Cloud Container Registry, and Google Cloud Deployment Manager
- Creating and storing container images
- Repeatable deployments with deployment configuration and templates
Execution Environments for Your Application
- Considerations for choosing an execution environment for your application or service: Google Compute Engine, Kubernetes Engine, App Engine flexible environment, Cloud Functions, Cloud Dataflow
Debugging, Monitoring, and Tuning Performance by Using Google Stackdriver
- Stackdriver Debugger
- Stackdriver Error Reporting
- Key concepts related to Stackdriver Trace and Stackdriver Monitoring
Conclusion
Training Materials
All GCP training students receive comprehensive courseware.
Software Requirements
Students must have a modern web browser (ideally Chrome) and Internet access.
