GCPDEVA - Developing Applications with Google Cloud Platform

In this certification & training course you will 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 pre-trained machine learning APIs to build secure, scalable, and intelligent cloud-native applications.

Duration: 3.0 days

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Virtual ILT | 03 Jan 2024 - 05 Jan 2024 India
Singapore | 05 Feb 2024 - 07 Feb 2024 Singapore
Virtual ILT | 05 Feb 2024 - 07 Feb 2024 Singapore
Virtual ILT | 06 Dec 2023 - 08 Dec 2023 Thailand
Virtual ILT | 20 Dec 2023 - 22 Dec 2023 Taiwan

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This course teaches participants the following skills:
  • 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 Container Engine as a runtime environment and later switch to a no-ops solution with Google App Engine flexible environment.


The course includes presentations, demonstrations, and hands-on labs.

Module 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.
Module 2: Google Cloud Client Libraries, Google Cloud SDK, and Google Firebase SDK
  • How to set up and use Google Cloud Client Libraries, Google Cloud SDK, and Google Firebase SDK.
  • Lab: Set up Google Client Libraries, Cloud SDK, and Firebase SDK on a Linux instance and set up application credentials.
Module 3: Overview of Data Storage Options
  • Overview of options to store application data.
  • Use cases for Google Cloud Storage, Cloud Firestore, Cloud Bigtable, Google Cloud SQL, and Cloud Spanner.
Module 4: Best Practices for Using Cloud Firestore
  • Best practices related to using Cloud Firestore in Datastore mode for:Queries, Built-in and composite indexes, Inserting and deleting data (batch operations),Transactions,Error handling.
  • Bulk-loading data into Cloud Firestore by using Google Cloud Dataflow.
  • Lab: Store application data in Cloud Datastore.
Module 5: Performing Operations on Cloud Storage
  • Operations that can be performed on buckets and objects.
  • Consistency model.
  • Error handling.
Module 6: Best Practices for Using 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.
  • Lab: Store files in Cloud Storage.
Module 7: 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.
  • Lab: Authenticate users by using Firebase Authentication.
Module 8: Using Pub/Sub to Integrate Components of Your Application
  • Topics, publishers, and subscribers.
  • Pull and push subscriptions.
  • Use cases for Cloud Pub/Sub.
  • Lab: Develop a backend service to process messages in a message queue.
Module 9: Adding Intelligence to Your Application
  • Overview of pre-trained machine learning APIs such as Cloud Vision API and Cloud Natural Language Processing API.
Module 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.
Module 11: Managing APIs with Cloud Endpoints
  • Open API deployment configuration.
  • Lab: Deploy an API for your application.
Module 12: Deploying Applications
  • Creating and storing container images.
  • Repeatable deployments with deployment configuration and templates.
  • Lab: Use Deployment Manager to deploy a web application into Google App Engine flexible environment test and production environments.
Module 13: Execution Environments for Your Application<
  • Considerations for choosing an execution environment for your application or service:Google Compute Engine (GCE),Google Kubernetes Engine (GKE), App Engine flexible environment, Cloud Functions, Cloud Dataflow, Cloud Run.
  • Lab: Deploying your application on App Engine flexible environment.
Module 14: Debugging, Monitoring, and Tuning Performance
  • Application Performance Management Tools.
  • Stackdriver Debugger.
  • Stackdriver Error Reporting.
  • Lab: Debugging an application error by using Stackdriver Debugger and Error Reporting.
  • Stackdriver Logging.
  • Key concepts related to Stackdriver Trace and Stackdriver Monitoring.
  • Lab: Use Stackdriver Monitoring and Stackdriver Trace to trace a request across services, observe, and optimize performance


Application developers who want to build cloud-native applications or redesign existing applications that will run on Google Cloud Platform


To get the most benefit from this course, participants should have the following prerequisites:
  • Completed Google Cloud Platform Fundamentals or have equivalent experience
  • Working knowledge of Node.js, Python, or Java
  • Basic proficiency with command-line tools and Linux operating system environments


This course is not associated with any certification.

Course Benefits

  • Career growth
  • Broad Career opportunities
  • Worldwide recognition from leaders
  • Up-to Date technical skills
  • Popular Certification Badges

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