Course Overview:

The course has a blend of engaging presentations, live demonstrations, and hands-on labs, you will gain practical experience using GCP’s suite of managed services and pre-trained machine learning APIs to: 

  • Get a solid understanding of core GCP services like Compute Engine, Cloud Storage, and Cloud SQL, and explore their role in building cloud-native applications. 
  • Master cloud-native architectural principles and best practices, including microservices, containers, and serverless functions. 
  • Dive into a range of managed services, including Cloud Functions, Pub/Sub, and Cloud Spanner, and discover how they streamline development and enhance application performance. 
  • Unlock the power of pre-trained machine learning models with Cloud AutoML and Cloud Vision API, adding intelligence and automation to your applications. 
  • Implement robust security measures and learn how to design your applications for scalability and high availability. 
  • Automate your deployment process with Cloud Build and Cloud Deployment Manager, and implement continuous integration and continuous delivery (CI/CD) pipelines. 

Developing Applications with Google Cloud Platform - What You'll Learn:

  • Implement proven methodologies for code maintainability, security, and efficiency.
  • Choose the right data storage option (relational databases, NoSQL, object storage) based on your application's specific needs and access patterns.
  • Implement federated identity management to simplify user authentication and authorization across diverse systems.
  • Structure your applications with loosely coupled components for enhanced flexibility, maintainability, and scalability.
  • Seamlessly integrate various application components and data sources using messaging queues and event-driven architecture.
  • Effectively debug, trace, and monitor your applications to ensure optimal performance and stability.
  • Streamline and replicate the deployment process using containers and deployment services like Cloud Build and Cloud Deployment Manager.

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Developing Applications with Google Cloud Platform: Key Features:

  • Our Google Cloud Platform training modules have 50% - 60% hands-on lab sessions to encourage Thinking-Based Learning (TBL).
  • Interactive-rich virtual and face-to-face classroom teaching to inculcate Problem-Based Learning (PBL).
  • GCP-certified instructor-led training and mentoring sessions to develop Competency-Based Learning (CBL).
  • Well-structured use cases to simulate challenges encountered in a Real-World environment during Google Cloud Platform training.
  • Integrated teaching assistance and support through an experts-designed Learning Management System (LMS) and ExamReady platform.
  • Being an official Google Cloud Platform Training Partner, we offer authored curricula aligned with industry standards.

Who Should Attend this Course on Developing Applications with Google Cloud Platform:

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

What are the prerequisites for the training?

To get the most out of this course, participants should have:

  • 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.
  • Why choose CloudThat as a developing Application with a Google Cloud Platform training partner?

    • Specialized GCP Focus: CloudThat specializes in cloud technologies, offering focused and specialized training programs. We are Authorized Trainers for the Google Cloud Platform. This specialization ensures in-depth coverage of GCP services, use cases, best practices, and hands-on experience tailored specifically for GCP.
    • Industry-Recognized Trainers: CloudThat has a strong pool of industry-recognized trainers certified by GCP. These trainers bring real-world experience and practical insights into the training sessions, comprehensively understanding how GCP is applied in different industries and scenarios.
    • Hands-On Learning Approach: CloudThat emphasizes a hands-on learning approach. Learners can access practical labs, real-world projects, and case studies that simulate actual GCP environments. This approach allows learners to apply theoretical knowledge in practical scenarios, enhancing their understanding and skill set.
    • Customized Learning Paths: CloudThat understands that learners have different levels of expertise and varied learning objectives. We offer customized learning paths, catering to beginners, intermediate learners, and professionals seeking advanced GCP skills.
    • Interactive Learning Experience: CloudThat's training programs are designed to be interactive and engaging. We utilize various teaching methodologies like live sessions, group discussions, quizzes, and mentorship to keep learners engaged and motivated throughout the course.
    • Placement Assistance and Career Support: CloudThat often provides placement assistance and career support services. This includes resume building, interview preparation, and connecting learners with job opportunities through our network of industry partners and companies looking for GCP-certified professionals.
    • Continuous Learning and Updates: CloudThat ensures that our course content is regularly updated to reflect the latest trends, updates, and best practices within the GCP ecosystem. This commitment to keeping the content current enables learners to stay ahead in their GCP knowledge.
    • Positive Reviews and Testimonials: Reviews and testimonials from past learners can strongly indicate the quality of training provided. You can Check feedback and reviews about our GCP courses that can provide potential learners with insights into the effectiveness and value of the training.

    Learning objective of the course:

    • Apply best practices for secure, scalable, and maintainable applications on GCP.
    • Choose the optimal data storage option (relational, NoSQL, object) based on application needs.
    • Simplify user authentication and authorization across diverse systems using federated identity management.
    • Structure applications with loosely coupled components for enhanced flexibility and scalability.
    • Seamlessly connect various components and data sources using messaging queues and event-driven architecture.
    • Streamline the deployment process and effectively debug, trace, and monitor applications for optimal performance.

    Course modules: Download Course Outline


    • 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.


    • 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.


    • Overview of options to store application data
    • Use cases for Google Cloud Storage, Cloud Firestore, Cloud Bigtable, Google Cloud SQL, and Cloud Spanner.


    • 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


    • Operations that can be performed on buckets and objects
    • Consistency model
    • Error handling


    • 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


    • 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.


    • 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.


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

    • Key concepts such as triggers, background functions, HTTP functions.
    • Use cases.
    • Developing and deploying functions.
    • Logging, error reporting, and monitoring.


    • Open API deployment configuration.


    • Lab: Deploy an API for your application.


    • 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.


    • 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


    • 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.

    Course Fee

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    Course ID: 20183

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    Frequently Asked Questions

    While completing Google Cloud Platform Fundamentals or having equivalent experience is recommended, the course is designed for intermediate developers wanting to build or migrate applications to GCP.

    Hands-on labs use Node.js, Python, or Java, but the core concepts are language-agnostic.

    50-60% of the course consists of hands-on labs, providing ample opportunity to apply your learnings in a simulated GCP environment.

    Absolutely! Implementing robust security measures and designing for scalability and high availability are key learning objectives.

    Yes, you'll learn to streamline deployments with Cloud Build and Cloud Deployment Manager, and even transition to a NoOps environment with App Engine.

    While this course prepares you for the Google Cloud Professional Cloud Developer certification, it's not directly tied to any specific certification.

    CloudThat offers specialized GCP training by certified instructors, with a hands-on focus, customized learning paths, and interactive sessions. We also provide placement assistance, career support, and continuously updated content.

    Please visit our website or contact us directly for enrollment information and any further questions you may have.

    Enquire Now