Associate Cloud Engineer



A Cloud Developer creates scalable, high availability cloud applications using Google Cloud and tools that are backed by fully managed services

French / English


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Next session : August


A Professional Cloud Developer creates scalable, high availability applications using Google recommended practices and tools. He has experience with cloud native applications, developer tools, managed services, and next-generation databases. He is also proficient in at least one generic programming language, and knows how to generate metrics and logs useful for debugging and monitoring code.

The Professional Cloud Developer exam assesses the following skills:

– Design of highly scalable, available and reliable cloud native applications
– Building and testing applications
– Deploying applications
– Integration of Google Cloud services
– Managing application performance monitoring



Basic knowledge of application development, systems operations, Linux operating systems and data analysis / machine learning will be useful in understanding the technologies presented.
Basic proficiency with command-line tools and Linux operating system environments


Describe the ways in which customers use Google Cloud
Choose and use application deployment environments on Google Cloud: App Engine, Google Kubernetes Engine and Compute Engine
Choose and use Google Cloud storage options: Cloud Storage, Cloud SQL, Cloud Bigtable and Firestore and Google Cloud Datastore
Connect your infrastructure to Google Cloud
Configure load balancers and autoscaling for VM instances
Automate the deployment of Google Cloud infrastructure services
Understand the architecture of Kubernetes
Create Kubernetes Engine clusters using the Google Cloud Console and gcloud/ kubectl commands

Training Program

1- Google Cloud Fundamentals: Core Infrastructure
• Introducing Google Cloud
• Getting Started with Google Cloud
• Virtual Machines in the Cloud
• Storage in the Cloud
• Containers in the Cloud
• Applications in the Cloud
• Containers in the Cloud
• Big Data and Machine Learning in the Cloud
• Summary and Review
2- Developing Applications with Google Cloud
• Best Practices for Application Development
• Google Cloud Client Libraries, Google Cloud SDK, and Google Firebase SDK
• Overview of Data Storage Options
• Best Practices for Using Cloud Firestore
• Performing Operations on Cloud Storage
• Best Practices for Using Cloud Storage
• Handling Authentication and Authorization
• Using Pub/Sub to Integrate Components of Your Application
• Adding Intelligence to Your Application
• Using Cloud Functions for Event-Driven Processing
• Managing APIs with Cloud Endpoints
• Deploying Applications
• Execution Environments for Your Application
• Debugging, Monitoring, and Tuning Performance
3- Getting started with Google Kubernetes Engine
• Introduction to Google Cloud
• Containers and Kubernetes in Google Cloud
• Kubernetes Architecture
• Introduction to Kubernetes Workloads
4- Serverless Cloud Run Development
5- Serverless Firebase Development
6- Deploy to Kubernetes in Google Cloud


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