This learning path is designed to help you prepare for the Google Professional Cloud Developer exam. Candidates who pass Google's exam will earn the Google Professional Cloud Developer certification. Even if you don't plan to take the exam, these courses and hands-on labs will help you get started on your way to becoming a Google Cloud Platform (GCP) developer.
To give you a solid foundation, this learning path starts with GCP fundamentals. Once you have that foundation, we’ll move on to the first section of the exam, which is about designing for scalability, availability, and reliability. Although GCP services are architected to deliver these characteristics, you need to design your implementations to take advantage of what GCP provides. The next section is on building and testing applications. One of the most important topics in this section is how to build a continuous integration pipeline. After that, we’ll move on to the actual deployment of your applications. There are four different compute services where you can deploy your code. The next section is on integrating your applications with other GCP Services. For example, you may need to use a messaging service to pass data from one module to another. The final section is on managing application performance monitoring.
- Design highly scalable, available, and reliable cloud-native applications
- Build and test applications
- Deploy applications
- Integrate Google Cloud Platform services
- Manage application performance monitoring
- Software developers who want to build applications on Google Cloud Platform
- People preparing for the Google Professional Cloud Developer exam
- General knowledge of IT architecture
- Software development experience
Learning Path Steps
This introduction to the learning path gives an overview of the requirements for Google's Professional Cloud Developer exam and how they will be covered.
This course introduces you to the fundamentals of Google Cloud Platform, including App Engine, Kubernetes Engine, Compute Engine, storage, BigQuery, Cloud Firestore, and app deployment.
Connect to Google Compute Engine (GCE) Linux VM Instances Using SSH
This lab will show you two methods for connecting to Linux VM instances over SSH.
This course uses a case study to show how to apply the design principles of security, compliance, disaster recover to meet real-world requirements.
Host a Static Website Using a Cloud Storage Bucket and Cloud CDN
In this lab, you will create a storage bucket that will host a static website. You will then create a load balancer that will balance the traffic to your bucket and you will create a CDN distribution that will edge distribute the load balancer that points t...
This course covers the Google best practices for setting up a CI/CD pipeline on GCP.
Develop, Build and Deploy a Container Application on Google Compute Engine
In this lab, you will develop a Python application, build it using Cloud Build, store the Docker image on Container Registry and deploy it on a Compute Engine instance.
This Lab teaches you how to use Cloud Functions, introducing you to all of the key concepts and trade-offs that you need to understand to work effectively with Cloud Functions.
Balance the Traffic to Compute Engine Instances Through a Load Balancer
In this lab you will create an instance group that will hold the VMs in your environment, then you will attach a load balancer to the group.
Exploring data storage, networking, and security services, this course is designed to help you pass the Google Cloud Professional Cloud Developer Certification exam.
Create a Network Infrastructure with Google Virtual Private Cloud
In this Lab, you'll create a basic network infrastructure composed of a VPC, two Subnets in different regions, and two firewall rules that will filter the ingress traffic.
Learn how to develop solutions and build highly scalable apps for Google Cloud Platform with this App Engine course.
Learn how to load data into BigQuery using files, run queries using standard SQL, and export data from BigQuery with this hands-on course.
Learn how to make BigQuery faster, cheaper, and more secure with this hands-on course.
This Lab will show you the basic concepts of BigQuery and will allow you to handle data and query them in a real GCP environment.
In this course, you'll learn which of your applications could make use of Bigtable and how to take advantage of its high performance.
In this lab, you will create two tables in a SQL PostgreSQL database, perform operations on them, monitor the resources usage and test that the atomicity property is respected by the database.
In this course, you'll learn how to write data processing programs using Apache Beam and run them using Cloud Dataflow, as well as learning how to run both batch and streaming jobs.
Google Cloud Pub/Sub is a message queuing service that allows you to deploy topics and attach subscriptions to them. Once a message is sent to the topic, it will send the message to all the attached subscriptions.
This hands-on tutorial teaches you monitoring, testing, managing, and troubleshooting your GCP app infrastructure.
In this lab, you will understand the best practices to monitor a compute engine instance by viewing the usage, creating alert policies and creating a chart.
Demonstrate your skills to pass the Professional Cloud Developer certification by performing tasks required by GCP cloud developers in this lab challenge.
Preview Exam: Google Professional Cloud Developer
About the Author
Guy launched his first training website in 1995 and he's been helping people learn IT technologies ever since. He has been a sysadmin, instructor, sales engineer, IT manager, and entrepreneur. In his most recent venture, he founded and led a cloud-based training infrastructure company that provided virtual labs for some of the largest software vendors in the world. Guy’s passion is making complex technology easy to understand. His activities outside of work have included riding an elephant and skydiving (although not at the same time).