Google Cloud Certified - Professional Cloud Developer

Course Overview

A Professional Cloud Developer builds scalable and highly available applications using Google-recommended practices and tools. This individual has experience with cloud-native applications, developer tools, managed services, and next-generation databases. A Professional Cloud Developer also has proficiency with at least one general-purpose programming language and is skilled at producing meaningful metrics and logs to debug and trace code.

The Professional Cloud Developer exam assesses your ability to

  • Design highly scalable, available, and reliable cloud-native applications
  • Build and test applications
  • Deploy applications
  • Integrate Google Cloud services
  • Manage application performance monitoring

Exam Format

  • Exam Duration: 120 Minutes
  • Number of QUESTIONS : 60
  • Exam format: Multiple choice and multiple select
  • Passing score: Google does not release exam marks for this certification – just a pass or a fail, so it is quite hard to know what the pass threshold is – estimates are around 80%

Pre-requisuite

No

Target Audience

  • Software developers who want to build applications on Google Cloud Platform
  • People preparing for the Google Professional Cloud Developer exam

Course Outline

Section 1: Designing highly scalable, available, and reliable cloud-native applications

  • 1.1 Designing high-performing applications and APIs.
  • 1.2 Designing secure applications.
  • 1.3 Managing application data.
  • 1.4 Application modernization.

Section 2: Building and testing applications

  • 2.1 Setting up your local development environment.
  • 2.2 Writing efficient code.
  • 2.3 Testing.
  • 2.4 Building.

Section 3: Deploying applications

  • 3.1 Recommend appropriate deployment strategies using the appropriate tools (e.g., Cloud Build, Spinnaker, Tekton, Anthos Configuration Manager) for the target compute environment (e.g., Compute Engine, Google Kubernetes Engine).
  • 3.2 Deploying applications and services on Compute Engine.
  • 3.3 Deploying applications and services to Google Kubernetes Engine (GKE).
  • 3.4 Deploying a Cloud Function.
  • 3.5 Using service accounts.

Section 4: Integrating Google Cloud services

  • 4.1 Integrating an application with data and storage services.
  • 4.2 Integrating an application with compute services.
  • 4.3 Integrating Cloud APIs with applications.

Section 5: Managing application performance monitoring

  • 5.1 Managing Compute Engine VMs.
  • 5.2 Managing Google Kubernetes Engine workloads.
  • 5.3 Troubleshooting application performance.: