~/gcp-cloud-devops-engineer · Build and implement CI/CD pipelines, including continuous testing, for application, infrastructure, and machine learning workloads ▊

GCP · objective · 20% of the exam

Build and implement CI/CD pipelines, including continuous testing, for application, infrastructure, and machine learning workloads

Exam objectives are the official skill domains Professional Cloud DevOps Engineer tests. Below are the official GCP docs our questions on this objective cite — review them, then practise.

Practise these 11 questions →

Official references for this objective

Google Cloud — Cloud Build serverless CI/CD platform | Google Cloud

Default pool lets you run builds in a secure, hosted environment with access to the public internet.
Google Cloud — Cloud Deploy - Fully Managed Continuous Delivery | Google Cloud

Cloud Deploy brings Skaffold to your pipelines, which, in unison with Cloud Code, brings pipeline parity across dev and CI/CD.
Google Cloud — Terraform blueprints and modules for Google Cloud  |  Terraform on Google Cloud  |  Google Cloud Documentation

cloud-deploy Create Cloud Deploy pipelines and targets
Google Cloud — Cloud Code | Google Cloud

Cloud Code for IDEs uses popular tools such as Skaffold, Jib, and kubectl to provide continuous feedback on your code in real time.
Google Cloud — Cloud Run | Google Cloud

On-demand access to NVIDIA L4 GPUs for running AI inference workloads. GPU instances start in 5 seconds and scale to zero.
Google Cloud — Software Delivery | Google Cloud

A reference architecture and supporting code to implement an opinionated software delivery model that can scale across multiple teams and multiple environments.