How to Build a Hybrid Cloud Platform with Google Cloud Services and On-Premise Kubernetes Infrastructure

                     How to Build a Hybrid Cloud Platform with Google Cloud Services and On-Premise Kubernetes Infrastructure
               



Tópico:
                     How to Build a Hybrid Cloud Platform with Google Cloud Services and On-Premise Kubernetes Infrastructure
               
Categoria: Tutoriais | FreeCodeCamp Premium
Idioma Principal: Português (Conteúdo de Tecnologia)

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In this article, you'll learn how to design and build a secure, scalable hybrid cloud platform that connects your on‑premises Kubernetes infrastructure to Google Cloud Platform. This allows on‑prem apps can consume cloud services (notably GPUs) without brittle long‑lived keys, manual credential management, or risky network patterns.

Who this is for:

• Platform engineers, SREs, and security-focused cloud architects who operate mixed on‑prem and cloud Kubernetes estates.

• Teams that need scalable, auditable access from on‑prem workloads to GCP resources (especially GPU instances) while minimizing operational overhead and blast radius.

What you'll get from this guide:

• The motivation and economics behind a hybrid approach (why GPUs often push workloads to the cloud).

• Common pitfalls with service account keys and how "accidental air gaps" occur in real environments.

• A practical, end‑to‑end pattern that uses Workload Identity Federation to give on‑prem pods short‑lived, auditable access to GCP without embedding keys.

What's included:

• Conceptual explanations, security tradeoffs, and operational best practices.

• Concrete examples and Kubernetes/Terraform artifacts (linked in the GitHub repo at the end of this article) so you can reproduce the setup in your environment.

Read on for the theory, then follow the hands‑on sections to provision GCP resources, configure federation, enforce policies with CEL and Kyverno, and validate secure, scalable GPU access from your on‑prem Kubernetes clusters.

Note: Kubernetes and Terraform artifacts are linked in the GitHub repo at the end of this article.

Table of Contents

• Prerequisites

• Why Hybrid Cloud Matters

• The Economics of Hybrid: GPUs Changed Everything

• Why Service Account Keys Fail at Scale

• How the Accidental Air Gap Happens

• How Workload Identity Federation Bridges the Gap

• How Kubernetes Identity Works

• How to prepare Google Cloud Platform resources

• How to Use CEL for Fine-Grained Access Control

• How to Inject Credentials Automatically with Kyverno

• How to Grant IAM Permissions to Federated Identities

• How to Verify the Setup

• How to Connect On-Prem Apps to Cloud GPUs

• How to Scale GPU Access with CEL Conditions

• The Security Properties Compared

• The Complete Infrastructure as Code Layout

• How to Run a Proof of Concept with vCluster

• Common Issues and How to Solve Them

• Conclusion

Prerequisites

Before following along, you'll need:

• A Kubernetes cluster that is not GKE (on-premises, bare-metal, or a virtual cluster)

• A Google Cloud project with the following APIs enabled: IAM, Security Token Service (STS), and Workload Identity

• Terraform installed and configured

• Kyverno installed in your cluster

• Python 3 with

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google-cloud-secret-managerand

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google-cloud-aiplatformlibraries (for the verification steps. Code available in the github repository.)

•

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kubectlaccess to your cluster

Why Hybrid Cloud Matters

If everything goes right, a hybrid cloud platform lets your on-premises and cloud workloads talk to each other as if they were part of the same network.

There are many practical reasons to run a hybrid cloud setup:

• Offloading analytics to BigQuery: You keep your analytics apps on-prem for data sovereignty, but pipe large datasets into BigQuery for world-class processing power — without buying extra servers.


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