Using Harbor as a Proxy Cache for Cloud-Based Registries

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⚡ TL;DR

The Problem: Public Registry Challenges Why Use a Proxy Cache? How it works: The Benefits: Setting Up Harbor as a Proxy Cache Step 1: Deploy and Access Harbor Step 2: Configure the Proxy Target (External Registry) Step 3: Create a New Project for the Proxy Using the Proxy Cache How it Works in Practice What happens behind the scenes: Visual Walkthrough Cache Invalidation and Retention Other Supported Registries Conclusion Discover more from VMware Cloud Foundation (VCF) Blog Related Articles Deploy VCF Private AI Services in Minimal VMware Cloud Foundation Environments NVMe Memory Tiering Design and Sizing on VMware Cloud Foundation 9 Part 4: vSAN Compatibility and Storage Considerations Using Harbor as a Proxy Cache for Cloud-Based Registries In the world of containerization, pulling images from public registries is a daily task for development teams, CI/CD pipelines, and production deployments. But what happens when your team scales? What starts as a simple docker pull nginx command can quickly become a bottleneck.

📝 Summary

The Problem: Public Registry Challenges Why Use a Proxy Cache? How it works: The Benefits: Setting Up Harbor as a Proxy Cache Step 1: Deploy and Access Harbor Step 2: Configure the Proxy Target (External Registry) Step 3: Create a New Project for the Proxy Using the Proxy Cache How it Works in Practice What happens behind the scenes: Visual Walkthrough Cache Invalidation and Retention Other Supported Registries Conclusion Discover more from VMware Cloud Foundation (VCF) Blog Related Articles Deploy VCF Private AI Services in Minimal VMware Cloud Foundation Environments NVMe Memory Tiering Design and Sizing on VMware Cloud Foundation 9 Part 4: vSAN Compatibility and Storage Considerations Using Harbor as a Proxy Cache for Cloud-Based Registries In the world of containerization, pulling images from public registries is a daily task for development teams, CI/CD pipelines, and production deployments. But what happens when your team scales? What starts as a simple docker pull nginx command can quickly become a bottleneck. docker pull nginx Picture this scenario: Your organization has 50 developers, each running builds multiple times a day. Your CI/CD system spins up fresh containers for every pipeline run. Each environment such as development, staging, and production pulls the same base images repeatedly. All of these pulls hit the public registry directly. Soon, you start experiencing: Rate Limiting Issues: Some public registries limit anonymous users to a specific number pulls per hour. With multiple teams and automated systems, you’ll hit these limits quickly, causing builds to fail with cryptic “too many requests” errors. Slow Build Times: Every pull traverses the internet, adding latency. A 500MB image that could be retrieved from your local network in seconds takes minutes from a public registry. Network Costs: Cloud providers charge for egress traffic. Repeatedly pulling multi-gigabyte images from external registries can result in significant monthly bills.