Engineering Efficiency: Re-architecting Docker Delivery to Cut Costs and Boost Speed

Faster Deploys, Lower Costs: How We Re-Architected Docker Image Delivery

We used to run a multi-node JFrog Artifactory cluster to support Docker image pulls across our 10+ datacenters.

But we noticed a growing issue:

App boot times were rising due to cross-region image pulls and large image sizes.

Instead of scaling Artifactory (and its licensing costs), we went the other direction.

We downgraded to a single-node Artifactory and built a smarter, cheaper edge caching layer:
• Stateless NGINX containers deployed in each region
• Acting as caching proxies with ephemeral storage

Results?
• Much faster image pulls
• Simplified infra
• Significant cost savings — both infra and license
• And a solution that scales with the business, not against it

Smart engineering isn’t always scaling up.
Sometimes it’s scaling wisely.

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