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feat: add export-assets script for CDN asset extraction and update Dockerfiles
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@@ -330,6 +330,7 @@
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"self-hosting/guides/custom-certificates",
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"self-hosting/guides/automated-bootstrapping",
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"self-hosting/guides/production-hardening",
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"self-hosting/guides/cdn-caching",
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"self-hosting/guides/monitoring-telemetry"
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]
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},
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106
docs/self-hosting/guides/cdn-caching.mdx
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106
docs/self-hosting/guides/cdn-caching.mdx
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@@ -0,0 +1,106 @@
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---
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title: "CDN Caching for Static Assets"
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description: "How to set up CDN caching to prevent version skew issues during deployments"
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---
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This guide explains a common issue with frontend asset caching during deployments and how to solve it using a CDN.
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## The Problem: Version Skew
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Modern frontend build tools like Vite generate content-hashed filenames for static assets (e.g., `main-abc123.js`). Each build produces unique filenames based on file contents. During deployments, this can cause a race condition:
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1. User loads `index.html` which references `main-abc123.js`
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2. New deployment replaces containers with a new build
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3. New containers only serve `main-xyz789.js` (new build)
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4. User's browser requests `main-abc123.js` from cached HTML
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5. Request returns **404** — the old asset no longer exists
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This results in broken pages, failed SPA navigation, and requires users to manually refresh.
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<Note>
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This is a documented limitation in Vite's official guidance: [Load Error Handling](https://vite.dev/guide/build#load-error-handling)
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</Note>
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### Current Behavior
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Infisical includes a built-in workaround that detects version mismatches and triggers a page reload. While functional, this introduces a noticeable delay for users during deployments.
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## The Solution: External Asset Storage
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The solution is to store static assets externally (e.g., S3, GCS, Azure Blob) and serve them through a CDN (e.g., CloudFront, Cloud CDN, Cloudflare). Assets are uploaded **before** container deployment, ensuring old versions remain available.
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### How It Works
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```mermaid
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flowchart LR
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User[User Browser]
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CDN[CDN]
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S3[(Object Storage)]
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App[Your Infrastructure]
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User --> CDN
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CDN -->|"/assets/*"| S3
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CDN -->|"/* (default)"| App
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```
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The key points:
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- **Asset persistence**: Old assets remain available even after new deployments
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- **Deployment order**: Upload new assets before deploying new containers
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- **Long cache TTL**: Content-hashed files can be cached indefinitely (we recommend 30 days)
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- **Automatic cleanup**: Configure lifecycle rules to expire old assets after 30 days
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At Infisical, we use **CloudFront + S3** for this purpose, but you can use any CDN and object storage combination that fits your infrastructure.
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## Exporting Assets
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Infisical provides a built-in command to export frontend assets from the Docker image:
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```bash
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# Export as tar archive to stdout
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docker run --rm infisical/infisical npm run assets:export > assets.tar
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# Extract the archive
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tar -xf assets.tar
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ls assets/ # Content-hashed JS/CSS files
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```
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Or export directly to a mounted directory:
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```bash
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docker run --rm -v $(pwd)/cdn-assets:/output \
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infisical/infisical npm run assets:export /output
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```
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### What Gets Exported
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The command exports the `/assets` directory containing:
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- JavaScript bundles (e.g., `main-abc123.js`, `chunk-def456.js`)
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- CSS files (e.g., `styles-789xyz.css`)
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- Other static assets with content hashes
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These files are safe to cache with long TTLs because their filenames change whenever the content changes.
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## Integration with Your Pipeline
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The general deployment flow should be:
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1. **Build** your new Docker image (or pull the official Infisical image)
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2. **Export** assets using `npm run assets:export`
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3. **Upload** assets to your object storage
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4. **Deploy** the new container version
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```bash
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# Example: Export and upload to S3
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docker run --rm infisical/infisical:$VERSION npm run assets:export > assets.tar
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tar -xf assets.tar
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aws s3 sync assets s3://your-bucket/assets --cache-control "public, max-age=2592000"
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# Then deploy your container
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```
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<Warning>
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Always upload assets **before** deploying the new container. This ensures the assets referenced by the new `index.html` exist before users can access them.
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</Warning>
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