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src/content/blog/ondemand-image-optimization-catapi.mdx
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src/content/blog/ondemand-image-optimization-catapi.mdx
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---
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pubDate: '2022-08-04'
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title: 'Free, on-demand image optimizations with Cloudflare'
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description: ''
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keywords:
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- image optimization
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- docker
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- sveltekit
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- svelte
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hidden: true
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---
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I wanted to use responsive images for my small page of cute [cats](/cat) (now removed as of 8/12/2024). Since
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one of the design goals is to give my significant other, who by the way loves
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cats a lot more than me, the option to add cats on the fly and also consume the
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cat pictures in other services, I require dynamic image optimization.
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Requirements:
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- On demand addition of new images
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- Optimization for different width and webp / progressive JPEG
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- Served from the edge for lowest latencies
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Since I've been working a lot with Cloudflare, I of course checked out their
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[Image](https://developers.cloudflare.com/images/cloudflare-images/) offering.
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While the service would exactly fulfill my requirements, it costs 5€/m, which I
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currently can not afford. I thought, this was a good opportunity to build my own
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little image optimization service, that I could maybe even use in the future for
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other image-related projects.
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## Infrastructure overview
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I rely on Cloudflare services to serve the optimized images. On pages, this
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Svelte website is hosted. For our API endpoints that this website is querying, I
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utilize Cloudflare workers. The optimized images are stored on the new
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Cloudflare R2 storage and an index is created on KV. Finally, I host the image
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optimization program on a Raspberry Pi at my place. It is connected with a
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Cloudflare tunnel to the internet. Any other device that has computing power and
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is accessible via the internet is alright.
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- **(1)**: a user uploads a new image, for example via this site
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- **(2)**: the worker processes forwards the image to the image optimization server
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- **(3)**: the optimization server does its thing and serves the optimized
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images in a folder. The worker is notified where the optimized images can be found.
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- **(4)**: the worker fetches the images and stores them with a consistent naming scheme in
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- **(5)**: an object containing metadata to the optimized image (location in R2) are inserted into KV
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