OpenRoss – fast, scalable, on-demand image resizer
21–30 of 34 posts
Re: OpenRoss – fast, scalable, on-demand image resizer
#22At first I thought OpenRoss was a new competitor to GraphicsMagick and ImageMagick, but it's just a Twisted plugin. The title should be changed.
Re: OpenRoss – fast, scalable, on-demand image resizer
#23Re: OpenRoss – fast, scalable, on-demand image resizer
#24I was surprised how... latent downloading from S3 is, and how it didn't seem to matter if I was running on Digital Ocean or EC2, downloading the image from S3 was always the slowest part. (Digital Ocean was actually faster!)
It takes about a second to process an image, but it is cached in front of CloudFront similar to the article.
Any tips for improving the latency from S3?
Re: OpenRoss – fast, scalable, on-demand image resizer
#25I would love to see a golang version of this.
Re: OpenRoss – fast, scalable, on-demand image resizer
#2622ms for a GraphicsMagick resize is quite fast. I'm curious what the average input and output sizes were used when computing that number?
Re: OpenRoss – fast, scalable, on-demand image resizer
#27Re: OpenRoss – fast, scalable, on-demand image resizer
#28Re: OpenRoss – fast, scalable, on-demand image resizer
#29It's still running happily in production.
Re: OpenRoss – fast, scalable, on-demand image resizer
#30Earlier quoted context omitted.
They say that, but there's one giant missing ", because..." in that paragraph. They never explain why they render in 10 sizes (why don't they know which sizes they need), and why is loading one of those sizes on a mobile app not feasible. It's stated like that and left hanging in the air. Either their use case is very weird, or they're deliberately vague for some reason only they know about. Also to clarify why 10 si…
When the site was originally designed, there were only 4 or 5 sizes, one for the feed, one for the product page, one for related products, one for thumbnails, etc. As the design changed, extra sizes got added to the image processing, and as with most early stage start-ups, it worked therefore there was no need to fix it. We eventually ended up in the position of having 2.5M products all with preprocessed images of ce…