Kraken.io – Image Optimization Web Service

Kraken is a web service designed to perform a similar function to desktop based applications such as ImageOptim. For as little as $7 a month (for half-a-gigabyte of images processed a month), you can have Kraken.io process your images and compress them. Alternatively, you can use their free web service by uploading files individually. The service works significantly faster than ImageOptim because of the powerful servers that they use to crunch your images.

But, how does it compare to the desktop equivalent?

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PNG vs. WebP Image Formats

Previously, we went over how the new WebP image format compared to the traditional JPG. One neat thing about WebP is that, unlike JPG or PNG, WebP has the ability to use either lossy or lossless compression, with or without transparency. While JPG is traditionally used to display photos, which have a high level of detail and are generally more complex and can suffer from a little bit of detail loss as a tradeoff for compression, WebP can also be used like a PNG, which is often used for web graphics with transparency or subtle patterns.

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JPG vs. WebP Image Formats

There are several kinds of file formats for images on the web. Primarily, web developers use JPG and PNG image files, depending on the content of the image itself. However, Google has made a push recently to use a new format– called WebP– that is supposedly more efficient than JPG, yet still has the ability to have transparency. In other words, WebP is the best of both JPG and PNG file formats– but does it really reduce image file sizes?

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Taking the Work Out of Optimization: Using Mod_Pagespeed

Since I originally moved my blog to the Jekyll platform, I’ve been looking for several ways to push the performance of my website further.

Over the last couple of months, I’ve been exploring several content distribution networks for my new web course Extreme Website Performance, such as CloudFlare and Amazon’s CloudFront, as well as forgoing a CDN altogether and focusing on reducing the number of network requests used (and therefore taking the bottleneck away from the distribution servers).

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