And social media sites regularly handle huge quantities of user-generated images.ĬDNs maintain edge servers around the globe with cached images, close to the end user. Many commerce sites, for example, regularly add new products, and the accompanying images.
React is an increasingly popular JavaScript front-end framework that works with most headless CMS like Contentful, Magnolia, Graphcms, Sanity, Prismic, Butter, Contentstack, Dotcms, Mura, Cockpit, Craft, Zesty.io, Kontent.ai.
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By separating the content and database of the CMS from the front-end framework like React, developers can free themselves from rigid templates of traditional CMS. Headless CMSs are an exciting trend that many web developers, enterprises, and eCommerce companies are adopting. At the end of the optimization cycle, image CDNs can reduce image payload up to 80%. All of these next-gen image formats are typically 30% more effective than a standard JPEG-and that is before further device-driven compression or resizing. ImageEngine also offers AVIF, of the newest image formats. For animated GIFs, an image CDN can convert them into MP4s or animated WebPs. Likewise, it can deliver WebP or JPEG 2000 to Apple’s Safari browser. For example, ImageEninge can use Google’s WebP file format to deliver optimized images to the Chrome browser. An image CDN automatically manages all of the complexity of selecting the optimal image format for a device or browser.
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However, developers and designers should not have to manually transform images and generate new code to deliver image variants to the devices and browsers that support them. Image and video file formats are constantly evolving. This enables an image CDN to deliver quickly to a range of devices at a lower cost.Īfter implementing ImageEngine, all of your images will be delivered in the most optimal image format, including next generation image formats like WebP, AVIF, and JPEG 2000. Virtual cloud-based edge servers effectively serve the entire globe from only a few dozen locations. Because an image CDN reduces image payload and response time so dramatically, it is no longer necessary to build out a CDN with thousands of POPs.
This requires intelligent, device-aware edge servers. Given their huge infrastructure investment, traditional CDNs need to keep data payloads large to pay for their legacy network costs.Īn image CDN takes a radically different approach by changing the original static image into dynamic content by optimizing the image in different ways based on where the image is viewed. And since the business model of traditional CDNs are based on a price per gigabyte delivered basis, they have no interest in optimizing the payload. Whether it is an Apple laptop, a Samsung Galaxy S9 smartphone, an Apple iPad Air 2, or a Motorola G3 smartphone, a traditional CDN will send the same large original image.
A traditional CDN does not know the screen size of the requesting device. There are several problems with the traditional CDN model when it comes to images. The idea is that by caching content and reducing the geographic distance, a traditional CDN will improve speed and reduce the burden on a company’s origin server. Typically, they do this by having edge servers at many Points of Presence (POPs) all over the world. A traditional content delivery network (CDN) focuses on pushing content as close as possible to the requesting user.
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