What is an Edge Server on a Content Delivery Network?
An edge server is a server located at various Points of Presence (POP) around the globe. Content Delivery Networks (CDNs) use these edge servers to store content in cache in close geographic proximity to the requesting users and their devices. Because they are closer and have content readily available in caches, edge servers can deliver content faster than a single origin server that might be far away. For example, ImageEngine has device-aware edge servers available at more than 20 POPs around the globe.
What Makes a Device-Aware Edge Server?
Typically, edge servers are pretty basic. They hold content and they deliver what is requested. In contrast, a device-aware edge server has device detection built into its business logic. And this device information drives a number of optimizations in the image CDN. For example, when a user in Singapore uses their Samsung Galaxy 21 to browse an eCommerce site, the initial HTTP request hits the edge server in Singapore. The server instantly identifies the Samsung Galaxy S21 and several important capabilities of the device: OS version, screen pixel density, screen resolution, and support for advanced image and video formats (e.g. WEBP or AVIFconverts). As part of a CDN, this edge server can act on the image request instantly, or it can share device information with other parts of the image CDN.
Do Device-Aware Edge Servers Make Delivery Faster?
If the edge server has seen that device model before, then it will already have stored images for the requested web page that are tailored exactly to the specs of that device. A device-aware edge server can make a lightning-fast response from its cached images 98% of the time! Not only are the cached images geographically close to the end user, but the images also have a dramatically smaller payload than the original-sized images – up to 80% smaller! With device-aware edge servers delivering significantly smaller images from geographically close locations, websites are able to cut several seconds off their page loading time. This time is crucial for decreasing bounce rates and increasing conversion rates.
How Does Device Information Reduce Image Payload?
Typically, an image CDN like ImageEngine will have several variations of a website’s images in its primed cache at the edge server. However, on a small percentage of requests, the edge server encounters a device model it has not seen in the recent past. It then can send the image request and device intelligence on to the image optimizer. The image optimizer pulls the website’s high-quality original image, and then performs three steps to reduce image payload.
First, it uses the device resolution to change the size of the image. For example, it cuts an original image 3,000 pixels wide to only 1,080 in the case of the Samsung Galaxy S21.
Next, it compresses the image using an image optimizing tool. This cuts out extraneous data that does not impact the visual quality of the image on the requesting device. It knows just how far to compress based on the device intelligence from edge servers.
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Finally, it selects the most efficient file format supported by the device, browser, and its operating system version. For example, for the Samsung Galaxy S21 running Android 12 and a Chrome browser, it would most likely convert a JPEG to WEBP or AVIF. WEBP is an image format from Google that stores image data more efficiently than JPEG. On average, converting images to WEBP (and applying other optimizations) saves 79% of image payload. AVIF is a next-gen image format based on the AV1 video codec and is about 30% more effective than WEBP. Compared to the original image, AVIF may reduce the payload by up to 90%.
In the rare instances when ImageEngine needs to create a new optimized image, processing time is fast – responding in milliseconds. This real-time optimization approach helps tailor image payload reduction and only converts and keeps in cache images that are commonly requested. And with a cache hit rate of 98%, the response time is faster than alternative CDN or image management solutions.
How Does Device Information Improve Image Quality?
Visual quality is very tricky to calibrate. If you do not know the exact device and display capabilities, then you are shooting in the dark about how much image information you can discard during the compression step. ImageEngine combines its device intelligence with advanced heuristics and machine learning to calibrate quality exactly to the device model. More can be learned about image quality control here.