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Device detection in Varnish

The goal of this VCL set is to provide a simple & easy way of getting device detection going in Varnish Cache. (http://www.varnish-cache.org)

Specific problems we want to solve:

  1. detect the most common and easily detected (mobile/tablet) platforms.
  2. provide example VCL for using devicedetect.vcl with your existing VCL.

These are explicit not goals for this project:

  • Create a comprehensive set of capabilities per client. We don't want to spend a lot of effort on maintenance.
  • Be perfect. It usually works, but if you need guarantees you should consider the commercial offerings instead.

This project is maintained and updated by the community. If you see any false positives or missing strings, fork the git repository and send a pull request.

Requirements

You need Varnish 3. It may function with some adjustments on previous versions, but you are on your own.

It is worth noting that there is no compilation/linking required. This is VCL code only.

Your backends needs to be able to do produce different content based on what type of device this is. This can be signalled to the backend through the URL, with an extra HTTP header or with a cookie. See the INSTALL.rst file for examples.

Use cases

The following uses are envisioned for this VCL:

Installation

See the INSTALL.rst file for details.

Similar efforts

These similar efforts for User-Agent insights are known to us:

Varnish Software has a commercial offering for DeviceAtlas lookup VMOD. Contact <sales@varnish-software.com> for inquiries and quotes. Read more at:

https://www.varnish-cache.org/vmod/deviceatlas-mobile-detection

There is an open source project for using OpenDDR in Varnish:

https://github.com/TheWeatherChannel/dClass

Other open efforts in this field:

Contact

This project lives on Github:

http://github.com/varnish/varnish-devicedetect/

Feature requests, bug reports and such can be added to the Github issue tracker.

This shiny piece of code is authored by Lasse Karstensen <lasse@varnish-software.com>.

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  • Python 80.9%
  • Shell 19.1%