David Elfi

Caching is the method that most improves response time in web applications (as Steve Souders shows in Cache is King), but in order to make use of it, every layer of your application must be configured for that purpose.

Most applications are initially developed with little or no use of caching and then must be refactored to fulfill performance goals. However, this approach incurs extra development costs that could be saved if response time is taken into consideration in the early stages of the development process.

The methodology that can save your life while you are still developing your application is pretty straightforward: keep caching in mind whenever handling data in your system. Either web APIs or internal backend data flows need to ask one simple question:

Can I survive if the data seen by the user is not the latest?

Sometimes the answer to this question is ‘no.’ For example, I would be fired very quickly if I built a bank system that showed more money than one consumer’s account really has. On the other hand, if the system interacts with general data services like social networks, news, weather, car traffic, etc., there is less need to ensure the latest piece of information is immediately shown to the user.

Of course, the latest data needs to eventually get to the user. Data cannot be too old or you risk confusing the user, but configuring a short expiration time (let’s say 5-10 minutes or less) for dynamic data that can support it can significantly improve the response time experience. That is called temporal consistency and it is crucial for having a successful caching strategy in place.

Nowadays, web applications are based on mashing up several web services coming from different sources. The best way to tackle different response times as well as data designs is to temporally cache those elements across all system layers. It is also applicable to data coming from your own system if the information needs to travel from one part of the world to another in several hops. If information is not critical, consider caching it at any intermediate stage and reuse when it is needed. Caching in the backend can avoid half of a trip. Even better would be to cache at the target device or a CDN system that can dispose of the full data trip or reduce it to only the last mile as an easy way to enhance performance.
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