Chapter 7: Static Meets Dynamic Adding Caches to Reduce Costs

Static content on a website is like a phone book, but imagine how difficult it would be to use your "paper cache" if the numbers inside the phone book constantly changed or if numbers differed based on who was looking them up.  This is why caching dynamic content poses a more difficult problem than caching static content.
Chapter 7: Static Meets Dynamic Adding Caches to Reduce Costs

This chapter excerpt is from "Scalable Internet Architectures", by Theo Schlossnagle, Copyright 2007 by Sams Publishing, ISBN 067232699x. Reprinted with permission, all rights reserved. To review a complete Table of Contents, please visit: www.samspublishing.com/title/067232699x

Chapter 6, "Static Content Serving for Speed and Glory," walked you through building a high-capacity static content serving system using a web caching system as the core technology. That software was responsible for fetching static content from "master" servers and peddling the cached content efficiently and inexpensively.

Why is the problem so different when the content is no longer static? Why can't we use the exact same solution presented in Chapter 6 for dynamic content?

Think of a website as if it were a phone book.  A cache is a piece of paper that sits next to your phone book on which you record all the numbers you look up.  Sounds like a good idea, right? So much so that you will probably tape that piece of notebook paper to the front of your phone book because you are likely to be interested only in a small subset of the information contained in the book and just as likely to be interested in the same information time and time again.  Sounds perfect, right? But the analogy is flawed.  Static content on a website is like a phone book, but imagine how difficult it would be to use your "paper cache" if the numbers inside the phone book constantly changed or if numbers differed based on who was looking them up.  This is why caching dynamic content poses a more difficult problem than caching static content.

One misconception about caches is due to the misalignment of the computing-centric definition and the English definition of the word cache.  In English, a cache is a place to store things often out of sight or in secret, and that definition assumes that it will be there when you return for it.  A computer cache is only meant to speed acquisition of data; if it is missing when you look for it, you incur what is called a cache miss.  This miss costs you nothing but time.

Caches are everywhere, from the "registers" on your CPU to L1/L2 CPU cache to disk drives to name servers to web systems–and the list goes on.  Caches are fundamental engineering tools both inside and outside technology.  If they are everywhere, how do you tell if a cache is a web cache? Let's define our web architecture as components directly creating browser-digestible content.  This definition eliminates many architectural components that use caches: load balancers, databases, networking equipment, disk drives, and so on.  This leaves us with web servers and application servers (glorified web servers).

Web servers are squished right in the middle of our spectacular architectural sandwich.  Web caches are caching components of any type that operate directly on web servers or between web servers and their adjacent layers as depicted in Figure 7.1.

Figure 7.1: Typical architecture surrounding web servers.

 

Performance Tuning Has Its Limits - Why are we talking about caching and not application performance tuning? This is an important question and deserves attention.  Our goal is to demonstrate techniques that can be used as building blocks for scalable systems–and caching is such a technique.  Application tuning can only increase performance, and you'll note that the title of this book is not High Performance Internet Architectures.  That is not to say that the concepts herein do not perform well, but rather that they focus on scalability and leave high-performance programming, tuning, and tweaking to other books.

Why are scalability and performance different? This is explored in detail in the introduction, but it deserves a few more words.  No matter how fast you make your application, you will be limited if it does not scale horizontally.

To put it another way, if your application performance can be increased by 10%, 5%, or perhaps 1% by doubling your hardware, you are in big trouble.  Moore's law says that your computer will be twice as fast in 18 months, so if you want to double your capacity, call me in a year and a half.  On the other hand, if your application and architecture are designed to be able to leverage 60% or more performance by doubling your architecture, you can scale your system up today.  Those percentages are arbitrary, and each architecture will have its own horizontal scaling efficiency.  100% means a perfectly (horizontally) scalable architecture, and 0% means an architecture that scales vertically, so performance tuning is your only option–so aim high.

 

______________________

Comments

Comment viewing options

Select your preferred way to display the comments and click "Save settings" to activate your changes.

Cookie storage

Slac's picture

Thanks for this good summary.

I have got some problems with cookie caching, because only small informations can be stored in cookies and this form of caching could come together bandwith problems on the client side.

So I think it can be better a combination of cookies and server caching. For example: A user comes and first time I read the cookie, and the next page query I can use serverside cache (created from cookie's datas). I change the cookie only when the user change his preferences.

In this example the process seems so:

1. I check the serverside cache, if found, then ok, else
2. I check the cookie, if found and valid, then ok, else
3. I get the informations from the database and write in cache and in cookie

And 30 minutes after the last page query (same as by sessions) the serverside cache can be invalidated by a timer.

Same problem

Ray's picture

My programmer Adam had the same problem. He figured out a compact way to server over 53 million of our blog articles on one little server.

The speed is awesome and googlebot is busy busy.. my blogs

~Ray

Good Summary

Schifoan's picture

Some of the technics are often used, but this article is a good summary for caching dynamic pages and content.

What an article! Sure beats

Student Organization Leader's picture

What an article! Sure beats the caching concepts discussed in my University's computer architecture class. Can't say that I manage web sites with enough traffic to need such levels of performance refining, but it sure is fun to learn.

Webinar
One Click, Universal Protection: Implementing Centralized Security Policies on Linux Systems

As Linux continues to play an ever increasing role in corporate data centers and institutions, ensuring the integrity and protection of these systems must be a priority. With 60% of the world's websites and an increasing share of organization's mission-critical workloads running on Linux, failing to stop malware and other advanced threats on Linux can increasingly impact an organization's reputation and bottom line.

Learn More

Sponsored by Bit9

Webinar
Linux Backup and Recovery Webinar

Most companies incorporate backup procedures for critical data, which can be restored quickly if a loss occurs. However, fewer companies are prepared for catastrophic system failures, in which they lose all data, the entire operating system, applications, settings, patches and more, reducing their system(s) to “bare metal.” After all, before data can be restored to a system, there must be a system to restore it to.

In this one hour webinar, learn how to enhance your existing backup strategies for better disaster recovery preparedness using Storix System Backup Administrator (SBAdmin), a highly flexible bare-metal recovery solution for UNIX and Linux systems.

Learn More

Sponsored by Storix