|Scalability Rules: 50 Principles for Scaling Web Sites|
|author||Martin L. Abbot and Michael T. Fisher|
|summary||50 Principles for Scaling Web Sites|
First off this book gives you a primer of rules for you to start with depending on whether you are mostly a manager, software developer or technical operations personnel. I'll concentrate on the specifics of the software developer chapter and summarize the others at the end of this review. Also note that aside from some SQL, I only saw PHP code in this book. Luckily there's only a handful of snippets presented and they are easy to follow. Additionally each chapter ends with solid references (usually online resources) to back up the claims listed in those sets of rules.
The first chapter is devoted to reducing the equation and focuses on removing needless complexity from your solution. You can find this chapter here if you want to see how the layout looks. They give a lot of solid reasons for this and also a lot of good examples like understanding what your users care about. Why build a prompt to export a blog post as a PDF if 99% of the users don't care about it? Next up they say the rule to design to scale means designing for 20x capacity, implementing for 3x capacity and deploying to 1.5x capacity. A strength of the book are the grids that illustrate what is low, medium or high cost and impact through the chapters. Every time they discuss options at different parts of the solution development process, the user is given a chart to understand why. The next rule stresses that you can usually identify 80% of your benefit achieved from 20% of the work (80-20 rule). Rule 4 is strangely specific and implores the reader to simply reduce DNS lookups. However — and this is the first of many — they remind the reader that this rule must be balanced with putting your system all on one server just to reduce DNS lookups. Such a strategy can result in that becoming a choke point. Rule 5 quite simply instructs the reader to use as few objects as possible in your webpage.
The final rule of chapter one is the first one I disagree with in the book. The rule says "Don't mix the vendor networking gear." And this goes against every fiber of my being. Why even have networking standards if you are not to mix the vendor networking gear? Looking to upgrade one component? Better stick to brand X no matter how crappy they have become. This results in being nickeled and dimed and vendor lockin. If scalability is your sole goal than perhaps this is sound instructions. But I cannot understand how anyone would indicate lockin to a vendor — especially in today's networking gear.
Chapter two is incredibly short but potent. It covers some basic database concepts like why ACID properties of databases make them difficult to split. This chapter is spot on and calls upon the AKF cube for dimensions of scalability. Three dimensions are: You can clone things, split different things and split similar things (like by country region). This cube reappears throughout the book and it should be noted that the book does a good job of giving examples of when each dimension is a good choice for scaling and when it is a bad choice compared to the other two. In my line of work, massive scaling solutions have implemented all three.
Skipping to the next developer chapter on not duplicating your work, the text ranged from the incredibly obvious "Don't double check your work" to relaxing temporal constraints. The chapter is short like chapter two and didn't offer me a whole lot. A third rule was again oddly specific in saying not to do redirects and even getting down into the very fine specifics of what HTTP codes are and how they affect your response times.
The next chapter for developers is chapter ten on avoiding or distributing state. Rule 40 actually came in useful at my job as it simply states "Strive for Statelessness." There was an easy solution to a problem in one of our projects that involved storing an object in the session to keep track of what was being displayed to the user. Having read the book, I instead made this web application nearly stateless (except user authentication and the like). Later on, as we started testing the application in multi-tabbed browsing and users began opening many search tabs and viewed several objects at once to compare them, I was glad that I had not gone down this path. Doesn't have much to do with scalability but I think all web developers should read this chapter as it really does pay to avoid state when possible.
As the rules grew closer to 50, they lost their potency. The authors did a good job of trying to put a bit of ranking in the appearance to these rules. The final developer chapter on asynchronous communication and message buses is probably the most specific and was the least useful for me. While all the rules in this chapter are true, they again border on the banal with examples like "Avoid Overcrowding Your Message Bus."
Having read this book cover to cover, it is a very short book with extremely succinct and organized summaries (the final chapter is a short review of each rule). The manager and operations chapters didn't really do a lot for me overall but would occasionally have very interesting chapters that opened up a lot of the logic behind content delivery services to me. Occasionally I would take slight issue with some rules but the most egregious rule I read was Rule 28 "Don't Rely on QA to Find Mistakes" and then the chapter opens with calling the title of this rule "ugly and slightly misleading and controversial." Because it is and could probably be replaced with another sentence from the chapter: "You can't test quality into your system." Why rely on sensational headlines when I'm already holding your book? I think this book would have been a solid 9/10 if not for this oddity in the large rule set.
I've given each of these rules a decent amount of thought and will keep them at the back of my mind as I write code in an agile environment. Mistakes made early on can be very costly in scaling terms. This book will definitely be kept around at work when I need a solid argument for those design decisions that might take more work but save in the future when it needs to scale.
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