Skip to main content

Data Majestic. Scalability thirsty Apps.

I have been interested on scalability of Humongous apps recently. Google declared the first ever free real time stock quotes provision today. So Tomorrow morning, If you are on Google Finance, You are not watching the 15-20 minute delayed results.

For an average Joe, this might be just another thing google can do. But for Technology enthusiasts, This is a much interesting step. Just give you an idea, a few days back Facebook opened up its chat feature to its ~70 million strong member base. Google does a similar feat with its Chat integration for its, I don't even know how many, million users. IMs are the least of issues. Presence Notification packets, Security, Keeping so many connections open, memory to handle all these are of highest consideration. It would be interesting how Google will explain feed polling from NASDAQ and delivery and still keep it realtime for Gigillian hits google.com/finance gets every day. What is even harder to imagine is how an open webapp(even available for unregistered visitors), will handle all these challenges and more.

This is just the tip of the iceberg, there are so many technical aspects. If this post locked you in for scalability, Get more here

Popular posts from this blog

Powered By

As it goes, We ought to give thanks to people who power us. This page will be updated, like the version page , to show all the tools, and people this site is Powered By! Ubuntu GIMP Firebug Blogger Google [AppEngine, Ajax and other Apis] AddtoAny Project Fondue jQuery

Decorator for Memcache Get/Set in python

I have suggested some time back that you could modularize and stitch together fragments of js and css to spit out in one HTTP connection. That makes the page load faster. I also indicated that there ways to tune them by adding cache-control headers. On the server-side however, you could have a memcache layer on the stitching operation. This saves a lot of Resources (CPU) on your server. I will demonstrate this using a python script I use currently on my site to generate the combined js and css fragments. So My stitching method is like this @memize(region="jscss") def joinAndPut(files, ext): res = files.split("/") o = StringIO.StringIO() for f in res: writeFileTo(o, ext + "/" + f + "." + ext) #writes file out ret = o.getvalue() o.close() return ret; The method joinAndPut is * decorated * by memize. What this means is, all calls to joinAndPut are now wrapped (at runtime) with the logic in memize. All you wa...

Faster webpages with fewer CSS and JS

Its easy, have lesser images, css and js files. I will cover reducing number of images in another post. But If you are like me, You always write js and css in a modular fashion. Grouping functions and classes into smaller files (and Following the DRY rule, Strictly!). But what happens is, when you start writing a page to have these css and js files, you are putting them in muliple link rel=style-sheet or script tags. Your server is being hit by (same) number of HTTP Requests for each page call. At this point, its not the size of files but the number server roundtrips on a page that slows your page down. Yslow shows how many server roundtrips happen for css and js. If you have more than one css call and one js call, You are not using your server well. How do you achieve this? By concatinating them and spitting out the content as one stream. So Lets say I have util.js, blog.js and so.js. If I have a blog template that depends on these three, I would call them in three script tags. Wh...