Latest Free Screencasts

This is the last of three screencasts where looking at a couple new libraries to help you scale your Rails applications. In this episode we start by learning about rubber, a capistrano/rails plugin that makes it easy to deploy/manage/scale on Amazon EC2. Then we look at a background job system with a killer user interface called Cloud Crowd. Lastly we look at a web service called Mad Mimi, which allows you to keep track of mailing lists and even move all of your mailer erb templates out of your web application. Utilizing Mad Mimi’s API can give your customer more control of their mailing lists, and alleviate some developer frustration surrounding email.

In this screencast we discover what typically causes Ruby server memory bloat, namely instantiating too many ActiveRecord objects. Thankfully there are several plugins which can help you detect when your application needs some help, and where your application is hurting the most. We start by taking a look at Rack-Bug, a toolbar which places all sorts of statistics about each requests at your fingertips. Next, we look at two libraries to help specifically track memory bloat; Memory Logic and Oink.

This is the first of three screencasts where we begin to look at a few new Rails libraries to help you scale your Rails applications. In this first episode we take a look at Bullet, which will help you optimize your SQL queries by giving you growl notifications when you’re not using eager loading properly or should be using a counter cache. Then there’s Rails Indexes which provides Rake tasks to find missing indexes in your database. Finally the last library we’ll learn about is Scrooge, a SQL query optimizer which can reduce the amount of data getting sent from your database to your Rails application.

In this second screencast we start out by learning the differences between the myISAM and InnoDB database engines for MySQL.  Next we learn how to scale a write heavy database by using Master Master replication, and how we might configure this to work with our Rails application.  Lastly we’ll figure out how to shard our database by spliting our tables between multiple databases and show how both New Relic and eBay take advantage of this technique.

If the bottleneck of your application is your database even after caching as much as possible, what can you do? This is the first of two screencasts where we’re going to learn about techniques for increasing the power of your Database. In this first video we learn how to grow our database step by step using both vertical and horizontal scaling.

One way to measure the scalability of your Rails application is to use Load Testing. This is the first of two screencasts where we attempt to give an introduction to load testing and show how to use two of the most basic Load Testing tools, Apache Bench and httperf.

This is the second of two episodes where we learn the basics of Load Testing our web applications. In this episode we take a look at autobench, a tool that automates our httperf load tests, then we’ll figure out how to visualize our httperf results in a graph, and finally take a brief look at a few other Load Testing tools you might want to get familiar with.

Rails 2.3 shipped with Rack support and contains a set of middleware libraries which can be used to customize and optimize your Rails application. In this screencast we go over the basics of Rack & Rack Middleware, walk through the Rails Rack stack, and show how to optimize certain actions in your Rails application using Metal.

Jesse Newland works at Rails Machine, where he’s helped scale many Rails applications. In this episode we ask him for 3 tips to help us Scale our applications. We’re then going to take a closer look at one of his recommendations: how to properly deploy a Rails app.

Jim Gochee is the VP of Engineering at New Relic, where he’s helped shape RPM, their server monitoring tool. After asking him his recommendations for Scaling Rails, we take a closer look at some of the advanced features of New Relic’s RPM tool. If you haven’t seen some of the upper tier performance monitoring features of RPM, prepared to be impressed.