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Use the IBM Virtual Loaner Program to help you set up an IBM development environment from a remote location and save valuable development time. Start with our new pre-configured SaaS stack featuring WebSphere Application Server Community Edition and DB2 Express C running on Linux, and use the features and support of the Virtual Loaner Program, including the save and restore capability that allows you to continue testing at a later time.

Announced late last year, Amazon tonight launched load balancing, monitoring, and auto-scaling for the Elastic Compute Cloud (EC2). These features have been requested many times by EC2 users and with this release Amazon continues to show that it listens and responds to feedback.

We are working to make it even easier for you to build sophisticated, scalable, and robust web applications using AWS. As soon as you launch some EC2 instances, you want visibility into resource utilization and overall performance. You want your application to be able to scale on demand based on traffic and system load. You want to spread the incoming traffic across multiple web servers for high availability and better performance. You want to focus on building an application that takes advantage of the powerful infrastructure available in the cloud, while avoiding system administration and operational burdens ("The Muck," as Jeff Bezos once called it).

Today we are introducing Amazon Elastic MapReduce , our new Hadoop-based processing service. I'll spend a few minutes talking about the generic MapReduce concept and then I'll dive in to the details of this exciting new service.

Thinking about a new Phone System. Let us share with you the benefits of VoIP, and introduce you to features such as Unified Messaging.

Cloud computing is a term used to describe a variety of computing models that involve a collection of computers housed in a secure facility accessed through a network connection, typically the Internet. However, cloud computing isn't new, in fact it has been around since the early 1950s.

The Amazon Elastic Compute Cloud (Amazon EC2) embodies much of what makes infrastructure as a service such a powerful technology; it enables our customers to build secure, fault-tolerant applications that can scale up and down with demand, at low cost. Core in achieving these levels of efficiency and fault-tolerance is the ability to acquire and release compute resources in a matter of minutes, and in different Availability Zones.

Some OpenSocial apps can be written entirely with client-side JavaScript and HTML, leveraging the container to serve the page and store application data. In this case, the app can scale effortlessly because the only request hitting your server is for the gadget specification which is typically cached by the container anyway. However, there are lots of reasons to consider using your own server: * Allows you to write code in the programing language of your choice. * Puts you in control of how much application data you can store. * Lets you combine data from users on multiple social networks. * Enables interaction with the OpenSocial REST API. Setting up an OpenSocial app that uses a third party server is fairly simple. There are a few gotchas and caveats, but the real issues come up when your app becomes successful - serving millions of users and sending thousands of requests per second. Apps can grow especially fast on social networks, so before you launch your next social app, you should think about how to scale up quickly if your app takes off. Unfortunately, scaling is a complex problem that's hard to solve quickly and expensive to implement. Luckily, there are several companies that provide cloud computing resources-places you can store data or run processes on virtual machines. These computing solutions manage huge infrastructures so you can focus on your applications and let the "cloud" handle all the requests and data at scale. This tutorial focuses on a simple photo-sharing app that uses a third-party server to host photos and associated metadata. If this app is going to host millions of images and support many requests per second, we won't be able to run it on a single dedicated host. We'll break the app down and analyze the interactions between the OpenSocial App and the back end server. Then we'll implement the app in the cloud, first using Google App Engine, then leveraging Amazon's S3 data storage service. Finally, we'll look at s