Cloud Foundry, a VMware-led project is the world’s first open Platform as a Service (PaaS) offering. Cloud Foundry provides a platform for building, deploying, and running cloud apps using Spring for Java developers, Rails and Sinatra for Ruby developers, Node.js and other JVM frameworks including Grails.

At BackType, we are heavy users of Hadoop. We use it to run computations on our 30TB datastore of social data. We've even open-sourced some significant projects that are built on top of Hadoop.

Unfortunately, Hadoop has problems. It's sloppily implemented and requires all sorts of arcane knowledge to operate it. We would be the first to try out a replacement for Hadoop if a viable alternative existed. In this post, we'll look at some of the darker aspects of Hadoop.

Last night, TechCrunch reported that Google will now require sites that import e-mail addresses from Gmail to also allow export of their data. The move was clearly aimed at Facebook, which has kept Google from accessing their users’ data. In response, many people have mentioned that while Facebook lets users download some data, they’re still not able to download an e-mail address book of their Facebook contacts. However, that’s not quite the case. Back in March, I published a guide to exporting data from Facebook using various tricks and FQL queries. Facebook has since made changes and added tools which have made the post a bit outdated, but much of the information still applies. In particular, I described using Yahoo’s contact import tool to download an e-mail address book for all your Facebook friends. This technique relies on a Facebook-approved feature and should not violate the site’s terms of service. A few specific steps have changed a bit, so I’ll recap the process here.

Since the rise of the Web, SQL-based relational databases have been the dominant structured storage technology behind online applications. The past few years have seen the emergence of the cloud as a compelling environment for online application development, bringing true utility computing into the infrastructure pantheon. But the cloud and SQL do not mix well, and multiple efforts are now underway to offer viable alternatives to the venerable database. In this article, I'll review the forces that have led to this shift, and I'll argue that while relational databases are by no means doomed, they will soon be joined in the cloud, and possibly out-shined by, new non-relational database technologies.

Välkommen till My CityCloud – en tjänst från City Network. My CityCloud ger dig möjligheten att sköta all din drift i molnet – sk ”Cloud Computing” eller vad som ofta också beskrivs som "elastic computing". Du kan du när som införskaffa mer datorkraft,

diskutrymme eller andra tjänster som ger full flexibilitet och tillåter dig att växa ”on demand”. Du väljer enkelt vilket operativsystem eller plattform du vill jobba med och du betalar bara för det du använder. Det finns inga som helst uppläggningsavgifter eller bindningstider.

Guess what? Almost all capacity changes are foreseeable. If you had done proper capacity planning, you would have had two key advantages:

* You would have added the capacity before it was needed, guaranteeing that the proper capacity is always in place.

* You would have discovered any operational issues with Amazon S3 before they impacted your operations (and thus allow you to take alternative steps to deal with the situation).

Scalr is a fully redundant, self-curing and self-scaling hosting environment using Amazon's EC2.

It allows you to create server farms through a web-based interface using prebuilt AMI's for load balancers (pound, nginx, or Amazon's load balancing service), app servers (apache, rails, others), databases (mysql master-slave, others), and a generic AMI to build on top of.

With the RightScale Cloud Management Platform, you can more easily deploy and manage business-critical applications on the cloud with new levels of automation, control, and portability. Whether you need a fast on-ramp to the cloud or support for complex deployments across multiple clouds, RightScale delivers. Join the thousands of companies using RightScale to manage their applications on the cloud today.

In our benchmarks we were only able to push 35 MB/s on small instances. So the actual requests per seconds were dependent on the object size we were pushing. The limit was always ~35 MB/s. Our typical HTML pages were around 50 to 70 KB, so we couldn’t reach the desired requests per second as our instance was at its bandwidth limit.

Usually when one instance hits its resource limits you load balance multiple ones. HAProxy is a fine example for a very robust TCP/HTTP load balancer. The problem is though, that it will not increase your bandwidth as all your traffic has to go through this one HAProxy instance. So even when you load balance multiple instances, each one is capable of pushing ~35 MB/s (—> ~350 MB/s with 10 small instances), the bottleneck will still be at ~35 MB/s (aka the load balancer).

Saving a custom AMI isn’t too difficult once you know how, but it takes a bit of digging around to find out how all the pieces work. I am going to assume you have an EC2 and S3 account already, know how to bring up an EC2 instance, have your Amazon API Tools installed on your Mac or Linux desktop, have your private and cert key’s installed, and have your aws access key id, aws secret access key, and Amazon account number handy (the account number is under your name on the Amazon account page. It looks like XXXX-XXXX-XXXX).