Today, we are excited to welcome Cloudera officially to the VMware family. VMware and Cloudera have entered into a partnership agreement that is meant to help users of Cloudera’s Hadoop distribution, CDH4, to run in the cloud. As part of this announcement, VMware has tested and certified Cloudera’s Enterprise Big Data software to run on vSphere 5.1 and that Cloudera is now part of the VMware Ready and Technical Alliances Partner (TAP) program.
This month at EMC World, VMware CEO Pat Gelsinger stated that over 500,000 Hadoop installations exist today on bare metal servers, with compute and data tied to the same physical server. By breaking compute and data apart, and putting it on fast-to-deploy vSphere virtual machines, big data becomes inherently more accessible, compute times can improve by up to 13%, and datacenters can optimize to provide more types of data services without adding more hardware.
It comes at a time where both the volume of data is exploding and, according to PwC’s 5th Annual Digital IQ Survey, 83% of their top performing companies believe that harnessing Big Data will give their firms a competitive advantage. As such, many CIOs are formally aligning their agenda to invest in big data this year. Continue reading
Whenever we’ve dealt with something for a while, our way of thinking about it becomes a habit. Hadoop deals with a lot of data. Currently, the record is 100 petabytes in a Facebook cluster that analyzes log data. Since it was built by the likes of Google and Facebook to deal with such large data volumes and performance, it originally was built to run on bare-metal servers. Since it wasn’t an option from the get-go, the notion that you can’t have that much data running on a move-able virtual machine safely has largely gone unchallenged.
However, as time has gone on, and technology has allowed for persistent storage on the cloud, organizations have started to rethink this paradigm. In fact, several companies are using Hadoop and big data today to gain competitive advantage. And while they are running it on virtualization, they are not moving the data. There are other advantages.
VMware’s Big Data product line marketing manager Joe Russell, spoke with Roberto Zicari this week in an interview on ODBMS.org that helps articulate why Hadoop not only can run on virtual infrastructure using Project Serengeti, but why companies should consider it to save time and make Hadoop more usable. Continue reading
RabbitMQ 3.1.0 is now available for immediate download.
Announced this morning on the new Pivotal blog, where RabbitMQ now resides, this version includes enhancements to garbage collection, consumption, requeuing, memory use, and dead lettering.
For those on Mac OS X, there is a newly packaged, standalone release of RabbitMQ that doesn’t require a separate Erlang install.
Some key, new capabilities include eager synchronisation of mirror queue slaves, automatic cluster partition healing, and improved statistics (including charts) in the management plugin. There are also many enhancements and bug fixes to the server, Java client, Erlang client, and a number of other plugins, including federation, old-federation, shovel, Web-STOMP, STOMP, and MQTT plugins, as well as the consistent hash exchange.
RabbitMQ’s blog post on the topic shares screenshots of several new features like the ones for new charts and filters below: