Anaconda, Hadoop, and OpenStack
IBM is working with Continuum Analytics to offer the latter’s Anaconda open data science platform as part of IBM’s Cognitive Systems. Anaconda will also integrate with IBM’s PowerAI software for machine learning and deep learning.
Hadoop, while it may be synonymous with big data, and while it may be free to access and work with, engineering teams globally will admit that behind every Hadoop undertaking is a major technical delivery project.
Failures are so commonplace that even the experts don’t have great expectations of 2017: at the recent Gartner Data & Analytics Summit in Sydney, research director Nick Heudecker claimed that 70% of Hadoop deployments in 2017 will either fail to deliver their estimated cost savings or their predicted revenue.
In my keynote address a year ago at the OpenStack Summit Austin, I offered the OpenStack community an ultimatum. First, I described how our world was exploding with connected devices (50 billion by 2020) and that 400 million new servers would be needed to process and store that data, which creates a massive challenge for those of us in the infrastructure business. How will we meet the needs of users at that scale?
That time again, when members of the OpenStack community vote on the release name for the upcoming series of milestones. The current release is called Ocata, the next release is code named Pike and is set to debut August 28.