At EMCworld 2013, one of the big stories was Pivotal and it’s importance to the EMC2 family and the future of computing. Pivotal is geared to provide the next generation of computing. According to EMC2 have gone past the Client-Server style to a scale-out, scale-up, big data, fast data Internet of Things form of computing. The real question however, is how can we move traditional business critical applications to this new model, or should we? Is there migration path one can take? Continue reading Can you Pivot to Pivotal?
For years we have had an expectation of privacy while using our computers, tablets, phones, email, etc. However, with the advent of big data analysis and everything being on the internet, the internet of things, there is no longer the veil that makes up an Expectation of Privacy. Big Data has allowed us to be tracked in new ways and as we add more devices onto the internet, more of our habits will be tracked: Such as location of boats, planes, your mobile device. Purchasing habits, your location within a store, or theme park. Perhaps even your usage of your toaster, house doors, your refrigerator, etc.
Where do we draw the line? Is there such a thing as personal privacy anymore or do we assume we are being tracked everywhere? When does our social media life end and privacy begin? What is considered to invasive? Continue reading Internet of Things: Expectation of Privacy
Splunk is well known for analyzing data in large volumes either within a local Splunk installation or within the Splunk Storm their cloud service. However, there has been a general lack of security related capability within both these tools. Yes they can correlate some security data, but requires a bit of hands on work to make happen. This has changed with the introduction of Splunk App for Enterprise Security v2.4. They now have some very powerful out of the box analysis for enterprise security and one that could solve a growing issue outlined within the latest Verizon Breach Report: the time it takes to determine a breach actually happened. Continue reading News: Splunk App for Enterprise Security Updated
We recently had a conversation with DataStax regarding their DataStax Enterprise product, which got us to thinking a little about the nature of Big Data and Cloud. DataStax is the company behind the Open Source Cassandra NoSQL database. It provides technical direction and the majority of committers to the Apache Cassandra project. Cassandra in turn is a Column Family-based database along the lines of Google’s BigTable. If you are a SQL programmer it’s determining feature is… it doesn’t do joins. Continue reading DataStax – Three Ways to access the same Big Data
Virtualization and cloud computing are not just innovations that require the support of new environments in existing operations management solutions. Instead, virtualized and cloud based environments are so different from their predecessors that an entirely new management stack will have to be built in order to effectively manage these environments. This new stack will be so different that it will replace, instead of augment the legacy/incumbent management stacks from legacy vendors. This ushers in the era of Big Data Operations Management. Continue reading Big Data Operations Management
On Thursday April 26 VMware announced that it has acquired Cetas, an early stage startup focused upon making access to advanced big data analytics much easier and cheaper. The obvious goal of this is that if you make something easier and cheaper, more of it gets consumed, which then allows more people to benefit from it. 25 years ago, mobile phones were expensive, the size of shoe boxes, and few people could afford to buy them and bother to use them. We all know how ubiquitous mobile phones are now, and this is entirely due to the democratization and commoditization of mobile phone access.
What Does Cetas Do?
Cetas makes it easy to apply advanced self-learning complex event processing technology to random sets of data. Furthermore it is built from the ground up to handle “big data” which means that it is designed to handle large data sets, large amounts of rapidly arriving data, and data that arrives at high rates of frequency (at or near real time rates). VMware thinks that Cetas is good for three primary uses cases shown in the diagram below.
There are two very interesting problems that VMware could potentially address with Cetas. The first is that doing analytics at cloud scale (think of trying to analyze data about every virtual server at Amazon at the same time) is clearly a big data problem, and a challenging problem purely on the front of making the analytics work and be easy to use with data sets of that size.
The second has to do with Operational Performance and Application Performance data. Right now VMware collects data from its hypervisor at 20 second intervals and rolls that up into 5 minute intervals for access via the vSphere API. These intervals are too long, and the rollups obscure too much data, but until now VMware has not had any way to analyze the data to make it more useful. Cetas therefore can potentially solve problems that apparently the Integrien technology that VMware purchased a couple of years ago is not suited to address.
How is Cetas Deployed
Cetas is available as a cloud resident service (analytics as a service), or as an on-premise solution.
When we look back five years from now, we will probably conclude that the Cetas acquisition was one of the most significant acquisitions that VMware did. The Cetas technology is going to bring real time self-learning analytics to several layers of VMware’s management offerings over time. As soon as VMware gets into the business of producing and analyzing real time, continuous and deterministic management data the final nail will be driven in the legacy management solutions that sample and operate at 5 minute intervals.