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Nati Shalom
CTO and Founder of GigaSpaces
Recent Activity
One thing that I like about working with an open source community like OpenStack is that you get direct access not just to the source code itself, but to its users and ecosystem as well. This allows you to be... Continue reading
Posted Oct 13, 2014 at Nati Shalom's Blog
OpenStack Silicon Valley is just a few short weeks away and we are looking forward to talking OpenStack with the local community. A main focus for Team Cloudify at the event will be around the topic of portability AKA hybrid... Continue reading
Posted Oct 13, 2014 at Nati Shalom's Blog
OpenStack is just not like any other cloud. OpenStack is an open source cloud and that makes it quite unique in comparison to many of the closed source public clouds generally available today, the most common being AWS, Azure GCE,... Continue reading
Posted Oct 13, 2014 at Nati Shalom's Blog
Cloudify OpenStack Native approach - The Story behind the Scenes In the previous post I outlined what I mean by native-approach to the OpenStack cloud. In a nutshell, a native approach represents out of the box tighter integration with OpenStack,... Continue reading
Posted Oct 13, 2014 at Nati Shalom's Blog
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Many APIs, Same Data In “The Seven Most Popular APIs in Big Data—Part One,” I described the various forms of popular data management APIs out there and how they’re often used. As I noted toward the end of the post,... Continue reading
Posted Oct 7, 2014 at Nati Shalom's Blog
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Part One: An Overview of the Current Situation It was only a few years ago when nearly everyone relied on SQL exclusively to tackle Big Data needs, but as the demand for speed and space increases, so have our options.... Continue reading
Posted Oct 6, 2014 at Nati Shalom's Blog
“You just can't have it all” is a phrase that most of us are accustomed to hearing and that many still believe to be true when discussing the speed, scale and cost of processing data. To reach high speed data... Continue reading
Posted Jul 30, 2014 at Nati Shalom's Blog
The big data movement was pretty much driven by the demand for scale in velocity, volume, and variety of data. Those three vectors led to the emergence of a new generation of distributed data management platforms such as Hadoop for... Continue reading
Posted Jul 24, 2014 at Nati Shalom's Blog
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OpenStack Orchestration Moves up the Stack OpenStack Icehouse, the Ninth OpenStack Release, was announced at at the last summit and was named for a street in Hong Kong. The Icehouse release is primarily focused on stability and maturity. The release... Continue reading
Posted May 11, 2014 at Nati Shalom's Blog
In his book Taste Test, Matt Jaynes compares a few popular configuration management tools such as Chef, Puppet, SaltStack and Ansible. Jaynes points to some of the areas of complexity within Chef in comparison to Ansible. According to Jaynes, Chef’s... Continue reading
Posted May 8, 2014 at Nati Shalom's Blog
Most of the Big Data topics that I covered in the past were focused mostly on the technical aspects of running Big Data. In this post, I want to take a different route and discuss the business challenges based on... Continue reading
Posted Apr 9, 2014 at Nati Shalom's Blog
In my previous post I discussed the evolution of networking in the cloud - from commodity hardware to the cloud, and the need for the virtualization of network functions, and the different drivers for change. In this post I will... Continue reading
Posted Mar 12, 2014 at Nati Shalom's Blog
I first heard the term NFV a year ago as part of the writeup that I was doing with Alcatel Lucent on CloudBand titled Carrier Grade PaaS covering our collaboration. Ever since that time it looks like the term has... Continue reading
Posted Feb 19, 2014 at Nati Shalom's Blog
In the world of relational databases, MySQL and Oracle RAC (Real Application Cluster) own a significant segment of the market. Oracle RAC owns the majority of the enterprise market, while MySQL gained significant popularity amongst many of the Web 2.0... Continue reading
Posted Feb 3, 2014 at Nati Shalom's Blog
Fixed - thanks!
1 reply
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In a stream processing model, data is processed as it arrives to the Big Data system. With a batch processing model, only once the data is stored does the system run a variety of batch analytics - typically through a... Continue reading
Posted Dec 15, 2013 at Nati Shalom's Blog
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Prediction has always been a fun exercise. It forces you to take a step back from your day to day activities, look at the market "crystal ball" and figure out what the future looks like. This year I found this... Continue reading
Posted Dec 6, 2013 at Nati Shalom's Blog
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The number of open source frameworks that are available today is continuously growing at an enormous pace, with over 1 million unique open source projects today, as indicated in a recent survey by Black Duck. The availability of these frameworks... Continue reading
Posted Nov 21, 2013 at Nati Shalom's Blog
Alex Freedland, Co-Founder and Chairman at Mirantis, wrote a controversial post in which he basically marks the breakup between some existing PaaS frameworks and OpenStack - CloudFoundry specifically. Personally, I think that Freedland highlights a growing sentiment in the OpenStack... Continue reading
Posted Oct 30, 2013 at Nati Shalom's Blog
Matt Jaynes, Founder of DevOps University, wrote a great post on Hacker News, What is Continuous Deployment, in which he points out one of challenges that many people gloss over when they embark on their DevOps journey. In a nutshell,... Continue reading
Posted Oct 27, 2013 at Nati Shalom's Blog
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Quite often, we get caught in the technical details of these discussions and lose sight of what this all really means. If all you are looking for is to collect data streams and simply update counters, then both approaches would work. The main difference between the two is felt in the level and complexity of processing that you would like to process in real-time. If you want to continuously update a different form of sorted lists or indexes, you’ll find that doing so in an event-driven approach, as is the case of Twitter, can be exponentially faster and more efficient than the logging-centric approach. To put some numbers behind that, Twitter reported that calculating the reach without Storm took 2 hours whereas Storm could do the same in less than a second. Such a difference in speed and utilization have a direct correlation with the business bottom line, as it determines the level and depth of intelligence that it can run against its data. It also determines the cost of running the analytics systems and, in some cases, the availability of those systems. When the processing is slower there would be larger number of scenarios that could saturate the system. Continue reading
Posted Oct 13, 2013 at Nati Shalom's Blog
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There’ve been various discussions in the community on OpenStack Interoperability and Portability. The discussions tend to be centralized around the future of the OpenStack API and whether or not it would make sense to support the AWS API on top... Continue reading
Posted Sep 10, 2013 at Nati Shalom's Blog
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Randy Bias CTO of Cloud Scaling sparked an interesting debate around the need of OpenStack to align itself with major public cloud offering, namely Amazon and Google clouds. According to an interview on GigaOM the timing behind Randy's proposal is... Continue reading
Posted Jul 29, 2013 at Nati Shalom's Blog
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OpenStack was first announced three years ago at the OSCON conference in Portland. I remember the first time I heard about the announcement and how it immediately caught my attention. Ever since that day, I have become a strong advocate... Continue reading
Posted Jul 16, 2013 at Nati Shalom's Blog
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Peter Chadwick Senior Product Manager - Cloud Infrastructure at SUSE wrote an interesting article arguing Why OpenStack Will Rule the Enterprise. Chadwick refers to three main points in his arguments: Variety - OpenStack is the only cloud platform that supports... Continue reading
Posted Jul 14, 2013 at Nati Shalom's Blog