Monthly Archives: October 2016

The Public Cloud – A Two Horse Race

Amazon Web Services – AWS, the public cloud pioneer with its first mover advantage is safely perched on top of the heap with 31% of the market share (this is for Q4 of 2015 for which numbers are publicly available). But going by the way Microsoft with its Azure is notching up numbers, the race between AWS and Microsoft Azure will be a two horse race in a year or two.

AWS, it seems is not sitting smug in its lead; in its bid to entice new customers and hold on the existing ones it has continually added newer services to already existing array of infrastructure as a service (IaaS) and platform as a service (PaaS) features. The recent example being AWS application discovery service which helps its users and system integrators with migration plan for applications. But interestingly AWS has dropped its prices to hold on to the lead raising fears of long term financial detriments.

Microsoft Azure in its quest to leverage its large base of on–premise technologies, is focusing on providing strong management and consistent user experience across platforms. This has rightly played into the enterprises interest to minimize vendors and systems thus creating loyal base of customers whom when fully converted may tip the race in its favor for Microsoft.

Another interesting facet of this race is the contrasting approaches of the competitors to cloud computing, while AWS relies on delivering value added services to its small and medium customers with emphasis on automation and scalability, Microsoft Azure is focusing on integration services between on premise technologies and its public cloud to leverage on its large enterprise customers.

These two leaders who have left the others players to grab the crabs are still to overcome certain challenges to safe –guard their leadership positions, AWS has to overcome the perception of its services being complex and pricing complicated. Microsoft Azure has to effectively counter the dearth of Azure cloud experts and perception that many of its features and functionalities are not ready to be used by very large customers.

For more on this read – The AWS vs. Azure race isn't over yet ( link - cloud-race/)

Tags: Amazon Web Services, Microsoft Azure, AWS, Cloud Computing

MILK – A New Language for Memory Management

It was always known that memory management was a challenge in the traditional systems where a few data points are in the play slowing down the process; this challenge becomes insurmountable when one deals with Big Data. MIT has recently announced a new programming language – MILK, which increases the speed of the common algorithms by 4x. This is believed to help in memory management and especially when we have Big Data playing a prominent part in the technologies of today.

The major reason for the clog in the performance is the need to retrieve data from the main memory of today’s chip and having to do this repeatedly slows down execution. Since memory management works on the principle of locality which assumes a program not only requires a particular portion of data stored in distant memory but may also require the neighboring portions as well. Thus slowing the process considerably. In Big Data however this does not play, it is usually the need to retrieve few datapoints scattered over huge data sets.

The new language MILK developed by MIT’s Computer Science and Artificial Intelligence Laboratory helps application developers to manage memory more efficiently. Application developer, using MILK, adds a few lines of code to any instructions written to retrieve a few data points scattered across huge data sources. MILK compilers then resolve to manage the memory management accordingly.

According to MIT, the programs written in MILK were four times faster than those written in existing languages, and ran on some common algorithm and promised that this will only get better as lot more research is envisaged to fine tune the technology further.

For more on this please read this article by Katherine Noyes @ programming-language- promises-a-4x-speed- boost-on- big-data.html

Tags: MILK, Big Data, Memory Management