IDG Contributor Network: An under-pressure OpenStack gets support from an (in)famous individual

Last week saw a few thousand devoted OpenStack community members flock to Boston to take part in the bi-annual OpenStack Summit. This summit marks a major turning point for the initiative. Since we all congregated in Barcelona last year, there have been some major pieces of news which have rocked the community. Only a couple of weeks before the event, Intel pulled out of a partnership with Rackspace to build an OpenStack-based test facility, and OpenStack poster boy Mirantis pivoted from a pure OpenStack strategy to one covering a number of open source initiatives.

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Computerworld Cloud Computing

Amazon’s Alexa gains support for Outlook calendars

Users of Amazon’s Alexa virtual assistant can now ask it questions about the contents of their Microsoft-hosted calendars. On Wednesday, the assistant gained the ability to interact with calendars from Outlook.com and Office 365, similar to how it works with Google Calendar.

Amazon didn’t make an announcement for the new feature. When asked about the change, a company spokesperson said that it was designed to only work with personal calendars.

That said, it was possible for me to connect my Office 365 calendar, which is provided through an enterprise subscription. When asked about what’s on my schedule, Alexa answered with the contents of my work calendar. It’s unclear if Amazon plans to continue supporting that functionality, and it may break at any time.

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Computerworld Cloud Computing

IDG Contributor Network: Mirantis to offer commercial support for OpenContrail SDN platform

As Mirantis is moving away from the ‘pure-play OpenStack company’ tagline, it’s adding more managed services to its resume to take on players like RackSpace and AWS. Mirantis is now offering commercial support for OpenContrail, an extremely popular software-defined networking (SDN) platform used with OpenStack.

There are three core components on any cloud: compute, storage and networking. Networking is becoming a very interesting field as companies like AT&T are betting big on OpenStack and software-defined networking to build their networks.

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CIO Cloud Computing

MariaDB adds support for big data analytics

MariaDB today moved to unite transactional and analytical processing in a single relational database with the announcement of the general availability of its open source MariaDB ColumnStore 1.0.

“What we’re offering is a single SQL interface for both OLTP and analytics,” says David Thompson, vice president of Engineering at MariaDB.

“MariaDB ColumnStore is the future of data warehousing,” Aziz Vahora, head of Data Management at Pinger, a specialist in mobile communication apps, added in a statement today. “ColumnStore allows us to store more data and analyze it faster. Every day, Pinger’s mobile applications process millions of text messages and phone calls. We also process more than 1.5 billion rows of logs per day. Analytic scalability and performance is critical to our business. MariaDB’s ColumnStore manages massive amounts of data and will scale with Pinger as we grow.”

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CIO Cloud Computing

AWS Lambda adds C# support

AWS Lambda, Amazon Web Services’ event-driven compute service in the cloud, is adding support for Microsoft’s C# language.

Using the .Net Core 1.0 runtime, developers can build AWS Lambda functions using C#. “The easiest way to get started is with the AWS Toolkit for Visual Studio, which includes project templates for individual C# Lambda functions, full C# serverless applications, and also tools to publish both projects types to AWS,” Amazon said in a bulletin on Thursday morning.

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InfoWorld Cloud Computing

SAP sees cloud, support revenue overtaking software in 2018

German business software maker SAP expects its revenue from cloud subscriptions and support to be higher than its revenue from software licenses in 2018, reflecting an industry trend.

This would be a dramatic shift for a company, which earlier had licenses and support of its business software as its mainstay business. There was considerable skepticism whether it would be able to quickly make the transition to the cloud with a new revenue model based on subscriptions rather than one-time payments. 

The market has moved significantly for SAP and its rivals like Oracle from on-premise software and services to applications delivered through the cloud on a subscription model.

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Network World Cloud Computing

SAP sees cloud, support revenue topping software by 2018

German business software maker SAP expects its revenue from cloud subscriptions and support to be higher than its revenue from software licenses in 2018, reflecting an industry trend.

This would be a dramatic shift for a company, which earlier had licenses and support of its business software as its mainstay business. There was considerable skepticism whether it would be able to quickly make the transition to the cloud with a new revenue model based on subscriptions rather than one-time payments. 

The market has moved significantly for SAP and its rivals like Oracle from on-premise software and services to applications delivered through the cloud on a subscription model.

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Computerworld Cloud Computing

IBM Strengthens Effort to Support Open Source Spark for Machine Learning

Spark 300x251 IBM Strengthens Effort to Support Open Source Spark for Machine LearningIBM is providing substantial resources to the Apache Software Foundation’s Spark project to prepare the platform for machine learning tasks, like pattern recognition and classification of objects. The company plans to offer Bluemix Spark as a service and has dedicated 3,500 researchers and developers to assist in its preservation and further development.

In 2009, AMPLab of the University of Berkeley developed the Spark framework that went open source a year later as an Apache project. This framework, which runs on a server cluster, can process data up to 100 times faster than Hadoop MapReduce. Given that the data and analyzes are embedded in the corporate structure and society – from applications to the Internet of Things (IoT) – Spark provides essential advancements in large-scale data processing.

First, it significantly improves the performance of applications dependent data. Then it radically simplifies the development process of intelligence, which are supplied by the data. Specifically, in its effort to accelerate innovation on Spark ecosystem, IBM decided to include Spark in its own platforms of predictive analysis and machine learning.

IBM Watson Health Cloud will use Spark to healthcare providers and researchers as they have access to new health data of the population. At the same time, IBM will make available its SystemML machine learning technology open source. IBM is also collaborating with Databricks in changing Spark capabilities.

IBM will hire more than 3,500 researchers and developers to work on Spark-related projects in more than a dozen laboratories worldwide. The big blue company plans to open a Spark Technology Center in San Francisco for the Data Science and the developer community. IBM will also train Spark to more than one million data scientists and data engineers through partnerships with DataCamp, AMPLab, Galvanize, MetiStream, and Big Data University.

A typical large corporation will have hundreds or thousands of data sets that reside in different databases through their computer system. A data scientist can design an algorithm using to plumb the depths of any database. But is needs 90 working days of scientific data to develop the algorithm. Today, if you want to implement another system, it is a quarter of work to adjust the algorithm so that it works. Spark eliminates that time in half. The spark-based system can access and analyze any database, without development and no additional delay.

Spark has another virtue of ease of use where developers can concentrate on the design of the solution, rather than building an engine from scratch. Spark brings advances in data processing technology on a large scale because it improves the performance of data-dependent applications, radically simplifies the process of developing intelligent solutions and enables a platform capable of unifying all kinds of information on real work schemes.

Many experts consider Spark as the successor to Hadoop, but its adoption remains slow. Spark works very well for machine learning tasks that normally require running large clusters of computers. The latest version of the platform, which recently came out, extends to the machine learning algorithms to run.


CloudTimes