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CCI

Johan den Haan explains how rapid application delivery platform as a service RAD PaaS will fundamentally transform enterprise app delivery and why it will do for your business what the App Store did for become as useful as the iOS app store

The year old Accenture Cloud Platform gets new additions to help businesses to manage and analyse their cloud solutions of and on premise and across multiple clouds 

The first HP Helion cloud solutions are now available and include a complete HP OpenStack solution, a development platform, an object storage solution and full certifications and support systems

Tom Homer explains why not all service providers are created equal, and why businesses should look for a service provider that meets their infrastructure needs now and into the future.

Powered by Oracle's latest generation SPARC hardware platform, CloudSigma brings its infrastructure-as-a-service approach to Solaris

Jeffrey Lyon looks at some of the ways to combat DDos attacks on your cloud real-estate

Businesses should dump their software licenses and their support contracts and move to the cloud, says Kevin Linsell

Disaster Recovery as a Service (DRaaS) is the most popular business continuity and disaster recovery cloud based solution for businesses, with security still the number one criteria for picking a cloud service

IBM and Intel bring new security features to the cloud have got together to add security to their solutions down to a chip-level to boost hybrid cloud deployments

Friday, 29 August 2014 16:37

Public cloud and the case for encryption

We take a detailed look at the need for cloud encryption at rest and in transit and analyse some of the solutions currently available on the market   

Figures from a new Citrix worldwide survey of Desktop-as-a-Service (DaaS) and other hosted mobile workspace providers show a move away from public cloud delivery to a more low level delivery.

 

The successful attempt by VMware to keep ahead of the Iaas and Paas cloud vendors, vCloud Hybrid Service, is getting anunexpected name change.

New benchmarking studies reveal how businesses running NoSQL databases can get up to 60% more performance from any existing IT infrastructure with a few minor tweaks

This month sees the opening of the first UK SoftLayer data centre to supply infrastructure as a service solutions to the UK and European market

The latest release of Flexiant’s Cloud Orchestrator V4.2 includes deep integration with Parallels and extends its software defined networking (SDN) capabilities through VMware

Adapts’ Kevin Linsell, explains why those considering disaster recovery solutions need to be prepared to strike the right balance between cost and necessity.

Bare metal servers are the hot topics at the moment when you need raw performance power and complete flexibility. Adam Weissmuller looks at why businesses are looking at Infrastructure as a service when a bare metal approach will give five times the performance and twice the efficiency. 

There are staggering failure rates across 'tech giant' IaaS implementations and the support and functionality required for an effective solution just isn’t there yet

Figures show that IaaS customers are regularly over specifying servers that are less than 50% utilised and consequently are over paying by around a billion pounds a year

A new API-driven server solution from Rackspace will deliver single tenant bare-metal servers that can be spun up as quickly as VMs with all the speed and flexibility of a dedicated hosted server.

Why businesses need a clear and thorough strategy if they want rewards and a return on investment rather than cloud chaos.


Businesses and service providers can now rapidly deliver cloud infrastructure with a new orchestration and virtualisation solution from Flexiant and Parallels


One challenge that IT decision makers face is choosing a cloud solution that can meet workload and performance requirements in the most cost-efficient manner. Even though industry hype suggests that enterprises should move everything into the cloud, the best solution is often a hybrid one.

Brinkster selects Flexiant Cloud Orchestrator to expand existing cloud business and open new revenue opportunities

Government is making good progress on the cloud-first policy with a strong take up on Infrastructure as a services however the levels of service supplied are significantly under-performing with the majority of users being disappointed with the results.

OpenStack Action 5 conference is on next week in Paris and is looking for Europe's leading OpenStack contributors and visionaries to participate

IBM launches the first System z-based IBM Enterprise Cloud System, offering 50% cost reductions on X86 server solutions and aimed at ISPs and businesses who need to run thousands of virtual servers.


Google have announced a plethora of new products and services to their Google Cloud Platform including bringing together their PaaS and IaaS platforms, Managed Virtual Machines for App Engine, real-time Big Data analytics with Google BigQuery, Google Cloud DNS and some heavy price cutting across the board.

Tuesday, 18 March 2014 14:57

Putting business analytics in the Cloud

Nuno Godinho, Director of Cloud Services, Europe for Aditi Technologies discusses how cloud technologies can enable business analytics and big data.

Ever heard of data scientists?  Well the Harvard Business Review named it the sexiest job of the 21st Century and it is has quickly risen to prominence in a number of industries including retail, oil and gas, telecommunications and financial services.  So what has this got to do with cloud?  Should we all be packing up our RESTful APIs and retraining? Not at all.  Before looking at what the cloud has to offer the data scientist and IT departments that work with them, lets have a quick dash through history and give an explanation of the role.

Analysing data with computers has gone through a number of significant changes over the years, from looking at raw numbers by hand, to spreadsheets, Business Intelligence and, more recently, visualisations and complex real-time predictive analytics.  One thing that has largely been consistent throughout that period has been the data and analysis taking place on-premise.  For a long time this was down to technical reasons, but now that has been overcome with many vendors offering PaaS and SaaS versions of their tools and platforms, which means most of the barrier can be put down to the commercial sensitivity of data and it going outside the firewall.  Will the service be reliable, safe from hackers, and adequately protected with encryption etc?

Extracting deep meaning from your cloud data

In terms of the data scientists themselves, in truth this role has been around for a long time.  Essentially it boils down to extracting deep meaning from data.  However, the key to doing it is understanding the data itself – not just the results – the raw data, its sources, formats and relationships and then combining this with strategies to analyse the data, from descriptive and prescriptive to predictive perspectives.  The data scientist has to have a mind that combines analytic, business and IT skills.  Previously representatives from these departments would (read might) have worked to generate the required analysis normally leveraging some kind of data warehouse tool.

Traditional business intelligence, reviews and presents historic data, whether that is two-seconds or two-years old.  For years analysts have been taking those same datasets and using them to built prescriptive models that describe the relationships between the data elements and how the numbers interact together.  But the latest frontier is real-time predictive analytics: using those models to predict (for example) an action, value or preference.  Usually an event, such as an attempted credit card transaction, triggers a model to be run against the transaction details to determine the chances of whether it could be fraudulent, or to make recommendations for other products an online shopper might like.  In financial services trading floor systems make thousands of these predictions a second to assess stock movements.

Using raw cloud compute for big data analytics

So where can the cloud fit into all this, and should it? The answer is, the cloud can be of benefit throughout the process of collecting and getting data to the point that it can be used in predictive analytics.  Firstly, it can be an aggregation point.  If your data sources are sensors distributed across an oil field, or even mobile such as truck geo-location data, the cloud can be the point where all those resources are brought together into a single data source for further processing.

Raw compute power from the cloud can also be used to process the big data associated with predictive analytics.  Creating models can be an intensive task depending on the size of the data sets, if you don’t actually need to do this often, why make the capital investment when you can just buy the machine time?

The cloud can also be used to enrich your data sets, by providing additional data sources for your models.  There are hundreds if not thousands of sources that can enhance your data, whether you need traffic data, government information, or simply temperature data.  These sources are validated, reliable and can substantially improve the quality of your models, whilst reducing the costs.

Does your cloud infrastructure match your needs?

The cloud can of course be responsible for the predictive analysis itself and it is at this point more than any other that you have to consider how quickly you need the results and whether speed and reliability demand you have the infrastructure on-site.  For example if you are making thousands of transactions a second that rely on predictive analytics, and the internet connection to your cloud provider is lost – what happens?  You may be able to switch to a back-up line, but how long does it take and what is the impact?

Data Scientists and IT departments alike should not ignore the role that the cloud can play in any analytics scenario.  That is not to say that it right for all of them, but as we have explained above, there are a number of ways that cloud computing can play a role, it doesn’t have to be all or nothing.  It can enhance models, lower costs and give smaller companies access to intelligence that they would otherwise not be able to afford.  Basically in order to do these kinds of activities and analysis we require huge amounts of compute power and storage space. This is why the cloud is the perfect partner for big data.

So, to say ‘No’ outright is to deny yourself the possibility of improving or simplifying the way in which analytics is executed in your company.

About Nuno

Nuno Godinho @NunoGodinho is a Windows Azure MVP and Director of Cloud Services, Europe for Aditi Technologies.

He has been an MVP for the last six years, first as an MVP in ASP.NET and the last three years as a Windows Azure MVP.  His is also a speaker at some of Microsoft's key events such as TechEd North America, TechEd Europe, Tech Days Worldwide Online, TechDays Netherlands and at other community events such as GASP - Grupo de Arquitectura de Software Português, Windows Azure UK User Group, Azure BE UG and so on. He is a prolific blogger and community creator.

Saturday, 11 January 2014 17:00

Predicting the cloud in 2014

Stefan Haase, Product Director at Cloud and IT services provider, InTechnology discusses what’s going to happen to the cloud market in 2014

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