Not all major changes are visible to the naked eye. Standing next to a glacier it is difficult to determine direction (does it grow or shrink across seasons) and watching continents move takes even some stamina for the casual observer. Luckily this is not the case for cloud computing.
Apart from the very noticeable cloud hype (more on the cycle of that soon) there is also very noticeable growth. At the end of a deep and wide group effort, Gartner published its “Forecast: Public Cloud Services, Worldwide, 2010-2016, 2Q12 Update” accompanied by Market Definitions and Methodology: Public Cloud Services. As I highlighted several years ago in Can the Real Cloud Market Size Please Stand Up? definitions are all important when trying to compare various cloud forecasts and especially cloud forecast categories.
According to Dan Vesset, program vice president for IDC’s Business Analytics Solutions, the business analytics software market “has crossed the chasm into the mainstream mass market.”
In 2011, Vesset explains, the business analytics market extended its post-2009 recovery with another stellar performance by growing worldwide revenues 14.1% year over year.
International Data Corporation forecasts, in fact, that it will continue to grow at a 9.8% compound annual growth rate (CAGR) through 2016 to reach $50.7 billio
Cloud security and cloud encryption are a significant challenge for any organization migrating to the cloud. Deploying proper cloud encryption while maintaining control of the encryption keys is an issue we’ve covered in previous blogs as well as in this whitepaper. But when it comes to big data, there are several additional challenges.
ActiveState has announced the general availability of Stackato 2.0, the application platform for creating a private Platform-as-a-Service (PaaS). The private PaaS solution now supports .NET applications, offers web-based visual cluster management and delivers performance improvements that foster enterprise development agility. In conjunction with the release, ActiveState also announced a Stackato enterprise customer relationship with Aeroflex.
According to Bart Copeland, CEO at ActiveState, “Stackato 2.0 redefines private PaaS for the enterprise, enabling more agile development, greater DevOps transparency, more efficient cloud management and faster time to market.”
The Stackato 2.0 release extends Stackato’s market leadership in PaaS polyglot compatibility. Enterprises can now deploy .NET applications to Stackato via technology integration with the Iron Foundry platform: Stackato’s automatic configuration tool links with Iron Foundry to support .NET apps in a Stackato PaaS cloud. In addition to .NET, Stackato supports applications coded in enterprise development languages like Java, Ruby, Python, Perl, PHP, Node.JS, Clojure, Scala, Erlang and more.
Cloud computing is bringing massive computing power once reserved for government and research institutions to every organization in the world. Problems that involve intensive calculations or simulations can benefit from the computing capabilities that the cloud provides. Whether through scale out architectures like Grid / Cluster / Hadoop or completely new approaches like GPU there are a variety of emerging high performance computing options coming to the cloud.
In his session at the 11th International Cloud Expo, Dan Rosanova, Senior Architect at West Monroe Partners, will describe the problem spaces and architectural techniques that are well served by cloud based high performance computing.
In his session at the 11th International Cloud Expo, Ronald Bradford, Founder & CEO of Effective MySQL, will discuss the issues of managing a large number of MySQL instances supporting one billion+ requests statements per day (and 50+ billion SQL statements). Topics include:
Monitoring and instrumentation are essential
How to automate installations, upgrades and deployments
MySQL replication issues with 300+ slaves per master
Traffic minimization techniques
Creating HA with regions and zones Real-time traffic stats (aggregated every 5 seconds)
AWS specific optimizations with EBS
Considerations with RDS
CumuLogic has announced the release of their Cloud Application Platform. The software allows Service providers to deploy Java PaaS solutions at their data centers.
This week has seen announcements from two companies I’ve been interested in and following for some time.
Nasuni makes a storage appliance that stores all of a customer’s data in “the cloud”. It’s available either as a physical device (effectively a server running their software) or as a virtual machine. What makes their product interesting is that both the data and filer configuration reside on the cloud and can be reconstituted anywhere if for some reason the filer is lost (for example if the appliance is down or power was lost). The only piece of data the customer needs to retain are the encryption keys to re-enable a new image of the filer. A physical filer can even be reconstituted into a virtual one. There’s a lot more to the product than this and I have it on long term trial in the lab (so expect a fuller review soon), however this week’s announcement relates to enhancements that bring block (in the form of iSCSI) to their existing file offering. What this means is a branch office could host both file data and store data on (say) virtual machines sitting on a Nasuni iSCSI LUN datastore.
One of the critical requirements for enterprises to adopt Cloud is the Hybrid capability. Since most of the mission critical applications live behind the firewall, they should be able to extend the functionality of these applications to the Cloud.
Since the initial announcement of Windows Azure, Microsoft has been constantly investing in hybrid features. I want to highlight some of the scenarios that are ideal candidates for the Windows Azure Hybrid Cloud.
Imagine a scenario where the e-Commerce storefront running on the public domain needs to check the customer data in an internal CRM to apply the right level of discount before each checkout. The CRM application is a homegrown line of business application developed in .NET. The business logic is already exposed through a set of service endpoints that is consumed by the frontend. Now, making these endpoints accessible to the storefront application running on the Cloud is a challenge. The IT team will not approve opening additional ports to enable communication over the public Internet. This is exactly where Windows Azure Service Bus will come to the rescue. The Service Bus relay features is designed for the use-case of taking existing Windows Communication Foundation (WCF) web services and making those services securely accessible to solutions that reside outside the corporate perimeter without requiring intrusive changes to the corporate network infrastructure. Such Service Bus relay services are still hosted inside their existing environment, but they delegate listening for incoming sessions and requests to the cloud-hosted Service Bus. By enumerating the CRM endpoints on the Service Bus, the storefront application will be able to invoke the business logic as if it is running natively on the Cloud. This feature makes it easy to extend the on-premise LOB application’s business logic to the Cloud.
In my previous blog, I wrote at length about the complexities of running a data cloud in production. This logical data set, spread across many nodes, requires a whole new set of tools and methodologies to run and maintain. Today we’ll look at one of the biggest challenges in managing a data cloud – monitoring.
Database monitoring used to be easy in the days before data clouds. Datasets were stored in a single large database, and there were hundreds of off-the-shelf products available to monitor the performance of that database. When problems occurred, one had simply to open up the monitoring tool and look at a set of graphs and metrics to diagnose the problem.
There are no off-the-shelf tools for monitoring a data cloud, however. There’s no easy way to get a comprehensive view of your entire data cloud, let alone diagnose problems and monitor performance. Database monitoring solutions simply don’t cut it in this kind of environment. So how do we monitor the performance of our data cloud? I’ll tell you what I did.