Why Network Latency Matters for Virtualized Applications

My colleague Russell Skingsley has an interesting take on the effects of latency on virtualized application performance. The purpose of virtualization is to optimize resource utilization. As Russell pointed out it isn’t just an academic conversation. For the cloud hosting provider it’s about revenue maximization. Network latency has a direct impact on virtualized application performance and therefore revenue for the service provider. Your choice of network infrastructure will impact your business, but it can be difficult to see how investing in high performance networking solutions will improve your business. I will try to connect the dots.

Don't Sell it Just Once
It’s a service provider axiom that you don’t want to waste your valuable assets by selling them to a single customer, even at a premium. Take dark fiber for instance, every SP has come to learn that selling a fiber to a single customer will never bring scalable revenues. Making the move to adding DWDM to the service mix allows you to scale up the number of customers and is an improvement over selling dark fiber, but is limited by the number of lamdas that can fit in the spectrum on a single fiber. The scaling is linear. A similar situation exists for shared cloud computing resources.

How the QFabric System Enables a High-Performance, Scalable Big Data Infrastructure

Big Data Analytics is a trend that is changing the way businesses gather intelligence and evaluate their operations. Driven by a combination of technology innovation, maturing open source software, commodity hardware, ubiquitous social networking and pervasive mobile devices, the rise of big data has created an inflection point across all verticals, such as financial services, public sector and health care, that must be addressed in order for organizations to do business effectively and economically.

Analytics Drive Business Decisions
Big data has recently become a top area of interest for IT organizations due to the dramatic increase in the volume of data being created and due to innovations in data gathering techniques that enable the synthesis and analysis of the data to provide powerful business intelligence that can often be acted upon in real time. For example, retailers can experience increased operational margins by responding to customer’s buying patterns and in the health industry, big data can enhance outcomes in diagnosis and treatment.

The big data phenomenon brings up a challenging question to CIOs and CTOs: What is the big data infrastructure strategy?  A unique characteristic of big data is that, does not work well in traditional Online Transaction Processing (OLTP) data stores or with structured query language (SQL) analysis tools.  Big data requires a flat, horizontally scalable database, accessed with unique query tools that work in real time. As a result of this requirement IT must invest in new technologies and architectures to utilize the power of real-time data streams.