Today, organizations likely face the same challenges as many of our large complex accounts. Specifically, they would like to be in a position to anticipate market changes and shifts in customer sentiments or preferences while continuing to not only outpace the competition, but also disruptions in their space.
Companies employ strategies to deliver business value by leveraging the following technologies to engage customers:
Mobile – MDM and MADP (Mobile Device Management and Mobile Application Development Platform)
Big data – including NoSQL, which is sometimes referred to as not just SQL
The goal is to access applications and data from anywhere, globally. No matter the size of the enterprise, companies want to be nimble (if not the most nimble, at least nimble enough to be able to quickly respond to global business trends as they develop).
To do this, organizations need to tap into vast amounts of both structured and unstructured data to provide a competitive edge. The ability to instantly access information at the right time to make effective decisions means that organizations need to be able to manage larger volumes and greater variety of data at a velocity that allows them to stay ahead of trends. The goal is to move beyond intuition and instinct to gather and act upon information of all types (volume and variety), as well as to gather information that allows us to opportunistically adjust the course and speed of business (velocity).
Today we have new methods of IT service delivery, such as cloud. This simplifies how businesses can act in rapidly changing markets by enabling the quick deployment of services at required levels of services. It also provides access to applications and data anywhere through any device, while providing cost-effective scalability.
Likewise, big data and analytics solutions provide our clients with tools to simplify vast amounts of data, yielding insights for rapid decision-making. Big data and analytics allow clients to deliver insights at the highest point of impact, create insights about customer preferences and use near real-time analysis to predict business outcomes.
Software Defined Environments (SDE) enables these solutions
So, what exactly does that mean? Software Defined Environments employ software patterns that better match the power of contemporary workloads with advanced optimized IT resources.
Software Defined Environments drive efficiency by making the connections between workloads and resources more effective (with workloads defined as social, mobile, big data, analytics, supply chain, web and more; software defined infrastructures are defined as compute, storage and network).
Specifically, here are the differences between traditional and Software Defined Environments:
Workloads are typically manually assigned to resources
IT operations manually map the resources for applications for software deployment
Optimization and reconfiguration to reactively address issues are also manual
Software Defined Environments:
Workloads are dynamically assigned
Resources are dynamically assigned based on application characteristics and availability
Software maps resources to the workload and deploys the workload
Analytics-based optimization and reconfiguration addresses infrastructure issues
IBM is working to define the standard for a specific type of Software Defined Environment: private, on-premises cloud infrastructure on the state of the art IBM PureSystems family.
“PureApplication System represents a significant shift in how information technology (IT) environments are built and maintained, in as much as they combine hardware resources, such as compute nodes, network appliances, and storage, with software, including virtualization software, operating systems, middleware, and applications.” (Creating Composite Application Pattern Models for IBM PureApplication System, 2013)
PureApplication System supports private, on-premises cloud environments by offering a built-in platform as a service (PaaS) layer that enables IBM clients to deploy enterprise applications and the underlying middleware within minutes, using the PaaS layer to define topologies and application environments in the form of reusable patterns.
Patterns are abstract models of IT deployments that encapsulate leading practices for installation, configuration and management of middleware and applications. Patterns can be deployed into PureApplication System repeatedly, avoiding the need to provision these environments individually and manually. This allows customers to employ Software Defined Environments based on years of IBM data and best practices.
It is the implementation of these patterns that will allow your organization to dynamically allocate workloads and resources based on application characteristics, providing cost-effective scalability and the ability to opportunistically adjust the scope, course and speed of business.
What are your experiences with Software Defined Environments? Comment below or connect with me on Twitter @GeryMenegaz or follow @IBMSDE to continue the conversation.
Chief Architect – IBM Global Technology Services