“The foundation of digital business is the boundary-free enterprise, which is made possible by an array of time- and location-independent computing capabilities – cloud, mobile, social and data analytics plus sensors and APIs. There are no shortcuts to the digital enterprise.”
— Mike West,Analyst,Saugatack Research 2015
At its core Digital is a fairly straightforward concept. It is essentially about offering customers more contextual and relevant experiences while creating internal teams that can turn on a dime to serve customers. It is clear that these kinds of consumer capabilities just cannot be offered using an existing technology stack. This blogpost seeks to answer what this next generation computing stack may look like.
What Digital has in Store for Enterprises…
Digital transformation is a daily fact of life at web scale shops like Google, Amazon, Apple, Facebook and Netflix. These mega shops have built not just intuitive and appealing applications but have gradually evolved them into platforms that offer discrete marketplaces that serve global audiences. They also provide robust support for mobile applications that deliver services such as content, video, e-commerce, gaming etc via such channels. In fact they have heralded the age of new media and in doing so have been transforming both internally (business models, internal teams & their offerings) as well as externally.
CXOs at established Fortune 1000 enterprises were unable to find resonance in these stories from the standpoint of their enterprise’s reinvention. This makes a lot of sense as these established companies have legacy investments and legacy stakeholders – both of which represent change inhibitors that the FANGs (Facebook Amazon Netflix and Google) did not have. Enterprise practitioners need to understand how Digital technology can impact both existing technology investments and the future landscape.
Where are most Enterprises at the moment…
Much of what exists in the datacenters across organizations are antiquated from a technology stack. These range from hardware platforms to network devices & switches to monolithic applications running on them. Connecting these applications are often proprietary or manual integraton architectures. There are inflexible, proprietary systems & data architectures, lots of manual processes, monolithic applications and tightly coupled integration. Rapid provisioning of IT resources is a huge bottleneck which frequently leads to lines of business adopting the public cloud to run their workloads. According to Rakesh Kumar, managing vice president at Gartner – “For over 40 years, data centers have pretty much been a staple of the IT ecosystem,Despite changes in technology for power and cooling, and changes in the design and build of these structures, their basic function and core requirements have, by and large, remained constant. These are centered on high levels of availability and redundancy, strong, well-documented processes to manage change, traditional vendor management and segmented organizational structures. This approach, however, is no longer appropriate for the digital world.” [2]
On that note, the below blogpost had captured the three essential technology investments that make up Digital Transformation.
The Three Core Competencies of Digital – Cloud, Big Data & Intelligent Middleware
If Digital has to happen, IT is one of the largest stakeholders…
Digital applications present seamless expereinces across channels & devices, are tailored to individual customers needs, understand their preferences & need to be developed in an environment of constant product innovation.
So, which datacenter capabilities are required to deliver this?
Figuring out the best architectural foundation to support , leverage & monetize on digital experiences is complex. The past few years have seen the rapid evolution of many transformational technologies—Big Data, Cognitive Computing, Cloud technology (Public clouds, OpenStack, PaaS, Containers, Software-defined networking & storage), the Blockchain – the list goes on and on. These are leading enterprises to a smarter way of developing enterprise applications and to a more modern, efficient, scalable, cloud-based architectures.
So, what capabilities do Datacenters need to innovate towards?
While, the illustration above is self explanatory. Enterprise IT will need to majorly embrace Cloud Computing – whatever forms the core offering may take – public, private or hybrid. The compute infrastructure ranging from a mix of open source virtualization to Linux containers. Containers essentially virtualize the operating system so that multiple workloads can run on a single host, instead of virtualizing a server to create multiple operating systems. These containers are easily ported across different servers without the need for reconfiguration and require less maintenance because there are fewer operating systems to manage. For instance, the OpenStack Cloud Project specifies Docker (a defacto standard), a Linux format for containers that’s designed to automate the deployment of applications as highly portable, self-sufficient containers.
Cloud computing will also enable the rapid scale up & scale down across the gamut of infrastructure (compute – VM/Baremetal/Containers, storage – SAN/NAS/DAS, network – switches/routers/Firewalls etc) in near real-time (NRT). Investments in SDN (Software Defined Networking) will be de riguer in order to improve software based provisioning, network, time to market and to drive network equipment costs down. The other vector that brings about datacenter innovation is around automation i.e vastly reducing manual efforts in network and application provisioning. These capabilities will be key as the vast majority of digital applications are deployed as Software as a service (SaaS).
An in depth discussion of these Software Defined capabilities can be found at the below blogpost.
Financial Services IT begins to converge towards Software Defined Datacenters..
Applications developed for a Digital infrastructure will be developed as small, nimble processes that communicate via APIs and over infrastructure like service mediation components (e.g Apache Camel). These microservices based applications will offer huge operational and development advantages over legacy applications. While one does not expect legacy but critical applications that still run on mainframes (e.g. Core Banking, Customer Order Processing etc) to move over to a microservices model anytime soon, customer facing applications that need responsive digital UIs will definitely move.
Which finally brings us to the most important capability of all – Data. The heart of any successful Digital implementation is Data. The definition of Data includes internal data (e.g. customer data, data about transactions, customer preferences data), external datasets & other relevant third party data (e.g. from retailers) etc. While each source of data may not radically change an application’s view of its customers, the combination of all promises to do just that.
The significant increases in mobile devices and IoT (Internet of Things) capable endpoints will ensure exponential increases in data volumes will occur. Thus Digital applications will need to handle this data – not just to process it but also to be able to glean real time insights. Some of the biggest technology investments in ensuring a unified customer journeys are in the areas of Big Data & Predictive Analytics. Enterprises should be able to leverage a common source of data that transcends silos (a data lake) to be able to drive customer decisions that drive system behavior in real time using advanced analytics such as Machine Learning techniques, Cognitive computing platforms etc which can provide accurate and personalized insights to drive the customer journey forward.
Can Datacenters incubate innovation ?
Finally, one of the key IT architectural foundation strategies companies need to invest in is modern application development. Gartner calls such a feasible approach “Bimodal IT”. According to Gartner, “infrastructure & operations leaders must ensure that their internal data centers are able to connect into a broader hybrid topology“.[2] Let us consider Healthcare – a reasonably staid vertical as an example. In a report released by EY, “Order from Chaos – Where big data and analytics are heading, and how life sciences can prepare for the transformational tidal wave,” [1] the services firm noted that an agile environment can help organizations create opportunities to turn data into innovative insights. Typical software development life cycles that require lengthy validations and quality control testing prior to deployment can stifle innovation. Agile software development, which is adaptive and is rooted in evolutionary development and continuous improvement, can be combined with DevOps, which focuses on the the integration between the developers and the teams who deploy and run IT operations. Together, these can help life sciences organizations amp up their application development and delivery cycles. EY notes in its report that life sciences organizations can significantly accelerate project delivery, for example, “from three projects in 12 months to 12 projects in three months.”
Finally, Big Data has evolved to enable the processing of data in a batch, interactive, low latency manner depending on the business requirements – which is a massive gain for Digital projects. Big Data and DevOps will both go hand in hand to deliver new predictive capabilities.
Further, business can create digital models of client personas and integrate these with predictive analytic tiers in such a way that an API (Application Programming Interface) approach is provided to integrate these with the overall information architecture.
Conclusion..
More and more organizations are adopting a Digital first business strategy. The current approach as in vogue – to treat these as one-off, tactical project investments – does not simply work or scale anymore. There are various organizational models that one could employ from the standpoint of developing analytical maturity. These ranging from a shared service to a line of business led approach. An approach that I have seen work very well is to build a Digital Center of Excellence (COE) to create contextual capabilities, best practices and rollout strategies across the larger organization.
References –
[1] E&Y – “Order From Chaos” http://www.ey.com/Publication/vwLUAssets/EY-OrderFromChaos/$FILE/EY-OrderFromChaos.pdf
[2] Gartner – ” Five Reasons Why a Modern Data Center Strategy Is Needed for the Digital World” – http://www.gartner.com/newsroom/id/3029231