Intelligent Tech Channels Issue 12 | Page 37

INTELLIGENT DATA CENTRES The organisations that will achieve digital supremacy in 2018 will be those that capitalise on new tools that enable their developers to innovate and create new sources of competitive differentiation. Kevin Leahy, Group SVP, Data Centre Business Unit, Dimension Data. development and deployment tools, particularly in the area of containerisation. These advancements have a significant impact on application portability and interoperability. Now developers can use containers to develop applications and move them into production across all the environments that make up their hybrid infrastructures. Increasingly, we will see organisations that are successfully accelerating their digital transformation focusing on using SaaS for non-differentiating processes. Using SaaS to ensure that their non-core focus areas are running optimally will enable organisations to focus their resources on creating and evolving their differentiation capability elsewhere. Rise of the API Increasingly, organisations are recognising the importance of APIs in enabling them to develop revenue-generating applications and services. This evolution has been dubbed the rise of the API economy. In 2018, organisations will start to see the wisdom in standardising on a set of APIs. We will see IT decision-makers move away from evaluating tools, technologies and services purely on the basis of their features and the capabilities they enable. Now, the first questions they will ask will be: Tell me about the APIs? In the year ahead, businesses will be challenged to keep up with the pace of change of APIs and ensure that they are able to invest in programming around them, to drive the business outcomes that they are looking for. The type and number of APIs that organisations select will depend on several factors, including the extent to which they want or need to abstract away the underlying technologies. The cloud management tool will seamlessly abstract away all the underlying clouds and you can just interface with the tool’s API, not those of the individual clouds. Services architecture There is a clear acceptance in the industry that hybrid IT is the model of the future. But hybrid IT has significant architectural implications, which organisations will need to address in the year ahead. Over the last decade, IT teams have focused much of their energies on technology integration and, during this period, there was a strong drive towards standardisation of technologies to make this more achievable. The advent of hybrid IT has changed the paradigm: mastering hybrid IT requires you to focus not on technology integration but on services integration. Most organisational architectures were not built with this theme in mind. If you attempt to bring together the different services components without first putting in place the appropriate architecture, you run the risk of delivering a poor, inconsistent user experience. And as the services start to become more complex, your ability to scale them and deliver with quality will be limited. Value of data In 2018, there will be an intensified focus on exploiting the value of data and ensuring it is made available to those who need it, when they need it, a truly data-centric view of IT. Historically, IT teams focused on managing the cost of an organisation’s data. They would move data from one tier of storage to another. As the value or the need to access certain sets of data diminished, they would be progressively moved to lower cost storage tiers. Today, there are two forces driving a shift in focus from cost, to value. First, the advent of all-flash storage means that there is less need for organisations to concern themselves with different storage types and tiers. In addition, you can architect such that cost is not an issue, by moving to an all-flash option to make your business faster. What is more important is the fact that as organisations transform into digital business, the role of data is taking on greater significance. Now, the emphasis is on finding new value in your data and being able to leverage the value of that data faster. This raises questions about where the data needs to be in order to extract that value, and what kind of analytics you need to perform.  37