01 October 2017

Anand Krishnan, EVP, cloud and general manager, Canonical

Technology innovation has been disrupting industries for decades. So it’s unsurprising that companies look over their shoulders to see which startups are going to change or influence their markets.

Organisations looking to leverage cutting-edge software capability now have to be able to build and manage integrated solutions, compiled from multiple, disparate sources, deployed across elastic infrastructures, which can scale to thousands of servers.

We coined the term ‘Big Software’ to represent the at-scale software organisations rely on to stay ahead. Any innovating organisation must expect to ingest increasing amounts of Big Software. They have to ramp up and maintain operational expertise of this type rapidly enough to keep pace with wider business needs.

This can only be achieved by open-sourcing IT operations knowledge, which involves encapsulating operational expertise in intelligent open-source ‘models’ to be used by numerous organisations. Those models become the automation backbone for Big Software, delivering speed and economics that legacy IT approaches can only dream of.

Companies routinely pour 80 per cent of their IT budget into operating existing infrastructure, leaving just 20 per cent for innovation. This is the shortfall disruptors exploit. Businesses aiming for growth in this software-defined age must move the dial in the opposite direction substantially.

It starts with rejecting the mindset that IT operations must be managed manually. This was adequate ten years ago, but in today’s fast-paced commercial world, every IT business must consider running its data centres the way Google and Amazon run theirs. This means automation revolving around truly intelligent, model-driven operations, allowing IT staff to focus on competitive differentiation.

For example, it took one pharmaceutical customer under 90 days to go from concept to being able to deploy, configure, stop and start apps across thousands of machines. This directly results in shorter time-to-market with new drugs, new chemicals or molecular entities – with the potential return measured in billions per patent. True model-driven automation readily pays for itself and then some.

In this period of extraordinary creative disruption, innovation is about letting go and making the software do the work. This enables people to work smarter, move faster, and focus on innovation. Clearly, disrupt or die is the new battlecry for both challenger and incumbent in this software-defined era.