Does your bank offer the ability to deposit a check by taking its picture with your smartphone? When that feature debuted a few years back, I remember thinking it was interesting and convenient enough that if my bank didn’t offer it soon, I’d be willing to switch to one that did.
I bring this example up for two reasons: one, it’s a microcosm of the larger race to innovation that is happening in every company and industry as we speak; and two, it involves banks, which are good touch-points for a discussion about the unique challenges established enterprises face as they attempt to implement DevOps practices in their IT organizations.
We know that DevOps means incorporating best-practice application delivery methods that improve communication, integration and collaboration between development and operations, but what is its ultimate goal? Quite simply, getting high-quality services to market faster than competitors – at a cost that aligns with both IT budgets and business goals. And as my check-depositing story illustrates, if you’re not first in the market, you at least need to be nimble enough to catch up, or you risk losing customers.
For long-time enterprises, this can be easier said than done. In my previous blog about DevOps culture, I used Etsy as an example of an organization that has had great success with its DevOps transformation, but the e-commerce company has been around for less than a decade. Its young IT architecture is apples to the oranges of established enterprises, whose complex environments often comprise a mix of legacy and modern technologies that have been cobbled together over time.
As a result, the DevOps journey is typically longer and more difficult for such organizations – but that doesn’t mean they can afford not to pursue it.
Improving Deployment Practices at Every Infrastructure Layer
When you look at the IT infrastructure of an established enterprise, you normally find three layers of technology. Let’s call the first “systems of record.” These are the legacy transactional systems (often mainframes) that have been with a company since the beginning. They do their jobs well, but their size and inflexibility make them resistant to the type of Agile development that DevOps typically embraces.
The next layer is “systems of differentiation,” or the various hardware, software and middleware components an organization accumulates as it grows, merges with/acquires companies and enters new markets. While these systems are often more Agile-ready than the systems of record, their decoupled/distributed nature can complicate and slow down development and deployment processes.
Finally, there is the “systems of innovation” layer, which is made up of mobile and Web applications and leverages the latest technologies. Because of its light footprint and flexibility, this layer is the most adaptable to DevOps practices. In fact, as you move up the layers from systems of record to systems of innovation, the holy grail of high-quality, fast and low-cost deployment becomes more and more attainable.
What does this mean from a macro perspective? Basically that established enterprises need to take a pace-layered approach, where application delivery occurs at different paces within the different areas of their architectures. The point, though, is to improve in each layer.
So if an organization pushes out a mainframe update once per year, perhaps it can move to a bi-annual schedule (with support from the right people, processes and technology, of course). On the other hand, a Web team that publishes updates once or twice a week could leverage DevOps tactics and technologies to adopt a daily update cadence. Bottom line: Different deployment paces are fine across layers, as long as improvements are occurring across the board.
Kick-starting the Journey with Service Virtualization
Now that we know why the DevOps journey can be difficult for established enterprises, let’s look at how one such organization, namely Union Bank, overcame these challenges and achieved success.
According to an article on Bank Systems & Technology, Union Bank was looking for ways to compete with top-tier banks, so it began “acquiring other institutions, updating legacy systems and launching new front-end applications.” In order to support these efforts, the bank implemented a service virtualization solution, which simulates constrained or unavailable systems across the software development lifecycle (SDLC). This allowed its developers, testers and performance teams to work in parallel for faster delivery and higher application quality and reliability.
Here are some of the results Union Bank has achieved since:
- Cut testing environment setup time from 42 days to 3 days
- Slashed three and a half months from mobile and Web application development time
- Reduced the cost of testing cycles by 65 to 85 percent
Obviously, a service virtualization solution is only one piece of the DevOps puzzle, but Union Bank stands as a powerful example of how a long-standing enterprise can leverage such a tool to be more innovative and nimble in the marketplace.
