This is the fourth of a series of blog posts discussing the five main considerations critical to successful cloud adoption by enterprises. If you missed them, the previous posts are here.
Today’s topic is about moving past the initial technology implementation phase to really realise the maximum enterprise benefit from cloud adoption.
At Beamap we live and breathe cloud computing all day every day, but it’s important to not lose sight of the fact that really it is not an end in itself, it is just an enabler. It’s all about the applications. An issue that we see in enterprises is that they have access to more agile cloud services, but the workloads that they run on them are still architected and developed in much the same way. So cloud has been “adopted”, but the biggest benefits come from fully leveraging the hard-fought benefits throughout the application lifecycle.
Vendor application issues
This is one of the real blockers on accessing the full benefits. The harsh reality is that most commercial applications out there are still not really architected to fully exploit cloud services. Application vendors have all the same problems that enterprises do in tracking the cloud market, and so support for features such as auto-scaling is often lacking (even worse, the vendor is likely to have “cloud-washed” their app in a marketing sense, so it’s hard to tell where the shortcomings are). Hence there is a long long tail of application rework required by vendors and in the meantime cloud is used simply as a hosting platform for these applications, which makes the business case against traditional hosting models much harder to make.
Internally developed application issues
For internally developed applications, the same issues are playing out, but require changes to the architecture, development and operations processes – and this takes time. Organisations need different skills and tools to implement and really get the benefits from continuous integration, continuous delivery and blue-green deployment practices, containerisation, serverless computing etc. And then there are the real game changing higher-level PaaS services to be exploited, or the use of commodity IaaS services to deliver a scale of operation at a cost point that was unimaginable just a few years ago – for machine learning, big data processing, artificial intelligence and IoT. In addition, like everything else in the world of cloud computing, this is not a static challenge, so in your applications teams there’s an ongoing need for training around opportunities, best practices and standards development related to the ever-improving cloud services.
…and what to do about it
There is a phasing and investment profile issue here that needs to be considered in the cloud business case work – whilst the target is to have a set of beautiful cloud-native applications, the creation (or conversion) of these applications takes longer than it does to stand up private cloud services, and certainly way longer than it does to access public cloud services. The size of internal cloud platforms and the operating model to support all cloud services only need to scale a touch faster than the application demand that is able to consume these services. When the application development capabilities don’t keep up with the cloud services that they can consume, that’s when you have a problem and are missing a trick.