Welcome!

@CloudExpo Authors: Liz McMillan, Pat Romanski, Yeshim Deniz, Zakia Bouachraoui, Elizabeth White

Related Topics: @CloudExpo, Microservices Expo

@CloudExpo: Blog Post

Standardization and Customization in the Cloud

The two go hand in hand

Maybe it is a misunderstanding, misperception or a myth, but it seems quite a few people make an incorrect assumption about standardization and customization when it comes to services delivered in the cloud. Specifically, the message I hear often from both providers and consumers seems to pit standardization and customization against each other, almost as if you can only have one or the other. This, of course, is wholly incorrect.

Seemingly, a lot of the confusion in the standardization/customization arena comes from the rhetoric often delivered around the different cloud delivery models. For instance, let's consider a common aspect of public cloud messaging. From my own personal experience, nearly every session or description I have listened to or read concerning a particular public cloud solution includes a bit about the delivery of a standardized set of services. This may seem a true enough message on the surface, but in fact, it is usually a bit misleading. More times than not, the more accurate message is that the public cloud solution delivers a minimally customized set of services. In other words, the public cloud solution delivers a set of services that appeal to a wide variety of users and use cases (as one would expect from the public cloud).

On the other hand, the talk around private cloud solutions tends to home in on customization. The messaging here is often that you can build whatever set of services you need, and then deliver them via a cloud environment. That may be true enough, but the problems start when you hear statements like, "This isn't like that standardized set of public cloud services, these are customized services that you can tailor to meet your company's needs." I have heard statements just like this in many different settings, from many different vendors to boot. I do not take issue with touting customization capabilities of a particular cloud solution (I do so all the time), but I do have a problem pitting that against standardization.

Simply put, standardization and customization are in no way mutually exclusive. I believe a lot of the confusion here comes from the fact that the industry ever used the phrase standardized services to describe assets delivered by the public cloud. If you think about it, it is ridiculous to say that either the public or private cloud can inherently deliver standardization. Only users can define and design their set of standardized services. They have to decide what their standard web server environment should look like or how to configure their standard operating system environment. In most cases, there is simply no way for a cloud provider to anticipate what is standard for a given user and use case.

In no way am I making an argument against the fact that the cloud enables standardization. In my mind, that is one of its chief benefits. The key though is that it enables standardization, not necessarily delivers it. Users have to decide what a standardized service is for them and their organization. This is nothing the cloud can anticipate for them.

The notion that only users can decide and design their set of standardized services also implies those services are customized. Users build and customize these services to fit their needs. Depending on the delivery model and the particular cloud solution, users can accomplish this in a variety of different ways, but the result remains the same. The user builds a set of customized services on which they can standardize within their organization, and then they deliver those services via the cloud.

Maybe I am the only one that perceives confusion around standardization and customization in the cloud. In that case, I just want to leave with one parting, summarizing thought: Customization and standardization work in conjunction to deliver enhanced user value for cloud-based services across all delivery models.

More Stories By Dustin Amrhein

Dustin Amrhein joined IBM as a member of the development team for WebSphere Application Server. While in that position, he worked on the development of Web services infrastructure and Web services programming models. In his current role, Dustin is a technical specialist for cloud, mobile, and data grid technology in IBM's WebSphere portfolio. He blogs at http://dustinamrhein.ulitzer.com. You can follow him on Twitter at http://twitter.com/damrhein.

CloudEXPO Stories
With more than 30 Kubernetes solutions in the marketplace, it's tempting to think Kubernetes and the vendor ecosystem has solved the problem of operationalizing containers at scale or of automatically managing the elasticity of the underlying infrastructure that these solutions need to be truly scalable. Far from it. There are at least six major pain points that companies experience when they try to deploy and run Kubernetes in their complex environments. In this presentation, the speaker will detail these pain points and explain how cloud can address them.
While some developers care passionately about how data centers and clouds are architected, for most, it is only the end result that matters. To the majority of companies, technology exists to solve a business problem, and only delivers value when it is solving that problem. 2017 brings the mainstream adoption of containers for production workloads. In his session at 21st Cloud Expo, Ben McCormack, VP of Operations at Evernote, discussed how data centers of the future will be managed, how the public cloud best suits your organization, and what the future holds for operations and infrastructure engineers in a post-container world. Is a serverless world inevitable?
Predicting the future has never been more challenging - not because of the lack of data but because of the flood of ungoverned and risk laden information. Microsoft states that 2.5 exabytes of data are created every day. Expectations and reliance on data are being pushed to the limits, as demands around hybrid options continue to grow.
Machine learning provides predictive models which a business can apply in countless ways to better understand its customers and operations. Since machine learning was first developed with flat, tabular data in mind, it is still not widely understood: when does it make sense to use graph databases and machine learning in combination? This talk tackles the question from two ends: classifying predictive analytics methods and assessing graph database attributes. It also examines the ongoing lifecycle for machine learning in production. From this analysis it builds a framework for seeing where machine learning on a graph can be advantageous.'
Enterprises are striving to become digital businesses for differentiated innovation and customer-centricity. Traditionally, they focused on digitizing processes and paper workflow. To be a disruptor and compete against new players, they need to gain insight into business data and innovate at scale. Cloud and cognitive technologies can help them leverage hidden data in SAP/ERP systems to fuel their businesses to accelerate digital transformation success.