What does it take to be successful in the evolving hybrid computing model?
This is the last blog in a three-blog series. In the first blog, I made the argument that in order to enable businesses to compete in highly-competitive, rapidly-changing marketplaces, IT organizations need to become more agile and innovative, and one way to accomplish that is to adopt a cloud computing model. Because the phrase cloud computing means different things to different people, in the second blog I used the definition of cloud computing that was created by the National Institute of Standards and Technology (NIST) in 2011 to explain what I mean by cloud computing.
In this blog, I will discuss how cloud computing has evolved and is continuing to evolve. This includes the coming together of public and private cloud computing into a hybrid cloud computing model. It also includes the emergence of edge computing as an extension of hybrid cloud. This blog will also discuss the functionality IT organizations need in order to be successful with this emerging model of computing.
The Traditional Hybrid Cloud Computing Model
Cloud computing began to have an impact on IT organizations roughly a decade ago and since its inception, the use of cloud computing has grown dramatically. For example, according to a recent article, Global cloud IT market revenue is predicted to increase from $180B in 2015 to $390B in 2020, which represents a Compound Annual Growth Rate (CAGR) of 17 percent. As mentioned, a key driver in the tremendous growth in the use of cloud computing is the belief that cloud computing has the ability to help organizations be more agile and innovative.
In addition to growing dramatically, the implementation and consumption of cloud computing has also evolved significantly over the last decade. For example, the initial use case for cloud computing was for small and mid-sized businesses to access a Software-as-a-Service (SaaS) provider such as Salesforce.com. In the current environment, organizations of all sizes access public cloud providers, and in addition to SaaS providers, this includes accessing Infrastructure-as-a-Service (IaaS) providers such as Amazon Web Services (AWS). According to Gartner, the most rapidly-growing segment of the cloud computing marketplace is the IaaS segments, which Gartner predicts will grow at 36.8 percent in 2017.
A decade ago, when someone used the phrase cloud computing, they were referring to what we now think of as public cloud computing. The reason for that is quite simple. At that time, there wasn’t any other form of cloud computing available. As cloud computing began to be adopted, the myopic focus on public cloud computing was reinforced in a book written by Nicholas Carr, entitled The Big Switch: Rewiring the World, from Edison to Google. That book, which was very highly regarded at the time, made the argument that all computing applications and services would soon be provided in a centralized fashion by public cloud providers. A major part of Carr’s argument was that public cloud providers are inherently more cost-effective at providing computing services than are individual enterprises.
In the current environment, public cloud computing remains a major component of the overall use of cloud computing. However, several years ago, many organizations began to adopt solutions from companies such as VMware that have enabled them to implement private cloud computing. Part of what drives organizations to choose private cloud computing over public cloud computing are concerns over security and control. There are also a number of operational issues. For example, it is difficult for an enterprise to troubleshoot performance problems with public cloud services due to the lack of visibility relative to infrastructure-level statistics.
Perhaps the most important reason why enterprises choose a private cloud solution over a public cloud solution is that Carr’s argument – public cloud providers are more cost-effective than are enterprise providers – is simplistic. While the cost of private cloud services can be viewed as being fixed, public cloud providers charge on a usage basis for the services they provide. As is the case with any service that is priced on a usage basis, there is a cross-over point after which it is more cost-effective to use a fixed-price service. Enterprises quickly found out that for long-running, compute-intensive workloads such as big data analytics and multi-tier web applications, it is much more cost-effective to run these workloads in a private cloud. Enterprises, however, also quickly learned that private clouds are not a panacea. Some of the major limitations associated with private clouds are the high cost of the required licenses and the cumbersome nature of the management.
Using cost as an example, there are times when it makes sense to run a workload in a public cloud such as AWS, and there are times when it makes sense to run workloads in a private cloud. As a result, organizations have recently begun to adopt hybrid cloud computing. In a hybrid cloud environment, users access the resources they need, whether those resources are hosted at one or more private cloud facilities or at one or more public cloud provider’s facilities. For example, a complex business service such as Supply Chain Management (SCM) is made up of multiple modules which, if run in a hybrid cloud environment, may reside in separate facilities, both private and public. In addition, these modules may move between the facilities as requirements and costs change.
 SCM is made up of functions such as inventory management, order management, procurement, and logistics, each of which may themselves be comprised of multiple modules.
In IT, it sometimes makes sense to centralize resources and it sometimes makes sense to decentralize resources. Over the last decade, the adoption of cloud computing has driven the centralization of resources into a relatively small number of public and private data centers. However, we have recently seen the start of a movement, referred to as edge computing, which begins to somewhat reverse the trend of centralizing resources.
Edge computing is a method of optimizing cloud computing systems by performing data processing at the edge of the network, near the source of the data. Part of the value of edge computing was discussed in a recent article in Forbes. According to that article, “Edge computing addresses many challenges that enterprise IT faces when running data-centric workloads in the cloud. It reduces the amount of data that flows back and forth between the datacenter and the public cloud. Edge computing will enable IT to retain sensitive data on-premises while still taking advantage of the elasticity offered by the public cloud. It reduces the latency involved in dealing with public cloud platforms.”
The adoption of edge computing gives new meaning to the phrase hybrid computing. No longer does that phrase refer exclusively to the combination of private and public clouds. Increasingly it refers to the combination of private clouds, public clouds and edge computing.
Starting with the adoption of public cloud services, the computing model has evolved dramatically over the last decade and it continues to evolve at a rapid pace. Given this volatile environment, a minimum requirement for IT organizations is the ability to take a set of servers and turn them into an effective private cloud solution. As discussed in the previous blog, that means that the solution must exhibit the following characteristics:
· Resource pooling;
· Broad network access;
· On-demand self-service;
· Rapid elasticity or expansion;
· Measured service.
The solution must also be efficient in that the management of the solution should require the absolute minimum amount of manual effort.
As outlined in this blog, private clouds are just one place to host workloads. To maximize the value they provide, IT organizations need the ability to host workloads in whatever location is optimal at each and every point in time. There are several criteria that determine the optimal location including:
To accomplish this goal, IT organizations must have the capability to seamlessly move workloads between a private cloud that is based on technology such as that provided by VMware and a public cloud such as AWS. On an ongoing basis, IT organizations also need the capability to move workloads in and out of edge computing sites.
However, IT organizations are under constant pressure for agility and cost-effectiveness. In order to respond to these pressures, the capabilities mentioned above must implement the highest levels of automation that are currently available and must continue to leverage technological advances, such as those enabled by the ongoing development of AI.