The Current State of Cloud Computing

In June, 2008 I gave a talk at a conference on The Promise and Reality of Cloud Computing. In his closing remarks, the conference organizer noted that most everyone had agreed that something big and profound was going on, but they weren’t quite sure what it was they were excited about. “There is a clear consensus that there is no real consensus on what cloud computing is,” he said. A few months later, The Economist published a special report on cloud computing with several articles on the subject. In the lead article, technology editor Ludwig Siegele started out his definition of cloud computing by first giving a very succinct history of computing:

“In the beginning computers were human. Then they took the shape of metal boxes, filling entire rooms before becoming ever smaller and more widespread. Now they are evaporating altogether and becoming accessible from anywhere. Computing has constantly changed shape and location - mainly as a result of new technology, but often also because of shifts in demand. Now, … it is turning into what has come to be called a ‘cloud’, or collections of clouds. Computing power will become more and more disembodied and will be consumed where and when it is needed.”

A major reasons for both the excitement and lack of consensus about cloud is that we were basically seeing the emergence of a new model of computing in the IT world. In the sixty years or so since there’s been an IT industry, cloud is only the third such model. First came centralized computing in the early ’60s and ’70s, followed by the distributed client-server model in the 1980s. It’s been difficult to come up with a simple definition of cloud computing, because there’s no single dimension around which to define a computing model. It’s like the fable of the blind men and the elephant. Each one touches a different part of the elephant. They then compare notes on what they felt, and learn that they’re in complete disagreement.

Over the past dozen years, cloud has gone through three major stages: first came infrastructure-as-a-service, mostly based on public clouds; then came cloud-based application constructs, such as containers, Kubernetes, and microservices; more recently, we’ve seen the emergence of hybrid clouds, including a variety of public and on-premise cloud environments and cloud-native applications.

What’s the current state of cloud computing?  “The need for superior speed and agility continues to push companies toward cloud adoption,” said a recent McKinsey article, Debunking seven common myths about cloud. But while there’s a strong desire to aggressively adopt cloud technologies and services, actual adoption figures have continuously lag expectations.

“For the most part, this delay in cloud adoption does not stem from a lack of ambition. Many company leaders have encountered major roadblocks along their path toward cloud or have gotten cold feet once they questioned its impact on costs, security, latency, and more. Conversations with hundreds of CEOs and CIOs have revealed a consistent set of myths that lead to these roadblocks and questions, hampering progress and adoption. Companies that have effectively counteracted these myths are the ones that have derived the greatest rewards from their move to cloud.” Let me summarize both the myths and the actual reality.

• The main value of cloud is IT cost reductions. Actually, the business benefits of cloud, - such as faster time to market, innovation, scalability, - generate greater incremental contributions than IT cost reductions.
• Cloud costs are higher than in-house computing. The cost benefits of cloud include a shared-resource model, paying only for the resources actually used, and automatic scaling. These benefits improve when workloads are optimized for cloud.
• Security of in-house data centers is superior to the security on cloud. Cloud service providers (CSPs) have invested billions in cloud security, hired thousands of top cyber experts, and developed an array of new tools and methods. Cloud breaches have almost all been the fault of customers, not the CSPs.
• Applications suffer latencies in cloud provider’s networks. Latency is generally the result of routing access to cloud networks through in-house data centers in an attempt to improve security. With experience and the assistance of CSPs, IT departments can quickly resolve such latency issues.
• Moving to cloud eliminates the need for an infrastructure organization. While different and generally smaller, the internal IT organization has the overall responsibility to define and manage the cloud architectures, services, and platform being used by their development teams. 
• The most effective way to transition to cloud is to focus either on applications or on entire data centers. Organizations should manage the transition to cloud by business domains or departments, starting with those domains that can most benefit from faster time-to-market, agility and scalability. Managing the transition by business domain is much more manageable than attempting to transition an entire data center.
• To move to cloud, you must either lift and shift applications as they are today or refactor them entirely. Companies should neither embrace a quick and cheap “lift-and-shift” transition strategy, nor a time-intensive and costly cloud optimization of a complex application workload. Instead, they should embrace a pragmatic, incremental strategy, taking advantage of specific techniques that bring the business benefits of cloud to applications over time.

Another recent McKinsey article argues that companies should leverage cloud to accelerate their digital transformations. “Only 14 percent of companies launching digital transformations have seen sustained and material performance improvements. Why? Technology execution capabilities are often not up to the task. Outdated technology environments make change expensive. Quarterly release cycles make it hard to tune digital capabilities to changing market demands. Rigid and brittle infrastructures choke on the data required for sophisticated analytics.”

“Operating in the cloud can reduce or eliminate many of these issues. Exploiting cloud services and tooling, however, requires change across all of IT and many business functions as well - in effect, a different business-technology model.” The article recommends three key such changes for leveraging cloud to enable digital transformations:

Focus on those business domains where the benefits from cloud investments matter most. These benefits include:

• faster time to market: “Cloud-native companies can release code into production hundreds or thousands of times per day using end-to-end automation”;
• innovative business offering: “Each of the major cloud service providers offers hundreds of native services and marketplaces… and provide access to third-party ecosystems with thousands more”; and
• efficient scalability: “Cloud enables companies to automatically add capacity to meet surge demand… and to scale out new services in seconds rather than the weeks it can take to procure additional on-premises servers.”

Select a technology and sourcing model that aligns with business strategy and risk constraints. “Decisions about cloud architecture and sourcing carry significant risk and cost implications - to the tune of hundreds of millions of dollars for large companies. … The right technology and source decisions not only mesh with the company’s risk appetite but can also ‘bend the curve’ on cloud-adoption costs.” These decisions include where to use different ‘as-a-service’ options; how to migrate and re-architect existing applications and workloads; and how many cloud service providers to engage.

Develop and implement an operating models to capture the value of cloud. “Capturing the value of migrating to the cloud requires changes to both how IT works and how IT works with the business.” These changes include shifting from IT services and projects to IT products; redesigning the technology delivery processes end-to-end; integrating cloud with the operations and management of the business; ensure that cloud designs are fully defined and embedded as software; and driving cloud skills across all development teams.

Comments

[Dan Delmar]

Nice article, Irving!
Do you have some data handy on "actual adoption figures have continuously lag expectations."