Digital transformation or “DX” has become a mainstream tech buzzword, and there is no sign of its use declining to describe the current state of business transformation. Digital transformation strategies modernize legacy and IT business process. DX creates new digital products by either making technology as the product or as a key enabler of the product. It represents a seismic shift from viewing IT as a nagging support function and cost center to an innovative core product strategy and profit center. 

By the end of this year, IDC predicts that 30% of G2000 companies will have allocated capital budgets equal to at least 10% of revenue to fuel their digital strategies. 

Shawn Fitzgerald, research director of Worldwide Digital Transformation Strategies at IDC states, “This shift toward capital funding is an important one as business executives come to recognize digital transformation as a long-term investment. This commitment to funding DX will continue to drive spending well into the next decade.”

As companies race towards a digital enterprise, which trends we are likely to see developing throughout 2020? This article discusses four trends pushing digital transformation we predict will dominate this year.

Trend 1 - Application Development on Serverless Computing

One digital transformation trend that is likely to continue to grow throughout 2020 is serverless computing. Serverless computing abstracts application functions away from the operating system and enables companies access to the most common legacy compute functions like database or extract, transform, load (ETL) and newer functions like Kafka, Spark, Docker, and Kubernetes via a service. 

This approach has been very popular with startups and existing enterprises developing greenfield applications. Serverless computing functions are available from all the major vendors — IBM Cloud Functions as a Service, AWS Lambda, Azure Functions, and Cloud Functions by GCP. 

As a result, companies no longer carry the overhead of maintaining persistent server instances. Developers don’t have to build and maintain their environments. This means reduced system administration overhead, less on-call rotations, less outages, and developers can spend the bulk of their time building their applications.

Serverless computing offers a pay-as-you go model with infinite scale. This removes the constraints of yearly CapEx allocations and shifts costs into variable OpEx. With infinite scale, companies are no longer at risk of outages or poor application performance during peak usage periods. This gives companies greater flexibility as they grow and allows them to control their expenses.

According to one survey, there was a softening in serverless computing in the early part of 2019. However, prior to that, serverless computing had shown consistent growth, and commentators still think of serverless as the next step in cloud infrastructure.

The 2019 State of DevOps report finds that serverless computing has captured the attention of 29% of cloud architects, 24% of SRE/DevOps and 24% of executives, who are now using it as a strategic trend.

Trend 2 - Using Multiple Public Cloud Vendors

Taking an omni-cloud (multi-cloud) approach has become a pillar of digital transformation among businesses, with a recent survey by IBM showing that 85% of  companies had chosen a multi cloud environment. The multi-cloud solution is made up of more than one cloud service from multiple cloud vendors combining on-premise infrastructure with public cloud service providers such as IBM Cloud, Amazon Web Services, Google Cloud Platform and Azure.

Many businesses favor the multi-cloud because applications have greater portability and cloud providers are working more readily together, see the API Economy below. A Gartner report states the key reasons for multi cloud adoption include reducing vendor lock-in, mitigating service disruptions and organizational efficiencies. This means that organizations can take advantage of the strengths of each cloud vendor both in features and location.  

There are a host of multi-cloud tools in the marketplace. For example, Multi-Cloud Object Gateway in OpenShift 4.2, provides a Single S3 storage interface, enabling consistent object access across all cloud providers. IBM API Connect enables developers to create and manage the lifecycle of an API across multiple clouds. For those who are staunch on open source, the Zenko and Kong API controller projects offer similar multi-cloud management functionality. 

Analysts forecast that larger companies will change to a multi-cloud approach because of the extra flexibility it provides. As organizations have an increased need for automation and agility, multi cloud is likely to continue on an upward trajectory between now and 2026.

Trend 3 - AI/Machine Learning

Some would argue that artificial intelligence (AI) and machine learning are digital transformation and future enterprise can’t exist without it. Data Science Central defines AI as the use of computers to mimic the cognitive functions of humans. When machines perform task supported algorithms in an “intelligent” manner, that is AI. 

On the other hand, machine learning is a subset of AI and focuses on the ability of machines to receive a set of data and learn for themselves. As they learn more about the information they are processing, algorithms change.

By 2020, Deloitte has predicted that “penetration rates of enterprise software with integrated AI and cloud-based AI platforms will reach about 87% and 83%, respectively, among companies that use AI software”.

As Deloitte explains in its report, “Cloud-based software and platforms help companies benefit from AI, even if they lack the expertise to build and train systems or to manage data on their own. According to our survey, AI early adopters are taking advantage. Many companies that aren’t using these technologies today plan to do so in the future”.

An exec from a financial planning company recently told me, “It took time, but we were able to analyze credit card expenditures and cross reference with moving violations to predict within 87% accuracy possible downside life events like divorce and terminal illness within 18 months. We had a hypothesis about sudden reckless spending and driving we wanted to test. It was eye opening to our clients and prompted them to reevaluate some of their life choices, leading to much more positive personal outcomes.”

There are a multitude of AI and ML startups out there in addition to the stalwart mature platforms of IBM Watson, TensorFlow, and Matlab for developers to engage and test.  

The advantages of AI and machine learning are manifold. Cloud providers can integrate AI through predictive analytics and chatbots, reduce hard costs through shipping optimization, manage leaner inventory, and in some cases, save people from their own choices. 

Trend 4 - Leverage the API Economy

As multi-cloud gains ground, so does the complexity. Often, companies are relying on a blend of tools to provide digital services across diverse enterprises, which poses significant challenges. Therefore, we are likely to see businesses opting for multiple cloud services across a broad array of vendors. The API Economy is the glue of the digital enterprise. While there are multiple takes on this term, Gartner provides a concise definition: 

“The API economy is an enabler for turning a business or organization into a platform.” 

There has been a mass exodus in recent years from greenfield data center build outs as companies opt for a combination of IaaS, PaaS, and SaaS. In a world of CI/CD which delivers features constantly, digital businesses can’t afford to go through all the lengthy legacy procurement processes to bring enabling technologies online for products.

While the cost benefit analysis between CapEx and OpEx is largely a wash, IT departments also don’t want to deal with the downside risk of outages, performance, security, and compliance in a very connected world.   

Realizing the days of vendor lock in are long gone, vendors now offer APIs to their technology that would have been unheard of 10 years ago. By leveraging the best feature sets across IaaS, PaaS, FaaS, and SaaS via APIs, the digital enterprise can transform their own products and services into a platform for their customers to consume. 

APIs from IaaS platforms like IBM SoftLayer, GCP, AWS, and Azure, along with PaaS platforms like OpenShift and other Docker/Kubernetes derivatives, and business function SaaS powerhouses like SalesForce, ServiceNow, and Workday give enterprise a broad array of options to build out digital infrastructure. 

Conclusion

As the digital economy builds momentum, there are several trends we can expect to see emerging in the coming year and beyond. This includes a greater use of AI and machine learning by cloud vendors and businesses. Serverless computing, the API economy as well as multi cloud are other likely trends are driving the digital enterprise and show no signs of slowing. 

About the Author

Darren Hoch is a partner, founder, and practice manager for DevOps and Hybrid Cloud  for Stone Door Group. Stone Door Group specializes in DevOps based digital transformation of the enterprise. Learn more about how we help companies build their digital enterprise through cloud migration, implementation of DevOps, and refactoring microservice apps on serverless platforms. To talk to Darren, drop us a line at letsdothis@stonedoorgroup.com.