Enterprise Architecture for Digital Business

Introduction

Geng Lin, F5 CTO, and Lori MacVittie, F5 principal technical evangelist

The destination of the digital transformation journey is a digital business.

During the first two decades of the 21st century, a digital transformation trend has driven the global economy. Over just two years—from 2019 to 2020—the pace of that transformation accelerated nearly tenfold.

The forces behind this acceleration span a broad spectrum of technological and societal changes that are not likely to slow for decades: wireless access for billions of people, the smartphone as an app platform, the increased speed and size of applications built on the cloud, the constrained number of engineers and developers, and customer demand for better, simpler experiences that empower them. The common theme of all these forces is the increased need and demand for innovation.

The outlines of this digital transformation journey are starting to take shape. What is emerging is a transformation to fully digital and automated businesses, resulting in the adaptability needed to respond to changes in the ecosystem, society, technology, and customer needs with a laser focus on customer experience, new ways of creating value, and a reshaping of the technical foundation of the businesses. At the heart of this transformation is the need to optimize business and technology for innovation.

The Innovation Equation

Today, most companies have a consistent theme of being stable at their core and innovating at the edge. If a business has a profitable product line or service, it won’t gamble with the core capabilities required to support it on a whim. However, company leaders might try new ideas on a small number of customers to discover whether the new product or service has traction without risking the whole business.

This is often reflected in the amount of money spent on maintaining core capabilities, which has consumed the bulk of corporate technology budgets for decades. Even after the explosive acceleration of digital transformation due to the global pandemic, organizations still allocated significantly more budget to their core than to innovation, on average, investing only 15% of budgets on business innovation initiatives and 59% on day-to-day business operations.¹

In a normal environment, this is not necessarily bad. But we are not in a normal environment. We have shifted into a business cycle in which organizations need to innovate.

Budget alone does not adequately express the ability of a business to adapt. A better measure is based on the capacity to engage in innovation, and that measure ultimately relies on people. The good news is that despite the additional burdens placed on IT by recent moves to a largely hybrid (remote/office) workforce, nearly half (40%) of organizations plan to expand their IT staff to meet demand.²

The bad news is that more people maintaining the core—keeping the lights on—does not necessarily contribute to the business’s ability to innovate. For that, technology needs to be used to enable staff to focus on adding value through innovation, rather than maintaining value by sustaining the status quo.

Consider an example: a company has been in business for 40 years. It has multiple product lines that are all profitable and can launch one or two new products or services a year. Maintaining its core ties up most of the business’s resources, and only a small percentage of the staff and resources are focused on developing new products or services. Most of its staff and budget are sustaining operations.

This means that the company’s ability to adapt is low. The business can’t take advantage of shifts in the market, putting it at a significant competitive disadvantage.

With the advent of the public cloud and subsequent adoption of its operating model, much of the core infrastructure needed to build products or run services became available as an operational cost and required minimal personnel to use. This shift was largely due to the ability of the public cloud to bear the cost of managing the infrastructure needed to deliver applications. All the budget and people dedicated to provisioning, scaling, monitoring, and operating infrastructure can be freed to focus on innovation.

But even with a jump in adaptability, we still have a significant shortage of skilled people to address market demand. A recent survey found that although half (50%) of employers are increasing hires, nearly all (92%) report difficulty finding talent with the right skills. Exacerbating the challenge is their struggle to retain existing talent in a fiercely competitive market.³

Organizations need to find another way to realize an order-of-magnitude jump in their capacity to innovate—not just to survive, but also thrive, in a digital economy.

Accelerating Adaptability

The goal of every business should be to achieve a budget and staff that increases the capacity to innovate. This requires more staff working on innovation than those maintaining the core. This is simply not possible for most organizations because of the following four key issues:

An operating model and culture intolerant of failure, leading to resistance to change

A majority of digital leaders (62%) see the traditional, ticket-based approach to ITOps as a waste of time because IT spends too much time figuring out how to respond to a digital incident.⁴

A security strategy based on control that requires significant resources rather than one based on adaptable risk management

An average of 46% of organizations report reductions in managing risk after adopting AI for security operations, with nearly half (44%) reporting cost reductions of up to 20% across all functions.⁵

Reliance on human intervention to operate applications and the infrastructure that delivers them

A plurality of tech leaders (70%) believe they need a new way to address digital incidents if they are expected to innovate.⁶

A lack of visibility into every part of the enterprise ecosystem, which hampers the ability to leverage technology that can reduce the budgetary burden of maintaining the core

The lack of insights is nearly universal. About 98 percent of IT staff and leaders report missing data critical to sustaining operations.⁷

As digital transformation drives businesses toward the goal of becoming adaptive, it must solve for these four key areas to enable adaptability and unlock the ability to innovate.

People turn to technology when economies of scale are needed. The technology changes, evolving from stone to steel to silicon, but the maxim remains intact: technology improves the efficacy and speed of business, allowing it to scale innovation.

The Role of Technology in Digital Transformation

Digital transformation is not a new phenomenon brought about by the global pandemic or the adoption of the internet, but the rate of transformation is accelerating because of the rapid advance of technology and the impact of macroeconomic and societal changes that the pandemic introduced. Today we see every industry engaged in digital transformation. From banking to retail, from media and entertainment to education, to manufacturing—virtually every industry is on a trajectory to become a digital business.

This process does not—and cannot—occur overnight. It is a journey that mirrors transformations in nature and that of a human life. A monarch butterfly, with an average lifespan of two to six weeks, can spend up to half that time in its transformational form as a chrysalis. Human beings spend one-fifth of their life growing from infancy to adulthood, with several significant transformations taking place within that period. Transformation takes time, and businesses should expect a similar experience. Human lives are often described as progressing through six distinct phases: fetus, baby, child, adolescent, adult, and elder. Business transformation is also delineated by phases of development, each marked by distinct characteristics and activities:

Phase 1: Task automation

In this stage, digitization leads businesses to turn human-oriented business tasks to various forms of automation, which means more applications are introduced or created as part of the business flow. This began with automating well-defined, individual tasks to improve efficiencies. A common example is interactive voice response (IVR) systems that answer common questions about a product or service but may need to hand them off to a human representative. In this phase, individual tasks are automated but not consistently integrated.

Phase 2: Digital expansion

As businesses start taking advantage of cloud-native infrastructures and driving automation through their own software development, a new generation of applications supports the scaling and further expansion of their digital model. The drivers behind this phase are business leaders who become involved in application decisions designed to differentiate or provide unique customer engagement. For example, healthcare providers are increasingly integrating patient records and billing with admission, discharge, and scheduling systems. Automated appointment reminders can then eliminate manual processes. Focusing on end-to-end business process improvement is the common theme in this phase.

Phase 3: AI-assisted business

As businesses further advance on their digital journey and leverage more advanced capabilities in application platforms, business telemetry and data analytics, and machine learning (ML) and AI technologies, businesses will become AI assisted. This phase opens new areas of business productivity gains that were previously unavailable. For example, a retailer found that 10% to 20% of its failed login attempts were legitimate users struggling with the validation process. The combination of consumer tendency to abandon a brand after a single bad experience with research that finds “on average, loyal customers are worth up to 10× as much as their first purchase” means that denying access by default represents a potentially significant revenue loss.⁸ Behavioral analysis can be used to distinguish legitimate users from bots attempting to gain access. Technology and analytics have enabled AI-assisted identification of those users to let them in, boosting revenue and improving customer retention.

The inevitableness of digitization means every business will make this journey. As with human journeys, each business will experience this transformation at a different pace. At times, external forces will accelerate or decelerate this journey, as we saw during the global pandemic.

Our research, confirmed by the industry at large, indicates that most organizations today are in the second phase of their journey.⁹ This phase is marked by a focus on application and operational modernization, with an increasing tendency to adopt cloud and edge technologies. This is the phase in which many will find their progress decelerated and, for some, blocked by seemingly insurmountable obstacles.

What stands in the way of completing this journey is an existing, rigid framework that governs how applications are developed, delivered, secured, and even integrated. It defines how data should be stored, accessed, and governed. It constrains infrastructure to aging standards. It makes assumptions about applications and their interactions, and about the nature of their users. Existing information architecture frameworks have existed since before the broad adoption of the internet, and well before the era of digitization we find ourselves in today.

For CIOs and IT leaders to successfully navigate the second phase of digital transformation, they must first identify key technologies and capabilities critical to enabling businesses to progress into the third and final phase of digital transformation. These capabilities include the following:

• Using infrastructure as efficiently as possible by delivering applications in a distributed model that includes private and public clouds, data centers, and edge computing

• Expanding and scaling digital operations by adopting site reliability engineering (SRE) operational practices to align technology with business outcomes

• Taking advantage of AI and analytics in both IT and lines of business by reimagining data architectures and governance to adapt to the convergence of operational technology (OT) and IT

• Operating securely at scale by incorporating security as a key component in every aspect of a digital business and embracing app delivery as a core disciplinary domain

Then, with a critical eye, technology leaders must reevaluate their enterprise architecture and determine how best to insert and leverage these technologies and capabilities. It is for this purpose—providing a framework for the transformation of the enterprise architecture—that we have taken on the task of writing this book.

Purpose and Scope

The purpose of this book is to explore the architecture required to successfully navigate the second phase of digital transformation. That transformation evolves the enterprise architecture into one more suited to support an increasingly data-driven and data-dependent digital business.

We’ve written this book for the CIO and the architect, for the IT director and the network engineer. We offer an architecture framework for transitioning IT to operate as a digital business.

We do not dive into the details or offer prescriptive advice on how—or what—to implement. Our goal is to provide a clear picture of the architectural transformation needed to enable a digital business to thrive. That transformation is determined not by us, or by any other expert, but by the technological shifts occurring in every industry and at every layer of the IT stack, which we also discuss.

In Chapter 1, we discuss the changes to existing enterprise architecture needed to infuse the capabilities required by a digital business. Each following chapter explores the trends and technologies driving changes in a specific domain. In Chapter 2, we explore the capabilities enabled by the adoption of cloud and edge technologies and the ability to adapt the deployment location of applications. We then look at the need for application delivery as an IT discipline in Chapter 3, driven by the requirement for digital business to operate safely at scale. The expansion of the data domain to embrace operational data (telemetry) and practices required to scale analytics in order to enable a digital business is the focus of Chapter 4. The rapid evolution of security is the focus of Chapter 5, in which we lay out the foundations for a modern security governance and architecture framework that infuses a security-first approach to digital business.

Chapter 6 covers the emerging need for observability and the expansion of automation from a productivity tool to an innovation accelerator. Finally, in Chapter 7, we dive into SRE as a catalyst for scaling operations in a modern, digital business.

Why We Wrote This Book

Why, indeed. As a group of leaders in a company most often identified simply with load balancing, it may surprise you to learn that F5 has been in the business of helping enterprises design, implement, optimize, and secure enterprise architecture for 25 years.

From its earliest role as a load balancer to securing, delivering, and distributing applications today, F5 has always been an integral partner with business and IT on the topic of architecture. From securing infrastructure against volumetric attacks, to defending against application attacks, to protecting a business against fraud and abuse, F5 is intimately familiar with the inner workings of enterprise architectures in every industry across the globe. In its lengthy history, F5 has also had the privilege of partnering closely with many application providers. These partnerships have been more than strategic, sales-oriented engagements. F5 has spent considerable effort to understand at a deep, technical level how these applications are deployed, delivered, and integrated with other applications and with the business itself.

Even more relevant than its technology portfolio are the leaders, technologists, architects, and strategists who have come together at F5. Hailing from wide-ranging industries—financial services, social networks, transportation, insurance, and other technology firms—the authors have expertise in every layer of the IT and digital business stack. Together, with our deep understanding of technology, we believe that we are uniquely positioned to analyze today’s trends and deliver the insight necessary to identify and articulate the sweeping changes they will have on enterprise architecture.

Conventions Used in This Book

The following typographical conventions are used in this book:

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Indicates new terms, URLs, email addresses, filenames, and file extensions.

Constant width

Used for program listings, as well as within paragraphs to refer to program elements such as variable or function names, databases, data types, environment variables, statements, and keywords.

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¹ Khalid Kark, “Maximizing the Impact of Technology Investments in the New Normal,” Deloitte Insights, February 23, 2021, https://oreil.ly/elI2k.

² Spiceworks Ziff Davis, “The 2022 State of IT,” https://oreil.ly/D795y.

³ Jason Perlow et al., “The 2021 Open Source Jobs Report” The Linux Foundation, https://oreil.ly/xg3zu.

⁴ Vivian Chan, “New Tech Leader Survey Reveals Why the Time for Real-Time Operations Is Now,” PagerDuty, November 10, 2021, https://oreil.ly/ltEok.

⁵ Tara Balakrishnan et al., “The State of AI in 2020,” McKinsey and Company, November 17, 2020, https://oreil.ly/gORVN.

⁶ Chan, “New Tech Leader Survey Reveals Why the Time for Real-Time Operations is Now.”

⁷ “The State of Application Strategy in 2022,” F5, April 12, 2022, https://oreil.ly/FRlOx.

⁸ Douglas Karr, “Customer Retention: Statistics, Strategies, and Calculations,” Martech Zone, May 19, 2021, https://oreil.ly/CvvXA.

⁹ F5, “The State of Application Strategy in 2022.”