Technology Operating Models for Cloud and Edge E-Book

Ahilan Ponnusamy

• Herausgeber: Packt Publishing
• Kategorie: Wissenschaft und neue Technologien
• Sprache: Englisch

Seitenzahl: 348

Veröffentlichungsjahr: 2023

Beschreibung

Cloud goals, such as faster time to market, lower total cost of ownership (TCO), capex reduction, self-service enablement, and complexity reduction are important, but organizations often struggle to achieve the desired outcomes. With edge computing gaining momentum across industries and making it possible to move workloads seamlessly between cloud and edge locations, organizations need working recipes to find ways of extracting the most value out of their cloud and edge estate.
This book provides a practical way to build a strategy-aligned operating model while considering various related factors such as culture, leadership, team structures, metrics, intrinsic motivators, team incentives, tenant experience, platform engineering, operations, open source, and technology choices. Throughout the chapters, you’ll discover how single, hybrid, or multicloud architectures, security models, automation, application development, workload deployments, and application modernization can be reutilized for edge workloads to help you build a secure yet flexible technology operating model. The book also includes a case study which will walk you through the operating model build process in a step-by-step way.
By the end of this book, you’ll be able to build your own fit-for-purpose distributed technology operating model for your organization in an open culture way.

Leseprobe

Technology Operating Models for Cloud and Edge

Create your purpose-built distributed operating model for public, hybrid, multicloud, and edge

Ahilan Ponnusamy

Andreas Spanner

BIRMINGHAM—MUMBAI

Technology Operating Models for Cloud and Edge

Copyright © 2023 Packt Publishing

All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews.

Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the authors, nor Packt Publishing or its dealers and distributors, will be held liable for any damages caused or alleged to have been caused directly or indirectly by this book.

Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information.

Group Product Manager: Preet Ahuja

Publishing Product Manager: Surbhi Suman

Senior Editor: Athikho Sapuni Rishana

Technical Editor: Arjun Varma

Copy Editor: Safis Editing

Project Coordinator: Ashwin Dinesh Kharwa

Proofreader: Safis Editing

Indexer: Subalakshmi Govindhan

Production Designer: Shyam Sundar Korumilli

Marketing Coordinator: Rohan Dobhal

First published: July 2023

Production reference: 1130723

Published by Packt Publishing Ltd.

Grosvenor House

11 St Paul’s Square

Birmingham

B3 1R

ISBN 978-1-83763-139-1

www.packtpub.com

To my wife, Kalpana, and kids, Arjun and Krishna, for giving me the time and space to work on this book.

– Ahilan Ponnusamy

To my family and friends near and far, small and tall, learning fast and slow, supporting me with my small, medium, big, and crazy ideas. You always have a place in my heart And a special thanks also to all the people who provide continuous inspiration through their technology understanding, pure talent or skills, positive attitude, support and feedback.

– Andreas Spanner

Forewords

This book is very timely. How we operate going forward and how we organize ourselves as IT organizations is a question on many people’s minds. The advent of the cloud made many things easier but, in reality, it created even more variability in the technology stacks that organizations deal with. The toolkit of IT professionals keeps getting bigger, with SRE and platform engineering being notable recent additions and new ideas coming up nearly every week.

What better than to have a book that helps put structure to the problem and demystify some of the buzzwords to cut it back down to what really matters? This book will help IT professionals find approaches to structure their organization, and it does so pragmatically and based on real-life experiences. Real life is messy and every organization will need to make decisions in their context. This book will not give a one-size-fits-all answer; it will help you make your own decisions.

I have spent many hours discussing with Andreas how organizations should react to the challenges of modern technologies being adopted in existing organizations and I am really glad to hold in my hands his best thoughts. With this book, he and his co-author, Ahilan, share so many years of experience with you that I am sure you will find many ideas here that will help you and your organization. It does not just cover the organizational model but also the interaction with technology – it is, after all, a symbiotic relationship when done well.

Let this book be one of the guides you use on your road to improvement. It will surely be one of mine and will take a place on my bookshelf next to other excellent books that make up the canon of modern IT thinking.

Mirco Hering,

Global Transformation Lead at Accenture

In the ever-evolving landscape of technology, businesses now find themselves at a pivotal moment. The exponential growth of data generated in real time in an increasingly distributed manner, and the sudden leap forward in the domain of Artificial Intelligence (AI), with foundation models making massive scaling possible and allowing enterprises to accelerate the integration of advanced AI capabilities into their operating model, represent both a challenge and an opportunity for businesses, which are often already trying to cope with existing digital transformation and cloud technology adoption challenges. It is in this context that Technology Operating Models for Cloud and Edge emerges as a guiding light, providing insights and strategies for organizations seeking to navigate this transformative era and build a strong technical foundation based on enterprise open source technologies for rapid adoption of change.

In this book, Andreas and Ahilan explore the complexities of defining a cloud operating model, the nuances of enterprise technology landscapes, and the limitations of traditional approaches and models such as Bimodal IT. You are empowered to forge a new path forward, leveraging a practical roadmap as well as generic, reusable patterns for building consistent and adaptive operating models across cloud and edge environments. Having had the privilege to closely collaborate with both authors in the context of our work advising organizations across a wide range of sectors, I can definitely see the wealth of their collective experience distilled into a set of actionable principles that can support technology strategists and cloud practitioners alike in navigating the technological complexities inherent to defining and delivering cloud operating models, ultimately harnessing the power of distributed architectures and leveraging their inherent advantages to optimize performance, scalability, and resilience. I am looking forward to embedding these principles on the ground in our future transformative engagements.

Vincent Caldeira,

Chief Technology Officer, APAC at Red Hat

Any enterprise can be decomposed into four components: (a) business model, (b) operating model, (c) technology model, and (d) culture. A digital transformation journey, when done properly, attempts to transform all four components. While each of these components is critical, given that we live in the digital era, the transformation of the technology operating model is absolutely imperative if you want to achieve exponential business outcomes.

The cloud had a tectonic impact on technology operating models. It shifted the way technology was architected, designed, and maintained. Cloud adoption has been wide-ranging, and some might even claim that the impact of the cloud qualifies as being planetary scale. However, just doing a lift and shift to the cloud ticks the box but does not help transform, and exponential outcomes will continue to remain elusive. And while enterprises have struggled to demonstrate value from their cloud initiatives, edge computing and architectures have been introduced into the mix, driven by real business use cases and AI-based aspirations.

Ahilan and Andreas provide an excellent framework and approach for enterprises to build their own distributed technology operating models. They sweep up and provide clarity on various types of cloud architectures, as well as encompass edge computing into their approach. I particularly enjoyed the value addition they provide by describing, in a fair bit of detail, open practices from the open practices library, which can be used to build this operating model from within. This collaborative approach will ensure intrinsic buy-in from key stakeholders toward the distributed technology model and go a long way in ensuring its timely adoption. Besides baking their decades of practical experience into the framework, the book also uses a very detailed, anonymized use case as a simulation, to bring out the methods as well as the learning in a real-life setting. While the framework created by the authors comprising streams, dimensions, and items is applied to the technology operating model, it is quite easily extensible to other components of an enterprise’s transformation journey, such as the business model and operating culture.

Digital transformation is easier said and read than done. I recommend you pick up Technology Operating Models for Cloud and Edge on your next visit or click to the bookstore, consume its content diligently, then apply the learning to real-life scenarios, and significantly enhance the probability of successfully transforming your own technology operating model.

Neetan Chopra,

Chief Digital and Information Officer at IndiGo

Contributors

About the authors

Ahilan Ponnusamy is a GTM specialist for the application platform at Red Hat based in Singapore. He enjoys working with customers to deliver accelerated business outcomes on hybrid cloud architectures and cloud-native application development and delivery practices. Ahilan completed his master’s in computer applications from MKU, India in 1999. His work history includes Philips CE in Eindhoven Netherlands, BEA technologies as a member of customer-centric engineering and support in India and USA, pre-sales tech lead for the cloud platform team at Oracle USA, principal platform engineer at Pivotal(VMware), and global architect at Dell Technologies, Singapore.

Originally from Madurai, Tamil Nadu, India, Ahilan currently resides in Singapore with his wife and two boys.

Andreas Spanner is currently working as a chief architect within the CTO organization at Red Hat. Prior to his role as the chief architect for Australia and New Zealand, Andreas worked across the globe in many different industries ranging from automotive, manufacturing, and supply chain logistics to telco, FSI, and the public sector in areas such as ERP, CRM, HR, payroll data, process migrations, internet security appliances, and B2B marketplaces. He has delivered Just-In-Time logistics and series production systems for customers such as BMW, Volkswagen, and Mercedes.

Andreas completed his engineering degree in Germany and got his first Commodore 64 when he was 12 years old. Originally from Bavaria, Andreas now lives in Sydney, Australia.

About the reviewers

With over two decades of experience in the technology industry across the globe, Niraj Naidu is a recognized thought leader in driving large-scale business and digital transformation initiatives and optimizing technology strategies. He has excelled in leading enterprise architecture and engineering practices, delivering value, and stewarding impactful customer outcomes. With expertise in strategic architecture delivery and agile software development, Niraj has implemented enterprise technology solutions that add value and stability to businesses. As a customer-focused technology strategist and leader, he continues to provide strategic guidance to help Fortune 500 organizations realize and maximize the value of their technology investments.

My sincerest thanks to the authors of this well-researched technical book for their invaluable contributions. Their expertise, leadership, meticulous approach, and practical insights have not only created a valuable resource for the technical community but have also elevated the understanding and application of the subjects covered. Their dedication to providing comprehensive and accessible content has made this book an indispensable guide.

John Heaton is an innovator, technologist, and leader who builds human-centered organizations enabled by innovative data-driven technology. John has worked independently and for large multinational organizations in a variety of roles covering technology governance, risk and compliance, enterprise strategy and architecture, big data and analytics, and portfolio and program management from conception through to implementation. John now works within organizations to design, build, and operate businesses focused on driving digital transformations. Recently, he helped develop and implement the digital strategy and operating model launching a successful 100% cloud-native digital bank.

Guillaume Poulet-Mathis is a senior technology executive with over 15 years of experience in enabling product innovation. He currently serves as the director of product engineering at Optus, an Australian tier-1 telecommunication company, where he is responsible for the engineering division building the Optus Living Network, a collection of unique on-demand and real-time network features redefining connection experiences for Optus customers. Guillaume spearheaded several technological innovations, such as cloud-native voice network functions and the introduction of an event-driven microservices platform on Kubernetes, enabling engineers to build products seamlessly spanning digital channels and telco network elements.

I would like to thank the numerous open source communities and advocates who have contributed to making technology more accessible and resilient. It is the contributions of passionate individuals that are improving our ways of working and powering the right level of optimism to solve today’s world problems with the power of many.

Sharad Gupta leads the Pre-Sales Solutions Engineering team at UiPath and has previously led similar teams at Pivotal (VMware) and DataStax. Sharad’s passion is to help customers implement modern architecture practices for resilient and scalable business operations.

In his past roles, Sharad led and advised on enterprise architecture and integration patterns for Fortune 500 companies. He received his master’s in computer engineering from Drexel University and an MBA from Fisher College of Business at The Ohio State University.

With constant curiosity about the world around us, Sharad enjoys engaging in discussions on topics such as process improvement, behavioral economics, business strategy, and business transformation.

Thenna Raj is an outcome-driven technology leader with over 20 years of experience in technology strategy, architecture, and delivery in complex environments across a range of industries, including retail, government, telecommunications, and financial services.

He specializes in delivering strategy and architecture functions across various business brands. Over the course of his career, Thenna has worked across systems engineering and design, business analysis, product management, and consulting roles. Thenna has extensive experience working in an agile environment across various organizations, and his diverse background provides him with the ability to translate strategic objectives into pragmatic outcomes.

Table of Contents

Preface

Part 1: Enterprise Technology Landscape and Operating Model Challenges

1

Fundamentals for an Operating Model

Why this book?

Defining the cloud and the edge – hybrid cloud, multi-cloud, plus near and far edge

Setting the organizational context – strategy, culture, capabilities, operating model, and more

Strategy

Capability

About culture and why we are recommending open practices

Operating model

Engineering and operations

Platforms

Guiding principles and guardrails

Being antifragile to change

Metrics

On teaming

On architecture

Summary

Further reading

2

Enterprise Technology Landscape Overview

Categorizing the enterprise technology landscape

The diversity and complexity involved

Application architecture

Infrastructure architecture

Difficulties in adopting a standard operating model

Resist change to reduce risk and improve stability

Embrace change to reduce risk and improve innovation velocity

Summary

Further reading

3

Learnings From Bimodal IT's Failure

Introduction to bimodal IT

Enterprise IT management with bimodal IT

The challenges and limitations of bimodal IT in the distributed future

Summary

Further reading (and listening)

4

Approaching Your Distributed Future

Top reasons for hybrid cloud adoption

Business reasons

Technology reasons

The external factors

Regional compliance requirements

Infrastructure limitations

Impact of 5G/6G, IoT, and edge computing

Summary

Further reading

Part 2: Building a Successful Technology Operating Model for Your Organization

5

Building Your Distributed Technology Operating Model

Building your operating model for the distributed future

Starting at the end

Managing your stakeholders

Selecting your dimensions

Scoping your dimensions

Detailing your dimensions

Summary

Further reading

6

Your Distributed Technology Operating Model in Action

Simulated case study

Case study overview

The IT landscape

Challenges and threats

Proposed next steps

Building an operating model for the Resurgence program

Building the distributed cloud and edge operating model

Defining streams

Selecting dimensions

Scoping dimensions

Detailing dimensions

Measuring progress

Summary

Further reading

7

Implementing Distributed Cloud and Edge Platforms with Enterprise Open Source Technologies

Building a Distributed Cloud and Edge Platform

Platform and Platform team

Implementing the platform based on the operating model

The power of enterprise open source

Mapping platform capabilities

Building the Resurgence platform detailed architecture

Summary

Further reading

8

Into the Beyond

Operating model challenges

Becoming antifragile

Understanding how open source connects antifragile, undifferentiated heavy lifting, and tech debt

Measuring organizational progress

Target operating model – gap analysis and roadmap

How much architecture do we need?

The ivory tower mindset

Understanding your organization’s life cycles

Prioritization and making the right choice

Managing lock-in

Multiple authorized operating model creators

Understanding Edge

Sustainability

Summarizing our journey thus far

What’s next?

Summary

Further reading

Acknowledgments

Index

Other Books You May Enjoy

Preface

Speeding up time to market, lowering the total cost of ownership (TCO), reducing CapEx, enabling self-service, and reducing complexity are important cloud goals; however, the desired outcomes don’t always materialize. With edge computing making its way through all industries on top of ongoing journeys to the public cloud (and back), it’s vital to share working recipes for organizations to find their preferred way of extracting the most value out of their technology investments.

This book demonstrates a practical way of building a strategy-aligned operating model while considering a variety of related aspects such as culture, leadership, team structures, metrics, intrinsic motivators, team incentives, tenant experience for development and product teams, platform engineering, operations, open source, and technology choices – just to name a few. You’ll understand how single, multi, or hybrid cloud architectures, security models, automation, application development, workload deployments, and app modernization can be re-utilized for edge workloads to help you build a secure, yet flexible technology operating model. You will learn how to build a distributed technology operating model using a case study.

By the end of this book, you’ll be able to build your own fit-for-purpose operating model for your organization in an open culture way.

Who this book is for

As a cloud architect, solutions architect, DevSecOps or platform engineering lead, program manager, CIO, CTO, or chief digital officer, if you’re tasked to lead cloud or edge computing initiatives, create architectures and enterprise capability models, align budgets, or show your board the value of your technology investments, then this book is for you. This book will help you define and build your cloud and edge computing capabilities around a fit-for-purpose technology operating model.

What this book covers

Chapter 1, Fundamentals for an Operating Model, looks at the challenges that the journey to the cloud has thrown at organizations and why. It goes through a rich set of examples to look at different ways to define key components of an operating model: the operating model dimensions. It also introduces key terms from engineering and operations and distinguishes between platform and product engineering and SRE. This chapter closes with thoughts on how to construct metrics, teaming, and how Conway’s law affects your architecture.

Chapter 2, Enterprise Technology Landscape Overview, gives an overview of common enterprise technology landscape components. It distinguishes between systems of innovation, differentiation, and systems of record, and examines the associated change cadence and challenges related to these cadences by expanding the classification from applications to infrastructure. It completes the discussion by looking into the difficulties around the adoption of a standard operating model because of the distinguished traits across that classification.

Chapter 3, Learnings From Bimodal IT’s Failure, examines closely why the Gartner Bimodal IT approach never yielded the results expected and extracts the learnings out of it in order to apply them to the distributed technology operating model. It looks at the change cadence differences between mode 1 and mode 2. It closes by highlighting that there is no endorsed bimodal architecture that combines a working approach between mode 1 and mode 2 estates.

Chapter 4, Approaching Your Distributed Future, focuses on the imminent distributed future. It looks at the reasons why the future is distributed and revisits hybrid and multi-cloud definitions while shedding light on specific business and technology reasons why the public or single cloud cannot be a target state for organizations. It spends time on different edge classifications to get a better handle on different viewpoints in light of worthwhile use cases. It closes by looking at emerging trends and external factors such as compliance, mergers, and acquisitions.

Chapter 5, Building Your Distributed Technology Operating Model, explains in detail the building blocks for a distributed operating model across the cloud and edge. It starts off by showing the steps toward the desired outcome in the Starting at the end section and introduces an operating model dashboard to track outcomes, work in process (WIP), and dependencies. It presents workshop-leading practices to help lead teams along the forming, storming, norming, and performing life cycle. The chapter also walks through more than 30 dimensions to consider and choose from for the operating model. It also provided numerous suggestions for further reading if you want to dive deeper into any of the research underpinning our recommendations.

Chapter 6, Your Distributed Technology Operating Model in Action, introduces an anonymized real-life use case and walks through how this organization built its distributed technology operating model in a hybrid multi-cloud and edge context.

It walks through the step-by-step process of utilizing already introduced templates and new assets that can be reused for the operating model development process.

Chapter 7, Implementing Distributed Cloud and Edge Platforms with Enterprise Open Source Technologies, walks through an operating model-based platform implementation example. It connects real work architecture, design, and implementation with the previously developed operating model. It shows how requirements and principles from the operating model flow into technology selection and how they map to capabilities.

Chapter 8, Into the Beyond, wraps the book up. It introduces additional aspects such as antifragility, geographically disparate (non-)autonomous operating models; different ways to measure progress; how tech debt, undifferentiated heavy lifting, and open source are connected; gap analysis; and roadmap development. It revisits prioritization and decision-making and introduces a quick way to make the best possible decision with the often limited information available.

To get the most out of this book

With prior knowledge of cloud computing, application development, and edge computing concepts, you will get the most out of this book.

You may appreciate it more if you are in a role such as CxO, senior business/IT leadership, enterprise architecture, or the development and operations teams.

Conventions used

There are a number of text conventions used throughout this book.

Code in text: Indicates code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles. Here is an example: “Prakash captured it and followed a similar approach to help the steam team define the transition states for the PTE.Platform.UnifiedPlatform item.”

Bold: Indicates a new term, an important word, or words that you see onscreen. For instance, words in menus or dialog boxes appear in bold. Here is an example: “For example, the two dependencies that were identified under LA.Customer were LA.Architecture.Resilience and LA.Architecture.Security.”

Tips or important notes

Appear like this.

Get in touch

Feedback from our readers is always welcome.

General feedback: If you have questions about any aspect of this book, email us at [email protected] and mention the book title in the subject of your message.

Errata: Although we have taken every care to ensure the accuracy of our content, mistakes do happen. If you have found a mistake in this book, we would be grateful if you would report this to us. Please visit www.packtpub.com/support/errata and fill in the form.

Piracy: If you come across any illegal copies of our works in any form on the internet, we would be grateful if you would provide us with the location address or website name. Please contact us at [email protected] with a link to the material.

If you are interested in becoming an author: If there is a topic that you have expertise in and you are interested in either writing or contributing to a book, please visit authors.packtpub.com.

Share Your Thoughts

Once you’ve read Technology Operating Models for Cloud and Edge, we’d love to hear your thoughts! Please click here to go straight to the Amazon review page for this book and share your feedback.

Your review is important to us and the tech community and will help us make sure we’re delivering excellent quality content.

Download a free PDF copy of this book

Thanks for purchasing this book!

Do you like to read on the go but are unable to carry your print books everywhere? Is your eBook purchase not compatible with the device of your choice?

Don’t worry, now with every Packt book you get a DRM-free PDF version of that book at no cost.

Read anywhere, any place, on any device. Search, copy, and paste code from your favorite technical books directly into your application. 

The perks don’t stop there, you can get exclusive access to discounts, newsletters, and great free content in your inbox daily

Follow these simple steps to get the benefits:

Scan the QR code or visit the link below

https://packt.link/free-ebook/9781837631391

Submit your proof of purchaseThat’s it! We’ll send your free PDF and other benefits to your email directly

Part 1:Enterprise Technology Landscape and Operating Model Challenges

In this part, you will get an introduction to key concepts associated with a cloud operating model, see an overview of the enterprise technology landscape, and learn how Gartner’s pace layered architecture can be used to classify applications and infrastructure based on key characteristics. It also covers why previously hyped concepts such as Bimodal IT didn’t take off, distills knowledge about its limitations, and explains the reasons why the future will be distributed for organizations.

This part has the following chapters:

Chapter 1, Fundamentals of the Cloud Operating ModelChapter 2, Enterprise Technology Landscape OverviewChapter 3, Addressing Diverse Technology Landscapes with Bimodal IT and Its LimitationsChapter 4, Approaching Your Distributed Future

1

Fundamentals for an Operating Model

In this first chapter, we will set the context for the remainder of this book and clarify some terms. In an industry full of buzzwords and ambiguity, we felt that level-setting and providing context deserves a chapter of its own. This will help you understand the rest of this book and communicate better based on agreed-upon terms and associated semantics.

In this chapter, you will learn about various concepts related to your strategy, goals, mission, vision, and objectives by looking at different frameworks. Additionally, you will explore different definitions of operating models and extract essential insights from them. This chapter will also delve into the significance of culture in creating high-performing organizations and teams, along with other important topics, such as capability and platform engineering. Overall, this chapter aims to equip you with a comprehensive understanding of the key elements that are necessary for successful organizational management.

Our goal is to provide you with answers to the following inquiries:

What exactly is an operating model and what is its significance?How does an operating model relate to strategy?What frameworks are available concerning operating models?How can you effectively implement an operating model in your organization?

By addressing these questions, we hope to equip you with a comprehensive understanding of operating models and their role in organizational success. By the end of this chapter, you will know what an operating model is and learned about business operating models and how we can translate them into technology operating models.

Why this book?

Simon Oliver Sinek is a British-born American author and inspirational speaker. He is the author of five books, including Start With Why and The Infinite Game. Let’s follow Simon Sinek’s advice and Start with Why. Every organization’s “why to use the cloud” could be subtly different. However, there are common ones such as CapEx, OpEx, or risk reduction, as well as faster time to market. Getting the desired return on investment (ROI) out of moving to the public cloud is not as easy as it looked when the hyperscalers sales team did their presentations. We are not going to cite percentages here, such as “X% of all cloud migrations fail.” First, we don’t have a consistent and overarching definition of “failure,” nor a specific one for each case. Second, every “failing” initiative has brought learnings with it. And third, we need to appreciate these first movers because we benefit from their learnings. However, research suggests that a significant number of cloud migrations do not go as smoothly as initially anticipated.

The reasons for limited cloud success can vary from organization to organization. Here are some examples:

Unclear direction-setting attempts like ‘cloud first’ left teams unsure of their future or what to do.Moving to the Cloud is mistaken for innovation.Goals to move large amounts of applications to the public cloud in an established enterprise without significant change management are not realistic.Companies experienced massive margin pressure because the cost of existing infrastructure didn’t disappear as quickly as anticipated.Operational expenditure (OpEx) and bill shock from the hyperscalers occurred due to the use of popular high double-digit gross-margin cloud services (compared to single-digit gross margins for owned hardware).Lift and shift shortcuts do not leverage Cloud on-demand scale-out/in features and, as a result, do not lead to the desired business demand-aligned pricing.Data mobility needs and associated egress costs were not taken into account.Marketing metrics driving wrong behaviors: “30 apps in 30 days” slogans sound good; however, the objectives were wrongly focused on the number of applications moved to the cloud instead of creating and deploying cloud-ready, cloud-optimized, and cloud-native applications that generate a return on investment (ROI).Seeing the public cloud as the ultimate target state: Shortcomings of architecting for an edge-inclusive distributed future led to low-ROI efforts of moving non-fit workloads to a public cloud environment.Unrealistic expectations leading to unrealistic timelines: For organizations with hundreds or thousands of applications, it is unrealistic to expect to move quickly, assuming application refactoring will happen simultaneously across hundreds of applications that can be worked on at the same time.Focus on technology instead of transitioning people, processes, and culture to enable cloud-ROI through microservices, containers, DevSecOps, GitOps, Agile delivery, and self-service.Data sovereignty, residency, and data concentration risk need mitigation through resilient architectures, which increase efforts and timelines.New cybersecurity threat vectors - the need for a consistent security posture across heterogeneous infrastructure footprints is more complex than traditional perimeter-based security.Multiple proprietary public cloud implementations required reinventing the wheel and offered little reuse.Even DIY private cloud builds, where the team had intrinsic business knowledge but followed a ‘build it and they will come’ approach, had limited success with adoption.

The main root cause of these challenges often lies within “organic – just do it” cloud journeys and the fact that these journeys didn’t start with an “operating model first” approach. Now, if we take all of these challenges and add edge computing to them, the chances of success become even less likely. The added number of edge locations, hardware, platforms, deployments, applications, data, and security requirements amplify the complexity. This shows what edge computing can potentially bring in terms of these challenges – it calls for a different, less fanboy (and girl!)-ish approach. And that’s why we recommend an operating model first approach.

The recommendation is to not start with logos that we want on our CVs, or our love for technology – not even a specific use case. We must start with the operating model. Even though operating models don’t last forever, they are usually longer lived than strategies and hence a good fit to use as an anchor. Operating models – if done well – are the glue between a company’s strategy and the people that make this strategy come alive during its execution.

Defining the cloud and the edge – hybrid cloud, multi-cloud, plus near and far edge

Cloud computing is a model for delivering computing resources, such as servers, storage, databases, and other services, over the internet. In cloud computing, users can access and use these resources on demand, without having to own and maintain their computing infrastructure.

Cloud computing is typically provided by third-party cloud service providers who manage and maintain the underlying hardware and software infrastructure, as well as provide the necessary network connectivity, security, and support services.

There are three main types of cloud computing services:

Infrastructure-as-a-Service (IaaS): This provides users with access to computing infrastructure such as virtual machines, storage, and networking resourcesPlatform-as-a-Service (PaaS): This provides users with a platform for developing, running, and managing applications without having to worry about the underlying infrastructureSoftware-as-a-Service (SaaS): This provides users with access to software applications that are hosted and maintained by the cloud provider

Hybrid cloud is a computing environment that combines both private and public cloud infrastructures. With hybrid cloud, organizations can use both on-premises (private cloud) and public cloud-based resources. Co-location providers such as Equinix count as on-premises and/or private clouds.

This approach enables organizations to take advantage of the scalability and cost-effectiveness of public cloud resources while maintaining sovereignty over their sensitive data and applications through private cloud resources. Organizations usually run their non-cloud-ready applications using 24/7-always on or monolithic core systems of records-type applications such as non-SaaS ERP, CRM, finance, and HR systems, such as on-premises ones.

Multi-cloud refers to a cloud computing environment that involves using multiple (public) cloud service providers to host different parts of an organization’s computing infrastructure or workloads. In other words, instead of relying on a single cloud provider, a multi-cloud strategy involves using multiple cloud providers in a coordinated manner.

Edge computing, on the other hand, involves processing data closer to where it is generated, rather than in a centralized cloud environment. It refers to the use of decentralized computing resources that are located at or near the edge of a network, rather than in a centralized data center. This can improve the speed and efficiency of data processing and reduce latency. Edge computing typically involves small, distributed computing resources located at the edge of the network, such as sensors, small form factor compute devices, robots, or edge servers. Depending on the distance from the user or data center, edge computing can be further categorized into near and far.

The associated benefits allow organizations to process data closer to the source of the data, which can reduce latency and improve the performance of applications and services and reduce network design complexity. By including edge computing in a hybrid and multi-cloud model, organizations can take advantage of the flexibility and scalability of the cloud, while also being able to process data in real time at the edge of the network. This ultimately enables organizations to address requirements and execute use cases that were not possible before.

Together, cloud and edge computing create a comprehensive computing environment that combines the benefits of both approaches. For example, an organization might use a hybrid cloud to store and manage its data and run both cloud-native and monolithic applications while using edge computing to process data generated by IoT or other edge devices in real time.

Setting the organizational context – strategy, culture, capabilities, operating model, and more

In today’s world, acronyms are everywhere! A three-letter acronym (TLA) can mean different things: OSS could mean Open Source Software or, in a telco context, Operational Support System, Open Sound System (Unix), or something else. And as you know, there are plenty of other examples out there. So, you understand why it’s important to set the context in your organization too. Here’s an example from a previous employer of mine: PS stood for professional services, as well as pre-sales. You can imagine how many unnecessarily confusing situations that caused. So, my recommendation is to kill not Bill, but ambiguity. This is worth it. The practices we will introduce in Chapter 5, Building Your Distributed Technology Operating Model, will help you achieve this.

In this first chapter, we will provide some context and a description of what we mean by the terms and terminology we use. We are slaying buzzwords right here, right now. Let’s get to it.

Strategy

A strategy is an integrated set of choices an organization makes, without really knowing if they work. A strategy is a set of hypotheses that you think will help you win on a playing field of your choosing. So, a strategy is based on a theory. That theory should be coherent and executable by the people in your organization right now. What winning looks like is defined by the strategic goals you define. Ideally, a strategy is communicated to your colleagues so that, as a team, you can all pull in the same direction. As an example, regarding the playing field of your choosing the Amazon bookstore decided to extend their playing field from an online bookstore. First, it was to become “The Everything Store” and then a public cloud service provider.

To clarify how to develop and set an operating model in the context of our strategy and goals, we can utilize an existing framework from the Business Motivation Model (BMM). The OMG Group’s BMM includes the Means to End framework. Means is the action plan, while End is the desired result or aspiration. You can study the BMM meta model via the link provided in the Further reading section and learn about the entities and relationships in more detail, but it’s not necessary to do so for this book.

The Means to End framework aims to put concepts such as Mission, Vision, Strategies, Goals, Objectives, and Tactics into context and defines a common language. A common language is a very powerful enabler. The information exchange and hence learning and understanding that occurs across teams, even from within the same organization because of that common language, is phenomenal.

I’ve run many workshops where this simple framework created a lot of clarity for the customer’s team, which is why I recommend it. I also added a link in the Further reading section in case you want to facilitate a workshop yourself.

Introducing the Means to End framework (see Figure 1.1) to workshop participants is an effective way to link their vision (for example, we want to be a digital bank with a brick-and-mortar experience) and mission (we prioritize building out our digital CX), as well as their strategy to goals, and distinguish between strategic goals (for example, grow assets under management beyond $80 billion for a bank) and associated tactical objectives (for example, automate 100% of the loan origination process). At this point, a valid tactic could be to fund a project that digitizes the enter loan origination process and the associated strategy to build out straight-through processing for all asset-related customer touchpoints:

Figure 1.1 – The Means to End framework

So, even though we ultimately talk about strategy, let’s take a quick detour to see how strategy is connected to the other elements you encounter in your organization. This will be useful later when we define the “success criteria” – that is, our goals and objectives – as we move toward our target state operating model. Let’s quickly go through the different elements of the framework and give some examples of what we mean by that:

A vision represents an organization’s future and is answering the question of who we are going to be in 2, 3, or 5 years from now.The mission is the means to achieve the vision (end) and sets the direction by stating what organizations do daily to achieve our vision.Goals are connected to the vision because the goals that have been set need to align with your organization’s vision. Because we are in the “strategic” layer, goals are strategic and hence answer the question, “What strategic goals do we need to hit to make this vision a reality?” Goals are longer-term but should be narrow enough and have qualitative definitions so that objectives can be created for them.Strategies are the means we choose to achieve our strategic goals (end). In this layer, we are figuring out what high-level approaches (programs of work, products, or services) and hypotheses are being funded to achieve our goals. Strategies are usually broad in scope and long-term compared to tactics. Think of a program and product instead of a project. As you can see, the mission informs the strategies.Objectives are steps toward a goal. They should be specific and of a qualitative nature with an end date to ascertain whether the goal has been reached or not. Objectives need to be linked to strategic goals; otherwise, you need to ask yourself: Why am I doing this?Finally, we have tactics. What tactical projects or tasks (means) do we employ to achieve our objectives (end)? Tactics are short-term and narrower in scope – think project or feature rather than program or product. Strategies inform the tactics, and the tactical objectives should support the strategic goals. To summarize, every objective you achieve brings you closer to reaching the associated strategic goal.

But I need to utter a word of warning: you can run into difficulties distinguishing between the strategic and tactical layers at times during workshops. A pro tip is to keep in mind that strategies and goals are usually longer-term and broader in scope. Tactics, on the other hand, are shorter-term and narrower in scope. The following diagram shows how you can outline the context of your strategy on a single page:

Figure 1.2 – Visualizing the big picture – a single-page overview of strategic context

And how is this related to the cloud operating model I came here for, you might ask? Great question! A business operating model needs to support the company’s strategy. For example, if you want to grow revenue and venture into customer segments by bringing new features or products faster to market while utilizing Agile and microservices but your IT operating model is set up to stabilize your systems of records, you might end up wasting lots of effort and money. So, the operating model needs to align if you want to be efficient and effective.

And the same is true for your cloud operating model and strategy. If you want to reduce your time to market, attract and retain talent, reduce OpEx, be more innovative, reduce tech debt, or improve your bottom or top line, then you need to do more than just select a hyperscaler to run on.

In short, your operating model needs to encompass things such as funding (project or product?), team setup (Conway’s law or Dunbar’s number?), platform (where and what to abstract?), cultural practices (Open Practice Library and/or DevSecOps?), and much more. This is the core of your cloud operating model. We will cover this in more detail in Chapter 5.

Capability

Capability is, in general, defined as the power or ability to do something. The Open Group Architecture Framework (TOGAF) defines it as an ability that an organization, person, or system possesses