Book Image

Technology Operating Models for Cloud and Edge

By : Ahilan Ponnusamy, Andreas Spanner
Book Image

Technology Operating Models for Cloud and Edge

By: Ahilan Ponnusamy, Andreas Spanner

Overview of this book

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.
Table of Contents (13 chapters)
1
Part 1:Enterprise Technology Landscape and Operating Model Challenges
6
Part 2: Building a Successful Technology Operating Model for Your Organization
8
Chapter 6: Your Distributed Technology Operating Model in Action

Difficulties in adopting a standard operating model

As explained earlier in this chapter, organizations have a diverse application and infrastructure landscape with unique characteristics based on their architecture and the business requirements they serve. Therefore, it is difficult to adopt a standardized operating model across the layers since emerging technologies such as edge computing and AI will further increase this complexity. Focusing on just the infrastructure layer alone, the Systems of Innovation layer delivers the most value with faster and safer experimentation capabilities to test new ideas, end-to-end automation, self-service, and horizontal scalability. But for enterprises that deliver most of their business services with traditional Systems of Record applications, moving to a modern infrastructure may not be feasible. Two opposing viewpoints are in play:

  • Resist change to reduce risk and improve stability
  • Embrace change to improve innovation velocity and...