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

Measuring organizational progress

We believe the best way to measure progress in a distributed technology operating model is via flow metrics. If you baseline your percentage of complete and accurate lead, wait, and process times, you will not only be able to optimize individual processes but also see whether completely revamped processes would actually help improve the overall outcome. For example, if your compliance process still imposes a wait time of 4 to 6 weeks to get your compute instance provisioned, does it matter that the actual provisioning of an EC2 instance only takes 5 minutes versus the previous 1 hour on your local virtual machine farm?

A word of caution: do not use metrics to compare teams. Problem spaces and technology stacks impose various degrees of complexity, hence comparing the flow between the mainframe team and the digital-natives team is unlikely to provide any insights. And don’t forget to consider building slack into your flow as Martin Fowler...