Book Image

Multi-Cloud Architecture and Governance

By : Jeroen Mulder
Book Image

Multi-Cloud Architecture and Governance

By: Jeroen Mulder

Overview of this book

Multi-cloud has emerged as one of the top cloud computing trends, with businesses wanting to reduce their reliance on only one vendor. But when organizations shift to multiple cloud services without a clear strategy, they may face certain difficulties, in terms of how to stay in control, how to keep all the different components secure, and how to execute the cross-cloud development of applications. This book combines best practices from different cloud adoption frameworks to help you find solutions to these problems. With step-by-step explanations of essential concepts and practical examples, you’ll begin by planning the foundation, creating the architecture, designing the governance model, and implementing tools, processes, and technologies to manage multi-cloud environments. You’ll then discover how to design workload environments using different cloud propositions, understand how to optimize the use of these cloud technologies, and automate and monitor the environments. As you advance, you’ll delve into multi-cloud governance, defining clear demarcation models and management processes. Finally, you’ll learn about managing identities in multi-cloud: who’s doing what, why, when, and where. By the end of this book, you’ll be able to create, implement, and manage multi-cloud architectures with confidence
Table of Contents (28 chapters)
1
Section 1 – Introduction to Architecture and Governance for Multi-Cloud Environments
7
Section 2 – Getting the Basics Right with BaseOps
12
Section 3 – Cost Control in Multi-Cloud with FinOps
17
Section 4 – Security Control in Multi-Cloud with SecOps
22
Section 5 – Structured Development on Multi-Cloud Environments with DevOps

Consolidating and interpreting data from monitoring systems

The only thing a business needs to be interested in here is how events in IT impact the business' operations. To be able to discern this, we need to consolidate and interpret monitoring data.

The big question is this: when is data from monitoring relevant to the business? It doesn't make sense to inform a business leader about the performance of CPUs in virtual machines, but it does make sense to inform him or her when system capacity is lacking and hindering the speed of processing transactions. In that case, the business might lose money since transactions might be processed too slowly or, worse, dropped because of timeout failures.

When is data relevant to a business? In short, data should enable business decisions. Deploying extra virtual machines or scaling out environments are not business decisions. These are technical decisions. A business decision would be to launch a new product at a given moment...