Application Delivery and Load Balancing in Microsoft Azure
by Derek DeJonghe and Arlan Nugara
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Preface
This book is intended for cloud solution architects and software architects looking to distribute load across multiple servers, applications, or regions within Microsoft Azure. Load balancing is used to improve performance and availability; however, the layer that is used to perform the load balancing action has evolved to become much more. This layer of a web application stack is known as the data plane, and it is used to transmit requests and connections to an application. The data plane can be used to validate, route, and manipulate inbound communication from clients to an application. By building up your control of this layer, you can optimize and facilitate your exact use case.
Throughout this book you will learn how load balancing and the data plane can be integral facets of your application delivery. We will discuss load balancing and application delivery in general before moving on to inform you about the available native options within Azure and explaining the software-based data plane solution known as NGINX (pronounced engine-ex), which can be used independently of your infrastructure provider. We will then discuss integrating NGINX with Azure and how native Azure services paired with NGINX can be complementary.
Once we have an understanding of the load-balancing data plane options available to us, well detail governance and monitoring of a given solution within Azure. Regarding this topic, well introduce the NGINX platform solution for control and configuration known as NGINX Controller. Finally, well wrap up with a section about security and how we can enable our data plane to be an invaluable asset in security and threat management.
While the examples and context will be specific to Microsoft Azure, the methodologies and overarching concepts will hold true for any cloud or infrastructure provider. It is our hope that those ideas impact you the most and enable you to design and implement secure, highly scalable, and highly available solutions.
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