Book Image

Google Cloud Platform for Architects

By : Vitthal Srinivasan, Loonycorn , Judy Raj
Book Image

Google Cloud Platform for Architects

By: Vitthal Srinivasan, Loonycorn , Judy Raj

Overview of this book

Using a public cloud platform was considered risky a decade ago, and unconventional even just a few years ago. Today, however, use of the public cloud is completely mainstream - the norm, rather than the exception. Several leading technology firms, including Google, have built sophisticated cloud platforms, and are locked in a fierce competition for market share. The main goal of this book is to enable you to get the best out of the GCP, and to use it with confidence and competence. You will learn why cloud architectures take the forms that they do, and this will help you become a skilled high-level cloud architect. You will also learn how individual cloud services are configured and used, so that you are never intimidated at having to build it yourself. You will also learn the right way and the right situation in which to use the important GCP services. By the end of this book, you will be able to make the most out of Google Cloud Platform design.
Table of Contents (19 chapters)
13
Logging and Monitoring

Why load balancers matter now

Load balancers are discussed a lot more often these days than they used to be, say, a decade or two ago. They used to be somewhat arcane tools that only some network planners or architects really had to worry about during edge-case planning; now, they are absolutely mainstream, and even developers and app architects need to understand what kind of load balancer to choose, and why.

Why have load balancers become such a conversation starter these days? The answer lies in two important features of compute on the cloud—ephemeral external IP addresses and autoscaling of backends:

In the cloud world, load-balancer devices are an essential static entry point for apps. They have a static IP address that clients can be sure will remain unchanged, and accept incoming client requests and distribute them to a variable set of backend instances. The size...