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Google Cloud Platform for Architects

Google Cloud Platform for Architects

By : Vitthal Srinivasan, Loonycorn Ravi, Judy Raj
3.1 (12)
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Google Cloud Platform for Architects

Google Cloud Platform for Architects

3.1 (12)
By: Vitthal Srinivasan, Loonycorn Ravi, 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)
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13
Logging and Monitoring

Summary

In this chapter, we have seen that Google Compute Engine falls under the umbrella of IaaS, and have learned how that compares with PaaS and SaaS. The provisioning and configuration of VM instances, including the use of startup scripts, as well as machine types and their effect on costs should now be clear. Some of the additional features linked to VM instances such as load balancing and autoscaling have also been discussed. And finally, we have covered the forms of storage that can be attached to a VM, such as persistent disks and local SSDs, while also touching upon snapshots and images.

Now that we have looked at Google's IaaS offering with Compute Engine, we can now move toward the PaaS options by examining Google Kubernetes Engine (GKE) and App Engine (AE).

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