Designing Geographically Distributed Environments with the Google Cloud Platform

In Compare the Cloud, Pavel Khrulev, Solutions Architect at DataArt, explores how geographically distributed environments can improve availability, disaster recovery, and performance of systems and provides an overview of several Google Cloud Platform’s cloud components.

«Any application must transfer data from the user to an app and back, and probably between application components. In the era of high-speed Internet and networks, it’s usually not a problem. But what if your data center is in California and you many users who transfer significant amounts of data from Russia and get huge amounts in return. This could be an issue because of network overhead. Transferring data could take too long. leading to performance that doesn’t satisfy system requirements. In that case, geographic distribution is beneficial. Moving datacenter/application components closer to the user’s location makes it possible to decrease network overhead and improve performance.»

«Going global with GCP is much easier because most of its services are global by nature. GCP makes it possible to be more efficient in aspects such as cost, automation, infrastructure design and performance. In my opinion, one of the most important skills in engineering (and software engineering isn’t an exclusion) – is the ability to select the proper tool for a specific task. If you’re building a of global, geographically distributed environment GCP is an excellent choice.»

«Currently, google infrastructure extends to 23 regions, 70 availability zones and 140 network edge locations. Let’s take a look at these regions, zones and edge locations.»

Original article can be found here.

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