Every cloud provider makes it possible to create geographically distributed environments. I’m going to take a closer look at this using an example of Google Cloud Platform – GCP.
Why do we need geographically distributed environments? What motivates the creation geographically distributed environments? There are three main reasons.
High Availability
High availability suggests a system that is available most or all of the time. It avoids single points-of-failure and leads to redundancy of system components and risk diversification. Redundancy means that system components have backups, and it one instance fails another remains available. This is called “failover.” This simple method is used even in aerospace engineering.
Distributing infrastructure geographically allows us to avoid single point-of failure and mitigate risks related to the geographical location of a system and data.
Disaster Recovery
Disaster recovery, the set of procedures and tools used to recover infrastructure in the event of disaster, affects high availability. DR plans always includes RTO and RPO. RTO is a recovery time objective. This is time in which infrastructure can be completely restored following a disaster and function at full capacity. RTO affects high availability directly. If RTO is long – there’s no high availability. RPO is the recovery point objective, or maximum time in which data can be lost as a result of disaster. It doesn’t affect HA directly but is very important. Geographical distribution can be part of a disaster recovery plan. If we experience a natural disaster (e.g. earthquake) that impacts a system in one location, there will still be a system functioning in another location and we can failover to it.
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

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