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In order to increase the resiliency and redundancy of a distributed system, it is common to keep standby systems and backups of data in different locations than the primary site, separated by a meaningful distance in order to tolerate local outages. Nasdaq has accomplished this by maintaining primary-standby pairs or primary-standby-disaster triplets with at least one system residing in a different site. The team at Nasdaq is experimenting with a redundant deployment scheme in Kubernetes with three availability zones, located within a single geographical region, in Amazon Web Services. They want to move the disaster zone to another geographical region in order to improve the redundancy and resiliency of the system. The aim of this thesis is to investigate how this could be done and to compare the different approaches.

To compare the different approaches, a simple observable model of the chain replicating strategy is implemented. The model is deployed in an Elastic Kubernetes Cluster on Amazon Web Services, using Helm. The supporting infrastructure is defined and created using Terraform. This model is subjected to evaluation through HTTP requests with different configurations and scenarios, to measure latency and throughput. The first scenario is a single user making HTTP requests to the system, and the second scenario is multiple users making requests to the system.

The results show that the throughput is lower and the latency is higher with the multi-region approach. The relative difference in median throughput is -54.41% and the relative difference in median latency is 119.20%, in the single-producer case. In the multi-producer case, both the relative difference in median throughput and latency is reduced when increasing the amount of partitions in the system.