Grid Architecture

Published: April 2017
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“Grid architecture” allows building a highly redundant and high-performing cluster by connecting the nodes together into a single resilient grid while maintaining the principle of data locality. Such architecture allows the cluster to stay operational even after multiple node failures.

This document discusses the benefits of using grid architecture to maintain data locality and provide higher performance and resiliency.

Common N+1 or N+2 cluster configurations do not provide sufficient redundancy level for certain workloads. While fitting some data processing application, the resilience provided by such configuration will not be enough for many independent workloads like VDI.

It is difficult to maintain both “data locality” and flexible scaling options. Without the data locality, performance in the cluster will decrease, since dividing compute and storage resources of a single process will transfer much of the data through fabrics. On the other hand, without flexible scaling, the cluster loses one of its main benefits, thus requiring higher expenses to grow resources.

The so-called “grid architecture” allows the cluster to maintain a high rate of fault tolerance while maintaining the principle of “data locality” and stay operational even if multiple nodes will go down. This cluster topology resembles a grid, where several take nodes create a cluster of their own. These “clusters” deliver a much higher rate of system resiliency comparing to typical N+1 or N+2 systems, where each component has one or two backup partners. Such systems will fail when losing roughly 1/3 of nodes. In the case with VDI, it is much better to have the remaining cluster nodes working, than have it all go down.

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