Hyper Converged Infrastructure | @CloudExpo #BigData #IoT #API #DevOps

At the outset, Hyper convergence looks to be an attractive option seemingly providing lot of flexibility. In reality, it comes with so many limitation and curtail the flexibility to grow the hardware resources such as server, storage, etc independent of each other. In addition, performance nightmare bound to hit once the system gets loaded. In late 1990s, storage and networking came out of compute for a reason. Both networking and storage need some specialized processing and it doesn't make sense for all the general purpose servers doing this job. It is better handled by the specialized group of dedicated devices. The critical element in the complete data center infrastructure is data. It may be better to keep this data in the special devices with the required level of redundancy than spreading across the entire data centers. However, hyper convergence emerged for a noble cause of ease deployment for a very small scale branch office scenarios since it is always complex to setup and operate traditional SAN. The real problem starts when we attempt to replicate this layout into large scale environment with the transactional workload. Three predominant issues can hit the hyper converged deployments hard and it can spell a death trap. While sophisticated IT houses know these problems and stay away from the hyper convergence, but others can fall prey to this hype cycle.

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