Hyper-converged cloud infrastructures–the pinnacle of today’s cloud technology, approximates the current public cloud experience. Based on the premises-based private clouds, artificial intelligence (AI) has become essential to cloud computing and essential in optimizing the hyper-converged cloud infrastructures. As the solutions provided by hyper-converged platforms rises with each new generation of packaged hardware infrastructure, more enterprise customers are seeking AI-ready storage. Upon integrating AI tools for management of the infrastructure, AI workload can easily be optimized.
The packaged hardware components manage and optimize the AI workload in the hyper-converged infrastructure. Optimized chips running on the hyper-converged server platforms help optimize storage and configure hardware for application acceleration within the hyper-converged environments. 2018 will see a drastic increase in the use of solid state drive (SSD) – flash storage, to enhance efficiency, energy conservation and performance at a lower cost. Predictive storage analytics in best artificial intelligence platforms will gain significant traction in data centers due to its ability to simplify and automate complex operations.
Hyper-converged infrastructure is being pushed into secondary storage by many organizations for freeing up primary storage space and rendering the non-critical data more accessible. Flexible multi-cloud storage enables the efficient transfer of data across different cloud environments, be it a public cloud or private. Storage vendors will be using software-defined storage (SDS) and IoT computing to enhance the artificial intelligence capabilities on a hyper-converged cloud infrastructure. Also, with the changes in machine learning and cognitive behavior marking a massive shift in the market, artificial intelligence is gradually becoming the backbone for data management.
