SIOS iQ Uses Machine Learning Analytics To Identify Root Cause Of Datastore Latency Issue, Improve Efficiency Of VMware Environment
Leading Massachusetts based furniture retailer uses Machine Learning Analytics to improve their operations and decisions. Jordan’s Furniture has locations throughout New England. Their IT department continuously improves its infrastructure to keep its business operations running efficiently and cost-effectively.
The Jordan’s Furniture IT department needed an IT analytics solution that would provide a view across their infrastructure and enable them to find and resolve issues and inefficiencies quickly and easily.
They wanted an easy to-implement, cost-efficient solution that would allow them to be proactive – resolving issues before they become serious. Essentially, one place to look to check the state of their operations, identify wasted VM resources. They can get solutions to performance issues, and predict capacity utilization for accurate budgeting.
Jordan’s Furniture implemented SIOS iQ machine learning analytics tool simply by downloading an OVA file that installs a lightweight virtual machine. The patented machine learning technology in SIOS iQ immediately “learned” the behavior patterns of interrelated objects in their environment. It began analyzing normal versus anomalous behavior patterns. The tool automatically provided key insights and actionable recommendations for improvements.
The IT team used SIOS iQ machine learning analytics tool to make informed decision about whether to purchase storage acceleration hardware. SIOS iQ instantly determined whether an application performance issue could be improved by the use of storage acceleration such as host-based caching, allflash arrays, or hybrid storage. It recommended changes that addressed the root cause of the performance issue. This would result in higher performance gains without the need to purchase additional hardware. With SIOS iQ, Jordan’s Furniture was able to improve performance without wasting time and money.
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