Why IT Needs Help from Machine Learning
The volume/scope of data that businesses produce and IT pros have to manage has grown rapidly. Managing this onslaught of data can hinder IT productivity, especially when they are hampered by traditional tools and old school approaches. The exponential growth of virtual IT infrastructures in both scale and complexity is pushing IT teams to their limits. However, IT teams are still looking at their virtual infrastructures in individual operational silos – compute, application, storage, and network.
They are using multiple tools to gather information about each silo and then piecing the results together manually. They rely on their own experience to develop a theory about the root cause of performance issues and to devise a strategy for resolution. This inaccurate approach is leaving IT time strapped, stressed out and without clear answers to key questions about application performance issues in virtualized environments, including how to fix them. More and more companies are looking to machine learning based solutions for the answer.
Given the enormous growth of virtualized systems, IT pros can no longer make informed decisions by analyzing alerts from traditional threshold-based analytics and monitoring tools. Similar to the manufacturing revolution of the past, IT pros now need help from machines to be effective in today’s data-driven world. They need a solution capable of simultaneously considering data from across the IT infrastructure silos and applications. A solution that understands the subtle ways that components in virtual environments interact with one another and the changing patterns of their behavior over time. Most importantly, IT pros need advanced machine learning and deep learning tools that do this work for them.
Read the entire article here, Why IT Needs Help from Machine Learning
via the fine folks at SIOS.