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SIOS Awarded Two New Patents for Machine Learning Analytics for IT Operations

SIOS Technology has been granted two new patents from the United States Patent and Trademark Office, relating to technology advancements in developing machine learning-based IT analytics for finding and resolving application performance issues in computing infrastructures such as VMware.

U.S. Patent No. 9,772,871, titled “Apparatus and method for leveraging semi-supervised machine learning for self-adjusting policies in management of a computer infrastructure,” is the first of eight core innovations developed and implemented in SIOS iQ and covered by this patent. It validates the ability of SIOS iQ to perform unsupervised learning of an environment and its behaviors for use in IT operations for purposes such as automating performance root cause analysis, while permitting human input to be used to adjust its models.

U.S. Patent No. 9,910,707, titled “Interface for orchestration and analysis of a computer environment,” covers the Graphical User Interface (GUI) design in SIOS iQ. Specifically, the GUI is configured to provide a user with a single point of view into the computer infrastructure by converging application, compute, storage, and network behavioral attributes into higher order descriptive dimensions of IT operational quality covering performance, efficiency, reliability and capacity. With this configuration, the end user to can readily review the state of the computing environment in a single glance and efficiently explore and interact with the GUI to identify issues threatening operations and obtain recommended solutions.

Jerry Melnick, President and CEO, SIOS Technology, noted, “Virtual environments supporting applications have become enormously complex over the last 10 years. The skills and resources required to manage these infrastructures simply have not kept up, compromising IT’s ability to meet business needs. Companies will need to turn to analytics solutions driven by AI and machine learning out of necessity. These next generation tools help companies understand and prevent problems that threaten service delivery, and vastly simplify and optimize their operations.”

According to Sergey Razin, Ph.D, CTO, SIOS Technology, “We’re very proud of our industry-first innovations that combine the power of machine learning with a highly intuitive interface. For the first time, using SIOS’ patented data visualization and graphical interface, users can instantaneously identify and visually see the interactions of resources across compute, storage, network and applications that are impacting their operations.”

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SIOS Awarded Two New Patents for Machine Learning Analytics for IT Operations

SIOS Technology has been granted two new patents from the United States Patent and Trademark Office, relating to technology advancements in developing machine learning-based IT analytics for finding and resolving application performance issues in computing infrastructures such as VMware.

U.S. Patent No. 9,772,871, titled “Apparatus and method for leveraging semi-supervised machine learning for self-adjusting policies in management of a computer infrastructure,” is the first of eight core innovations developed and implemented in SIOS iQ and covered by this patent. It validates the ability of SIOS iQ to perform unsupervised learning of an environment and its behaviors for use in IT operations for purposes such as automating performance root cause analysis, while permitting human input to be used to adjust its models.

U.S. Patent No. 9,910,707, titled “Interface for orchestration and analysis of a computer environment,” covers the Graphical User Interface (GUI) design in SIOS iQ. Specifically, the GUI is configured to provide a user with a single point of view into the computer infrastructure by converging application, compute, storage, and network behavioral attributes into higher order descriptive dimensions of IT operational quality covering performance, efficiency, reliability and capacity. With this configuration, the end user to can readily review the state of the computing environment in a single glance and efficiently explore and interact with the GUI to identify issues threatening operations and obtain recommended solutions.

Jerry Melnick, President and CEO, SIOS Technology, noted, “Virtual environments supporting applications have become enormously complex over the last 10 years. The skills and resources required to manage these infrastructures simply have not kept up, compromising IT’s ability to meet business needs. Companies will need to turn to analytics solutions driven by AI and machine learning out of necessity. These next generation tools help companies understand and prevent problems that threaten service delivery, and vastly simplify and optimize their operations.”

According to Sergey Razin, Ph.D, CTO, SIOS Technology, “We’re very proud of our industry-first innovations that combine the power of machine learning with a highly intuitive interface. For the first time, using SIOS’ patented data visualization and graphical interface, users can instantaneously identify and visually see the interactions of resources across compute, storage, network and applications that are impacting their operations.”

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As businesses increasingly rely on high-performance applications to deliver seamless user experiences, the demand for fast, reliable, and scalable data storage systems has never been greater. Redis — an open-source, in-memory data structure store — has emerged as a popular choice for use cases ranging from caching to real-time analytics. But with great performance comes the need for vigilant monitoring ...

Kubernetes was not initially designed with AI's vast resource variability in mind, and the rapid rise of AI has exposed Kubernetes limitations, particularly when it comes to cost and resource efficiency. Indeed, AI workloads differ from traditional applications in that they require a staggering amount and variety of compute resources, and their consumption is far less consistent than traditional workloads ... Considering the speed of AI innovation, teams cannot afford to be bogged down by these constant infrastructure concerns. A solution is needed ...

AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...

Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...

A Gartner analyst recently suggested that GenAI tools could create 25% time savings for network operational teams. Where might these time savings come from? How are GenAI tools helping NetOps teams today, and what other tasks might they take on in the future as models continue improving? In general, these savings come from automating or streamlining manual NetOps tasks ...

IT and line-of-business teams are increasingly aligned in their efforts to close the data gap and drive greater collaboration to alleviate IT bottlenecks and offload growing demands on IT teams, according to The 2025 Automation Benchmark Report: Insights from IT Leaders on Enterprise Automation & the Future of AI-Driven Businesses from Jitterbit ...

A large majority (86%) of data management and AI decision makers cite protecting data privacy as a top concern, with 76% of respondents citing ROI on data privacy and AI initiatives across their organization, according to a new Harris Poll from Collibra ...

According to Gartner, Inc. the following six trends will shape the future of cloud over the next four years, ultimately resulting in new ways of working that are digital in nature and transformative in impact ...

2020 was the equivalent of a wedding with a top-shelf open bar. As businesses scrambled to adjust to remote work, digital transformation accelerated at breakneck speed. New software categories emerged overnight. Tech stacks ballooned with all sorts of SaaS apps solving ALL the problems — often with little oversight or long-term integration planning, and yes frequently a lot of duplicated functionality ... But now the music's faded. The lights are on. Everyone from the CIO to the CFO is checking the bill. Welcome to the Great SaaS Hangover ...

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