Skip to main content

SIOS Technology Announces Newest Release of SIOS iQ Machine Learning Analytics

SIOS Technology announced the latest release of SIOS iQ machine learning analytics software, which has new features that deliver accuracy and precision in performance root cause analysis for VMware environments.

It also includes dashboard enhancements for improved usability and a graphical topological impact view enabling faster identification and resolution of issues.

“SIOS iQ meets a growing need for accurate, real-time insight into application and server performance, efficiency, and reliability in VMware environments,” said Jason Bloomberg, President, Intellyx. “The SIOS PERC Dashboard and SIOS iQ’s graphical topological impact view and search features cut through the vast volumes of data ‘noise’ these complex environments generate, identifying critical issues and their root causes across the entire virtual infrastructure.”

“By putting all key information about an organization’s infrastructure at their fingertips, SIOS iQ enables IT managers to ensure their applications are operating efficiently, that issues are identified and resolved quickly, and that VMware resources are not being wasted,” said Jerry Melnick, President and CEO, SIOS Technology. “These newest enhancements further simplify the understanding of IT operations and help resolve issues in dynamic virtual environments.”

Designed to be a powerful platform for IT operations information and issue resolution, SIOS iQ applies an advanced data analytics/Big Data approach to a broad range of data sets, including application and infrastructure data from third party tools and frameworks, to recognize abnormal patterns of behavior and identify root causes of performance issues. The latest innovations from SIOS deliver industry leading precision and accuracy in identifying and resolving root causes of performance issues.

SIOS iQ features are released on an ongoing basis. New releases in Q4 2015 include: Version 3.2 released in October featuring support for VMware vSphere 6.0, search functionality, and enhancements to performance root cause analysis.

Version 3.3 is immediately available and includes:

- Immediate Time to Value with Best Practices Analysis – New best practices analysis feature enables SIOS iQ to provide insights on performance, efficiency, reliability, and capacity utilization immediately after implementation, accelerating its automated process of learning and characterizing behavior of interrelated objects in the infrastructure.

- VMware vRealize Operations Manager 6.0 (vROps) Event Injection –SIOS iQ enables vROps to display: high availability cluster health; host-based caching configuration recommendations; undersized VMs; and idle resources including snapshot and VM sprawl through its Environment Health map and issue display. With SIOS iQ, vROps users gain precise identification of performance issues, such as “noisy neighbors”, hardware degradation, and slow application performance with specific recommendations for remediation.

- Enhanced Performance Issue Event Correlation – SIOS iQ can now identify additional root causes of performance issues, including network anomalies (released in v3.2), newly provisioned VM(s), Live Migration of VMs, and under-sized VMs.

The next release of SIOS iQ, version 3.4, will be available by the end of the year and will include:

- Topology Impact Analysis View – SIOS iQ provides a dynamic, visual map of the VMware infrastructure showing interrelated objects (VMs, network, storage, and applications) and their interrelationships highlighting current status and highlighting anomalous behavior. Touch-enabled drill down screens enable IT to explore detailed root causes of performance issues and recommendations for improvement.

- Semi-Supervised Learning – IT staff can augment SIOS iQ’s understanding of both normal and anomalous infrastructure behavior by adding individualized parameters for increased precision and accuracy.

- Reliability Analysis for VMware HA – SIOS iQ enables users to ensure their VMware infrastructure is protected in the event of host failures. The SIOS PERC Dashboard™ reliability indicator shows the number of host failures that a cluster has sustained over time and indicates when there are not enough hosts to sustain future failures.

SIOS iQ version 3.3 is immediately available. SIOS iQ version 3.4 will be available by the end of the year.

The Latest

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

SIOS Technology Announces Newest Release of SIOS iQ Machine Learning Analytics

SIOS Technology announced the latest release of SIOS iQ machine learning analytics software, which has new features that deliver accuracy and precision in performance root cause analysis for VMware environments.

It also includes dashboard enhancements for improved usability and a graphical topological impact view enabling faster identification and resolution of issues.

“SIOS iQ meets a growing need for accurate, real-time insight into application and server performance, efficiency, and reliability in VMware environments,” said Jason Bloomberg, President, Intellyx. “The SIOS PERC Dashboard and SIOS iQ’s graphical topological impact view and search features cut through the vast volumes of data ‘noise’ these complex environments generate, identifying critical issues and their root causes across the entire virtual infrastructure.”

“By putting all key information about an organization’s infrastructure at their fingertips, SIOS iQ enables IT managers to ensure their applications are operating efficiently, that issues are identified and resolved quickly, and that VMware resources are not being wasted,” said Jerry Melnick, President and CEO, SIOS Technology. “These newest enhancements further simplify the understanding of IT operations and help resolve issues in dynamic virtual environments.”

Designed to be a powerful platform for IT operations information and issue resolution, SIOS iQ applies an advanced data analytics/Big Data approach to a broad range of data sets, including application and infrastructure data from third party tools and frameworks, to recognize abnormal patterns of behavior and identify root causes of performance issues. The latest innovations from SIOS deliver industry leading precision and accuracy in identifying and resolving root causes of performance issues.

SIOS iQ features are released on an ongoing basis. New releases in Q4 2015 include: Version 3.2 released in October featuring support for VMware vSphere 6.0, search functionality, and enhancements to performance root cause analysis.

Version 3.3 is immediately available and includes:

- Immediate Time to Value with Best Practices Analysis – New best practices analysis feature enables SIOS iQ to provide insights on performance, efficiency, reliability, and capacity utilization immediately after implementation, accelerating its automated process of learning and characterizing behavior of interrelated objects in the infrastructure.

- VMware vRealize Operations Manager 6.0 (vROps) Event Injection –SIOS iQ enables vROps to display: high availability cluster health; host-based caching configuration recommendations; undersized VMs; and idle resources including snapshot and VM sprawl through its Environment Health map and issue display. With SIOS iQ, vROps users gain precise identification of performance issues, such as “noisy neighbors”, hardware degradation, and slow application performance with specific recommendations for remediation.

- Enhanced Performance Issue Event Correlation – SIOS iQ can now identify additional root causes of performance issues, including network anomalies (released in v3.2), newly provisioned VM(s), Live Migration of VMs, and under-sized VMs.

The next release of SIOS iQ, version 3.4, will be available by the end of the year and will include:

- Topology Impact Analysis View – SIOS iQ provides a dynamic, visual map of the VMware infrastructure showing interrelated objects (VMs, network, storage, and applications) and their interrelationships highlighting current status and highlighting anomalous behavior. Touch-enabled drill down screens enable IT to explore detailed root causes of performance issues and recommendations for improvement.

- Semi-Supervised Learning – IT staff can augment SIOS iQ’s understanding of both normal and anomalous infrastructure behavior by adding individualized parameters for increased precision and accuracy.

- Reliability Analysis for VMware HA – SIOS iQ enables users to ensure their VMware infrastructure is protected in the event of host failures. The SIOS PERC Dashboard™ reliability indicator shows the number of host failures that a cluster has sustained over time and indicates when there are not enough hosts to sustain future failures.

SIOS iQ version 3.3 is immediately available. SIOS iQ version 3.4 will be available by the end of the year.

The Latest

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.