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Evolven Granted US Patent for Automated Dependency Mapping

Evolven Software announced that the United States Patent and Trademark Office has granted it a new patent encompassing a unique approach to IT environment dependency mapping.

Evolven's Change Analytics technology enables IT professionals to track actual changes in on-premises and cloud IT environments. The system automatically analyzes risk of detected granular changes carried out in the end-to-end environment, correlating investigated performance and stability issues to changes causing them, and proactively identifying changes that could cause future issues.

One key aspect of effectively and efficiently resolving IT issues is a detailed understanding of the IT system and of its environment in general. Multi-tiered enterprise systems typically include a plethora of heterogeneous components located at various layers of the information technology stack and possibly spread over multiple areas of the IT environment. Since these components typically depend on one another, a change in one component could affect the behavior of another component or even cause it to cease functioning completely.

These dependencies might contain cross-product and cross-host dependencies, they require in-depth expert knowledge to be identified manually, and they also frequently change over time. Thus keeping track of them can be a challenge.

Evolven's newly patented technology enables automated dependency discovery. In effect, it builds an IT component dependency graph by looking for references between components while crawling their configuration data at a granular level.

Most vendors in the industry either employ indirect methods based on analysis of network activity and load processing or intrusive methods based on fault injections and perturbations. These methods, however, have several drawbacks.

In contrast, Evolven's newly patent technology employs a different approach — one based on 'reading' actual specified configurations.

"Being able to automatically and accurately map dependencies between environment components is critical to not only enhance root cause analysis but to prevent incidents from happening in the first place," stated Sasha Gilenson, Evolven CEO. "As enterprise applications typically include numerous components at various layers and spread over multiple areas of IT environments, and as these components commonly depend on each other, a deep understanding of the dependencies in IT environment is essential."

Evolven Software has been granted U.S. Patent No. US20190081861A1.

This patented technology accomplishes the following:

- Accelerates root-cause analysis and so shortens time spent troubleshooting

- Prevents performance and stability incidents

- Allows companies to avoid compliance and security issues by automatically detecting unauthorized and undesired changes

"By leveraging Evolven's exclusive machine learning capabilities, enterprises can make important correlations across silos, recognize patterns, automatically identify anomalies, detect unauthorized changes, and apply efficient troubleshooting by intelligent root-cause analysis," said Boštjan Kaluža, Chief Data Scientist at Evolven. "With Evolven's AIOps capabilities, IT professionals can generate actionable insights from huge amounts of operations data, thereby minimizing the time needed to find and diagnose stability issues, preventing outages and downtimes, and enhancing IT support around critical business services."

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Evolven Granted US Patent for Automated Dependency Mapping

Evolven Software announced that the United States Patent and Trademark Office has granted it a new patent encompassing a unique approach to IT environment dependency mapping.

Evolven's Change Analytics technology enables IT professionals to track actual changes in on-premises and cloud IT environments. The system automatically analyzes risk of detected granular changes carried out in the end-to-end environment, correlating investigated performance and stability issues to changes causing them, and proactively identifying changes that could cause future issues.

One key aspect of effectively and efficiently resolving IT issues is a detailed understanding of the IT system and of its environment in general. Multi-tiered enterprise systems typically include a plethora of heterogeneous components located at various layers of the information technology stack and possibly spread over multiple areas of the IT environment. Since these components typically depend on one another, a change in one component could affect the behavior of another component or even cause it to cease functioning completely.

These dependencies might contain cross-product and cross-host dependencies, they require in-depth expert knowledge to be identified manually, and they also frequently change over time. Thus keeping track of them can be a challenge.

Evolven's newly patented technology enables automated dependency discovery. In effect, it builds an IT component dependency graph by looking for references between components while crawling their configuration data at a granular level.

Most vendors in the industry either employ indirect methods based on analysis of network activity and load processing or intrusive methods based on fault injections and perturbations. These methods, however, have several drawbacks.

In contrast, Evolven's newly patent technology employs a different approach — one based on 'reading' actual specified configurations.

"Being able to automatically and accurately map dependencies between environment components is critical to not only enhance root cause analysis but to prevent incidents from happening in the first place," stated Sasha Gilenson, Evolven CEO. "As enterprise applications typically include numerous components at various layers and spread over multiple areas of IT environments, and as these components commonly depend on each other, a deep understanding of the dependencies in IT environment is essential."

Evolven Software has been granted U.S. Patent No. US20190081861A1.

This patented technology accomplishes the following:

- Accelerates root-cause analysis and so shortens time spent troubleshooting

- Prevents performance and stability incidents

- Allows companies to avoid compliance and security issues by automatically detecting unauthorized and undesired changes

"By leveraging Evolven's exclusive machine learning capabilities, enterprises can make important correlations across silos, recognize patterns, automatically identify anomalies, detect unauthorized changes, and apply efficient troubleshooting by intelligent root-cause analysis," said Boštjan Kaluža, Chief Data Scientist at Evolven. "With Evolven's AIOps capabilities, IT professionals can generate actionable insights from huge amounts of operations data, thereby minimizing the time needed to find and diagnose stability issues, preventing outages and downtimes, and enhancing IT support around critical business services."

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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 ...