Skip to main content

ScienceLogic Releases v7.2 of IT Operations and Cloud Management Platform

ScienceLogic released a new version of the company's IT operations and cloud management platform, ScienceLogic 7.2. With enhanced service management capabilities and support for HTML5, the product makes it easier for customers to view and manage their IT services across data center and cloud environments as well as introduce new business services.

The ScienceLogic platform’s IT service management (ITSM) features enable service providers and corporations to monitor and manage any combination of IT resources as an overall service. The product now provides access to unlimited services metrics, expanding the ability to discover, classify, monitor, and manage an IT service across on-premises and cloud-based resources, with views into health, availability and risk. The benefit is an instant high-level view across diverse services while supporting simple drill-down for comprehensive service diagnostics.

ScienceLogic has also added a powerful rules engine for service membership. The service can be defined once via an easy-to-use graphical user interface and will automatically adjust as components move across modern, dynamically provisioned data centers and cloud infrastructures. ScienceLogic delivers ITSM capabilities from one pre-integrated management platform with one code base, one user interface, and one centralized management database, preventing the need to purchase and integrate a variety of products together from one or more vendors just to get a service-oriented view.

In addition, the ScienceLogic platform's 100 percent Web-based user interface now supports HTML5, so that IT operations and service management data can be consumed anywhere, at any time, using any tablet or mobile device. ScienceLogic provides pre-built dashboards, and clients can customize their own by simply dragging and dropping widgets onto a page. The dashboards and widgets are contextual, meaning individual elements can be selected to expand on the metrics and data needed, and to change “context” to see information consistently across multiple clouds, for example.

An executive can view a dashboard on an iPad, for instance, to get an at-a-glance status of the real time and past availability and performance of a critical application such as Exchange, as well as determine the risk of performance deterioration based on current factors. Service providers can easily create NOC dashboards for their IT operations as well as customers to view service-level compliance and ascertain the risk of breaching client SLAs.

“The ScienceLogic management platform is so versatile that our customers use it in many ways to manage and grow their businesses,” said Richard Chart, executive vice president of product management for ScienceLogic. “Enhancing our service management capabilities and adding support for HTML5 are two more ways we make it easy for customers to manage service delivery the way they want to, improve IT operations efficiency, and increase the value of their services.”

ScienceLogic charges per device, with a perpetual license fee of $150 per device and a one year subscription license costing $10 per device per month.

The Latest

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.

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...

ScienceLogic Releases v7.2 of IT Operations and Cloud Management Platform

ScienceLogic released a new version of the company's IT operations and cloud management platform, ScienceLogic 7.2. With enhanced service management capabilities and support for HTML5, the product makes it easier for customers to view and manage their IT services across data center and cloud environments as well as introduce new business services.

The ScienceLogic platform’s IT service management (ITSM) features enable service providers and corporations to monitor and manage any combination of IT resources as an overall service. The product now provides access to unlimited services metrics, expanding the ability to discover, classify, monitor, and manage an IT service across on-premises and cloud-based resources, with views into health, availability and risk. The benefit is an instant high-level view across diverse services while supporting simple drill-down for comprehensive service diagnostics.

ScienceLogic has also added a powerful rules engine for service membership. The service can be defined once via an easy-to-use graphical user interface and will automatically adjust as components move across modern, dynamically provisioned data centers and cloud infrastructures. ScienceLogic delivers ITSM capabilities from one pre-integrated management platform with one code base, one user interface, and one centralized management database, preventing the need to purchase and integrate a variety of products together from one or more vendors just to get a service-oriented view.

In addition, the ScienceLogic platform's 100 percent Web-based user interface now supports HTML5, so that IT operations and service management data can be consumed anywhere, at any time, using any tablet or mobile device. ScienceLogic provides pre-built dashboards, and clients can customize their own by simply dragging and dropping widgets onto a page. The dashboards and widgets are contextual, meaning individual elements can be selected to expand on the metrics and data needed, and to change “context” to see information consistently across multiple clouds, for example.

An executive can view a dashboard on an iPad, for instance, to get an at-a-glance status of the real time and past availability and performance of a critical application such as Exchange, as well as determine the risk of performance deterioration based on current factors. Service providers can easily create NOC dashboards for their IT operations as well as customers to view service-level compliance and ascertain the risk of breaching client SLAs.

“The ScienceLogic management platform is so versatile that our customers use it in many ways to manage and grow their businesses,” said Richard Chart, executive vice president of product management for ScienceLogic. “Enhancing our service management capabilities and adding support for HTML5 are two more ways we make it easy for customers to manage service delivery the way they want to, improve IT operations efficiency, and increase the value of their services.”

ScienceLogic charges per device, with a perpetual license fee of $150 per device and a one year subscription license costing $10 per device per month.

The Latest

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.

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...