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Heroix Introduces Longitude for Large Scale IT Monitoring

Heroix introduced Heroix Longitude for very large-scale IT systems monitoring.

The new release of the software also offers greater reporting capabilities for VMware, providing users important information on a broader range of critical metrics.

Companies that must monitor thousands of servers, network devices and the associated applications can easily leverage Longitude because of its enhanced efficiency and noticeable speed. The lightning fast performance is evident even in the largest data centers. Organizations with significant IT resources can rely on Longitude to scale up to monitor large enterprise environments.

"As the amount of data and the need to manage it mushrooms, enterprises must add more IT resources," noted Dick Levin, VP of Development, Heroix. "Larger data centers and more IT infrastructure create complex challenges. IT monitoring software must detect degraded performance issues very rapidly in order to keep resources available and meet SLA requirements."

By 2020, IDC predicts that the digital universe will "grow by a factor of 300..."

IDC expects it to reach "40 trillion gigabytes..."

Heroix has made it possible for Longitude users to cope with this surge in data by adding significant speed and overall performance improvements to the interface.

Heroix has also added new reporting and other capabilities to the Longitude VMware Edition:

- VMware knowledge base

- historical performance reports

- zombie VM reports

- additional performance metrics

The VMware knowledge base is a result of Heroix's special expertise with VMware software and years of supporting monitoring capabilities specifically for it.

Comprehensive reporting capabilities create a holistic picture of an enterprise's IT systems, enabling IT to better reduce downtime, meet SLA commitments and save money. For example, comparing historical performance metrics with current conditions, administrators can identify and solve existing issues faster.

Longitude VMware Edition's new summary reports allow users to quickly identify resource depletion issues that span across multiple vCenter instances and their accompanying hosts and VMs, showing CPU, memory, disk, network, file, datastore usage, cluster CPU and memory problems. The additional Zombie reports list VMs whose resource usage (CPU, memory and IO rate) are less than a user configurable threshold. This helps companies reclaim and reuse underutilized resources faster and in a more effective way.

In addition to Longitude's VMware monitoring capabilities, Longitude also monitors and reports on applications, systems and networks, providing detailed insight into overall IT performance. Longitude is already known for its power, ease-of-use and affordability, and Longitude 8.2 provides significant increases in speed and efficiency.

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 ...

Heroix Introduces Longitude for Large Scale IT Monitoring

Heroix introduced Heroix Longitude for very large-scale IT systems monitoring.

The new release of the software also offers greater reporting capabilities for VMware, providing users important information on a broader range of critical metrics.

Companies that must monitor thousands of servers, network devices and the associated applications can easily leverage Longitude because of its enhanced efficiency and noticeable speed. The lightning fast performance is evident even in the largest data centers. Organizations with significant IT resources can rely on Longitude to scale up to monitor large enterprise environments.

"As the amount of data and the need to manage it mushrooms, enterprises must add more IT resources," noted Dick Levin, VP of Development, Heroix. "Larger data centers and more IT infrastructure create complex challenges. IT monitoring software must detect degraded performance issues very rapidly in order to keep resources available and meet SLA requirements."

By 2020, IDC predicts that the digital universe will "grow by a factor of 300..."

IDC expects it to reach "40 trillion gigabytes..."

Heroix has made it possible for Longitude users to cope with this surge in data by adding significant speed and overall performance improvements to the interface.

Heroix has also added new reporting and other capabilities to the Longitude VMware Edition:

- VMware knowledge base

- historical performance reports

- zombie VM reports

- additional performance metrics

The VMware knowledge base is a result of Heroix's special expertise with VMware software and years of supporting monitoring capabilities specifically for it.

Comprehensive reporting capabilities create a holistic picture of an enterprise's IT systems, enabling IT to better reduce downtime, meet SLA commitments and save money. For example, comparing historical performance metrics with current conditions, administrators can identify and solve existing issues faster.

Longitude VMware Edition's new summary reports allow users to quickly identify resource depletion issues that span across multiple vCenter instances and their accompanying hosts and VMs, showing CPU, memory, disk, network, file, datastore usage, cluster CPU and memory problems. The additional Zombie reports list VMs whose resource usage (CPU, memory and IO rate) are less than a user configurable threshold. This helps companies reclaim and reuse underutilized resources faster and in a more effective way.

In addition to Longitude's VMware monitoring capabilities, Longitude also monitors and reports on applications, systems and networks, providing detailed insight into overall IT performance. Longitude is already known for its power, ease-of-use and affordability, and Longitude 8.2 provides significant increases in speed and efficiency.

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 ...