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An Interview with Neebula Co-Founder - Part Two

Pete Goldin
APMdigest

In Part Two of BSMdigest’s exclusive interview, Ariel Gordon, Neebula VP of Products and Co-Founder, talks about his new company and the role of BSM in today's dynamic IT environment.

BSM: What are the inherent IT management challenges introduced by cloud environments?

This is a question that deserves its own separate set of articles. There are so many challenges: which type of cloud suits your needs, how do you manage it, how do you manage the quality of services on top of it, how do you change your internal IT structure to support this environment? But if you have moved to a private IaaS cloud, the major challenge is how to manage the business services on top of it so that their performance and quality are not impacted. Most of today’s cloud management solutions are able to manage the infrastructure at an application component level and are not aware of the business service concept. And so managing and understanding all the components that need to support a service in this environment is a challenge which I have seen customers struggle to resolve on their own. Products like Neebula were built with this problem in mind.

BSM: What is required for a BSM tool to manage the cloud?

For a BSM tool to work in a cloud environment, it must have what I call a “Real Time Service Model”, as it must understand at any given moment the components of a service, their location and issues that are impacting them. This includes all the components of a service, the applications, storage, servers, and even the network. Then the BSM tool must be able to report on the status of the service and must be able to ask the cloud infrastructure to remediate issues that are impacting the service. The issue is that most of today’s BSM tools are unable to keep such a map up to date in real time and so are not fit for such environments.

BSM: Do virtual environments present the same challenges as cloud?

Virtual environments are not the same as cloud. One can move a physical server to a virtual server and then this server can live on the same hypervisor for many years without being moved. This is not a paradigm change from the BSM management tool's perspective. All you have done is consolidated your environment but things are still static. You still need to manage your consolidation correctly so that you do not have too many resource hungry VMs on the same hypervisor. The major issue there is to watch VM performance and move them to a stronger platform if needed, much like you would have done in the past, just that the move is easier. The issue is that virtualization also makes it easy to move and create new servers. And so very rapidly you start activating DRS and moving down the path towards an internal cloud.

BSM: What was the initial driver behind Neebula? What were you trying to accomplish?

There were two major issues that drove us to start Neebula. The first was the introduction of virtualization and cloud computing, and the issues they would bring to existing BSM customers. Managing business services is still a must in these new environments and there is a need for a tool that is able to extend the capabilities of the existing BSM tool for this environment. The major issue is Real Time Service Modeling. At Neebula, we set about to resolve it, and when doing so we also resolved a second issue, which was the cost of building and maintaining the service model in a “static” data center.

BSM implementations today are actually a journey. IT organizations are always in the process of implementation and improvements but do not fully achieve their goals. Neebula was built to help them get there much faster.

BSM: You refer to Neebula as “Adaptive BSM”. What does this term mean?

Adaptive BSM means that your BSM solution will automatically adapt to changes in the environment, the applications, and all the components that support a business service. So when a server has moved, you know it happened in real time. And when a new flow is put into WebSphere Message Broker that is now accessing a new component, you know about it without a need for manual intervention.

In a survey we did in 30 organizations that implemented BSM, 61% of them admitted that the service models they have are less than 75% accurate. Adaptive BSM comes to resolve that issue and get them closer to 100%.

BSM: How can models mapping business services to related applications, servers, network and storage devices be kept automatically up to date in a virtualized environment?

The idea is simple. The tool needs to separate the logical model of the service that contains the applicative structure of the business service and the physical model that contains all the components that support a service. The trick is then how – in real time – to discover and bind the physical model to the logical model in an economical way, in order to have the full service model. Neebula has patent pending technology to do just that.

The second issue is that even logical models are dynamic. Although this is an application change, this happens also more rapidly than you would want. In the same survey, 57% said that they have more than one change a week in their environment that would influence a service model. And so a way to keep the logical model up to date automatically is also needed as well – and this is exactly what Neebula can do.

BSM: Where does BSM need to go from here?

To succeed in the new environments, BSM tools have to be more adaptive. They must be able to understand how the new environment supports all the components of a service. This means that we are going to see much more real-time mapping capabilities. In addition, we are going to see BSM tools morph and integrate to the cloud management tools to enable better support for business services on the cloud. The support for cloud will extend hybrid cloud implementations e.g. support of services that span static IT, private clouds, and public clouds in all its different variants.

Click here to read Part One of the BSMdigest interview with Ariel Gordon, VP of Products and Co-Founder of Neebula.

About Ariel Gordon

Ariel Gordon, VP of Products and Co-Founder of Neebula, is a well known expert in the industry, with more than 20 years of experience in systems management. Prior to co-founding Neebula, Ariel was Chief Technology Officer at BMC Software. At BMC, Ariel was one of the creators of BMC's Business Service Management (BSM) strategy and pioneered the creation BMC's BSM Atrium integration infrastructure. Ariel joined BMC through the acquisition of New Dimension Software, where he served as VP of R&D and CTO. Ariel was a driving force behind New Dimension's successful CONTROL product line which included CONTROL-M, one of the leading scheduling products in the market.

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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 ...

The gap is widening between what teams spend on observability tools and the value they receive amid surging data volumes and budget pressures, according to The Breaking Point for Observability Leaders, a report from Imply ...

An Interview with Neebula Co-Founder - Part Two

Pete Goldin
APMdigest

In Part Two of BSMdigest’s exclusive interview, Ariel Gordon, Neebula VP of Products and Co-Founder, talks about his new company and the role of BSM in today's dynamic IT environment.

BSM: What are the inherent IT management challenges introduced by cloud environments?

This is a question that deserves its own separate set of articles. There are so many challenges: which type of cloud suits your needs, how do you manage it, how do you manage the quality of services on top of it, how do you change your internal IT structure to support this environment? But if you have moved to a private IaaS cloud, the major challenge is how to manage the business services on top of it so that their performance and quality are not impacted. Most of today’s cloud management solutions are able to manage the infrastructure at an application component level and are not aware of the business service concept. And so managing and understanding all the components that need to support a service in this environment is a challenge which I have seen customers struggle to resolve on their own. Products like Neebula were built with this problem in mind.

BSM: What is required for a BSM tool to manage the cloud?

For a BSM tool to work in a cloud environment, it must have what I call a “Real Time Service Model”, as it must understand at any given moment the components of a service, their location and issues that are impacting them. This includes all the components of a service, the applications, storage, servers, and even the network. Then the BSM tool must be able to report on the status of the service and must be able to ask the cloud infrastructure to remediate issues that are impacting the service. The issue is that most of today’s BSM tools are unable to keep such a map up to date in real time and so are not fit for such environments.

BSM: Do virtual environments present the same challenges as cloud?

Virtual environments are not the same as cloud. One can move a physical server to a virtual server and then this server can live on the same hypervisor for many years without being moved. This is not a paradigm change from the BSM management tool's perspective. All you have done is consolidated your environment but things are still static. You still need to manage your consolidation correctly so that you do not have too many resource hungry VMs on the same hypervisor. The major issue there is to watch VM performance and move them to a stronger platform if needed, much like you would have done in the past, just that the move is easier. The issue is that virtualization also makes it easy to move and create new servers. And so very rapidly you start activating DRS and moving down the path towards an internal cloud.

BSM: What was the initial driver behind Neebula? What were you trying to accomplish?

There were two major issues that drove us to start Neebula. The first was the introduction of virtualization and cloud computing, and the issues they would bring to existing BSM customers. Managing business services is still a must in these new environments and there is a need for a tool that is able to extend the capabilities of the existing BSM tool for this environment. The major issue is Real Time Service Modeling. At Neebula, we set about to resolve it, and when doing so we also resolved a second issue, which was the cost of building and maintaining the service model in a “static” data center.

BSM implementations today are actually a journey. IT organizations are always in the process of implementation and improvements but do not fully achieve their goals. Neebula was built to help them get there much faster.

BSM: You refer to Neebula as “Adaptive BSM”. What does this term mean?

Adaptive BSM means that your BSM solution will automatically adapt to changes in the environment, the applications, and all the components that support a business service. So when a server has moved, you know it happened in real time. And when a new flow is put into WebSphere Message Broker that is now accessing a new component, you know about it without a need for manual intervention.

In a survey we did in 30 organizations that implemented BSM, 61% of them admitted that the service models they have are less than 75% accurate. Adaptive BSM comes to resolve that issue and get them closer to 100%.

BSM: How can models mapping business services to related applications, servers, network and storage devices be kept automatically up to date in a virtualized environment?

The idea is simple. The tool needs to separate the logical model of the service that contains the applicative structure of the business service and the physical model that contains all the components that support a service. The trick is then how – in real time – to discover and bind the physical model to the logical model in an economical way, in order to have the full service model. Neebula has patent pending technology to do just that.

The second issue is that even logical models are dynamic. Although this is an application change, this happens also more rapidly than you would want. In the same survey, 57% said that they have more than one change a week in their environment that would influence a service model. And so a way to keep the logical model up to date automatically is also needed as well – and this is exactly what Neebula can do.

BSM: Where does BSM need to go from here?

To succeed in the new environments, BSM tools have to be more adaptive. They must be able to understand how the new environment supports all the components of a service. This means that we are going to see much more real-time mapping capabilities. In addition, we are going to see BSM tools morph and integrate to the cloud management tools to enable better support for business services on the cloud. The support for cloud will extend hybrid cloud implementations e.g. support of services that span static IT, private clouds, and public clouds in all its different variants.

Click here to read Part One of the BSMdigest interview with Ariel Gordon, VP of Products and Co-Founder of Neebula.

About Ariel Gordon

Ariel Gordon, VP of Products and Co-Founder of Neebula, is a well known expert in the industry, with more than 20 years of experience in systems management. Prior to co-founding Neebula, Ariel was Chief Technology Officer at BMC Software. At BMC, Ariel was one of the creators of BMC's Business Service Management (BSM) strategy and pioneered the creation BMC's BSM Atrium integration infrastructure. Ariel joined BMC through the acquisition of New Dimension Software, where he served as VP of R&D and CTO. Ariel was a driving force behind New Dimension's successful CONTROL product line which included CONTROL-M, one of the leading scheduling products in the market.

Hot Topic
The Latest
The Latest 10

The Latest

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 ...

The gap is widening between what teams spend on observability tools and the value they receive amid surging data volumes and budget pressures, according to The Breaking Point for Observability Leaders, a report from Imply ...