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Second Gear Application Performance Management

Marcel M. Karman

In 2014 Gartner predicted that "75 percent of IT organizations will be bi-modal in some way by 2017." We are in the midst of this two-speed IT approach that organizations are adopting at an increasing rate to stay relevant for their customers. Where Speed 1 is the traditional IT that is being managed by the IT Operations persona, and Speed 2 is the agile IT where within the organization especially the Developer persona and the Line of Business Persona are involved to get the most out of the digital innovations that flood our daily lives.

One thing that these personas have in common is that they have a need for monitoring. In this blog I will focus on the needs of the various personas.

The Developer

Obviously a developer wants to build nice applications or cloud services. They want to build apps quickly like startups do, without being bogged down by testing and support, and wants to spend time on improving things rather than fixing things.

The requirements of a developer are that they want to be sure that their application is running and performing well for their end-users and if it’s not functioning properly than they need monitoring to help them to find the problem. And very important; the monitoring tool should not be intrusive and be very simple to use. Tools should fit the startup mentality workflow!

The Line of Business

You can say that the Line of Business (LoB) represent the organization`s customers. So they commonly want to improve the customer satisfaction and be able to see which services are successful and which ones are not. Requirements of the LoB are often that they want visibility into the customer experience of applications and services.

IT Operations

The IT Operations persona is another large user of monitoring solutions. Their point of view differs very much of that of the LoB and the Developer. Where the Developer and LoB have a startup mentality, the IT Operations persona most of the time has a mentality far from that. IT Operations has to deal with the scaling of applications that are being managed and they have to meet security and compliance standards as well. Important to them is that they can deliver applications in a controlled and efficient way. A status quo situation would be ideal for them because this improves the quality of the IT services and minimizes the risk of outages. However new services must be introduced by the organization to stay competitive, but this can destabilize the infrastructure and is therefore risky. So IT Operations is always in a balancing act; create stability – and managing newly introduced applications and services in the environment.

The requirements of IT Operations are at a minimum to manage services across the entire hybrid cloud environment and rapidly determine the cause of any issues. So therefore they need end-to-end visibility and control – aka One Dashboard where everything comes together from the on-premise environment and all the different cloud environments.

As an example; IT Operations could use an on-premise Application Performance Management (APM) solution that enables them to obtain the required visibility and control of the hybrid cloud environment. All the monitoring metrics that originate from the different environments (public and private cloud) can be shown in One Dashboard where IT Operations has an instant view on what is happening. Furthermore, IT Operations has always the need to work as effective and efficiently as possible and therefore they need to spot emerging problems fast which is possible with the APM solution build-in innovative analytics that can prevent possible costly outages.

Bringing it together

Below figure gives an overview of how an ideal APM solution could be used in the organization, where the three different personas all can use the same solution. Through the whole organization you should work with one solution, with the same look and feel, and that can fulfill the requirements of the different personas of the organization. The personas can see in their personal monitoring dashboard the items that are important for them and take the required actions when needed. Furthermore this solution can be used in different delivery models, such as on-premise, SaaS and PaaS, so plenty of choices to choose from, or to use jointly.

In the end

In the end there is only one point of view in the organization that really matters. How does the CIO feel about monitoring in the hybrid cloud environment with an organization that is running on two speeds?

The CIO point of view is a "very simple one". Most of the time the CIO has targets on Minimizing Risk, Reducing Costs and Improving Service Levels for the organization’s customers. Therefore an enterprise all-encompassing Application Performance Monitoring solution that can be delivered in multiple delivery models is an ideal fit. So this type of a hybrid APM solution is perfect match for the Two-speed IT approach that organizations are experiencing.

Marcel M. Karman is a Cloud Architect at IBM.

Hot Topics

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 ...

Second Gear Application Performance Management

Marcel M. Karman

In 2014 Gartner predicted that "75 percent of IT organizations will be bi-modal in some way by 2017." We are in the midst of this two-speed IT approach that organizations are adopting at an increasing rate to stay relevant for their customers. Where Speed 1 is the traditional IT that is being managed by the IT Operations persona, and Speed 2 is the agile IT where within the organization especially the Developer persona and the Line of Business Persona are involved to get the most out of the digital innovations that flood our daily lives.

One thing that these personas have in common is that they have a need for monitoring. In this blog I will focus on the needs of the various personas.

The Developer

Obviously a developer wants to build nice applications or cloud services. They want to build apps quickly like startups do, without being bogged down by testing and support, and wants to spend time on improving things rather than fixing things.

The requirements of a developer are that they want to be sure that their application is running and performing well for their end-users and if it’s not functioning properly than they need monitoring to help them to find the problem. And very important; the monitoring tool should not be intrusive and be very simple to use. Tools should fit the startup mentality workflow!

The Line of Business

You can say that the Line of Business (LoB) represent the organization`s customers. So they commonly want to improve the customer satisfaction and be able to see which services are successful and which ones are not. Requirements of the LoB are often that they want visibility into the customer experience of applications and services.

IT Operations

The IT Operations persona is another large user of monitoring solutions. Their point of view differs very much of that of the LoB and the Developer. Where the Developer and LoB have a startup mentality, the IT Operations persona most of the time has a mentality far from that. IT Operations has to deal with the scaling of applications that are being managed and they have to meet security and compliance standards as well. Important to them is that they can deliver applications in a controlled and efficient way. A status quo situation would be ideal for them because this improves the quality of the IT services and minimizes the risk of outages. However new services must be introduced by the organization to stay competitive, but this can destabilize the infrastructure and is therefore risky. So IT Operations is always in a balancing act; create stability – and managing newly introduced applications and services in the environment.

The requirements of IT Operations are at a minimum to manage services across the entire hybrid cloud environment and rapidly determine the cause of any issues. So therefore they need end-to-end visibility and control – aka One Dashboard where everything comes together from the on-premise environment and all the different cloud environments.

As an example; IT Operations could use an on-premise Application Performance Management (APM) solution that enables them to obtain the required visibility and control of the hybrid cloud environment. All the monitoring metrics that originate from the different environments (public and private cloud) can be shown in One Dashboard where IT Operations has an instant view on what is happening. Furthermore, IT Operations has always the need to work as effective and efficiently as possible and therefore they need to spot emerging problems fast which is possible with the APM solution build-in innovative analytics that can prevent possible costly outages.

Bringing it together

Below figure gives an overview of how an ideal APM solution could be used in the organization, where the three different personas all can use the same solution. Through the whole organization you should work with one solution, with the same look and feel, and that can fulfill the requirements of the different personas of the organization. The personas can see in their personal monitoring dashboard the items that are important for them and take the required actions when needed. Furthermore this solution can be used in different delivery models, such as on-premise, SaaS and PaaS, so plenty of choices to choose from, or to use jointly.

In the end

In the end there is only one point of view in the organization that really matters. How does the CIO feel about monitoring in the hybrid cloud environment with an organization that is running on two speeds?

The CIO point of view is a "very simple one". Most of the time the CIO has targets on Minimizing Risk, Reducing Costs and Improving Service Levels for the organization’s customers. Therefore an enterprise all-encompassing Application Performance Monitoring solution that can be delivered in multiple delivery models is an ideal fit. So this type of a hybrid APM solution is perfect match for the Two-speed IT approach that organizations are experiencing.

Marcel M. Karman is a Cloud Architect at IBM.

Hot Topics

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 ...