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4 Key ITSM Solutions

Dennis Rietvink

To stay competitive, organizations need to constantly evolve and improve all aspects of their businesses. They also have to engage measurable practices to ensure that all implemented changes are cost-effective and vital for their businesses.

ITSM, or IT Service Management, is a modern approach to planning, implementing and managing IT services of an agile, service-oriented organization. The practice is business, rather than technology-centered. IT services add the most value when they are in complete alignment with the needs of an organization. Otherwise, they impede a company's ability to react to market changes, put a strain on the budget, and, ultimately, result in dissatisfied customers and lost business opportunities.

The ability to measure progress and calculate ROI of IT projects is an important part of ITSM. Without a clear idea of project costs, organizations can't plan for the future and choose projects that would add the most strategic value at the lowest cost.

Organizations interested in implementing ITSM practices can follow the ITSM guidelines presented in three frameworks:

ITIL (Information Technology Infrastructure Library) consists of five books - Service Strategy, Service Design, Service Transition, Service Operation and Continual Service Improvement. The books are published to help organizations design, deploy, as well as measure the impact of their ITSM projects.

MOF (Microsoft Operations Framework) includes a number of guides to help design and deploy IT services in the most effective and affordable way. The guides break down the process into three phases - the Plan Phase, the Deliver Phase, and the Operate Phase.

COBIT (Control Objective for Information and Related Technology) offers guides on the ways to align IT objectives with business goals. It breaks down the process into four steps - Plan and Organize, Acquire and Implement, Deliver and Support, and Monitor and Evaluate.

ITSM frameworks are not dependent on one particular technology. The idea is to choose systems and applications that fit best the unique needs of each organization. The winning combination can include several products and services that deliver the best result at the lowest cost.

Some IT solutions can support a number of objectives of ITSM. A comprehensive infrastructure monitoring solution enables organizations to oversee in real time the performance of critical applications to ensure that all business processes are running smoothly.

Four key solutions that help deliver ITSM benefits include the following:

1. Distributed Application Monitoring

By monitoring groups of applications and processes, rather than individual components, an organization can get a better insight into its current business situation, since IT managers can instantly see how the monitored items are connected. The system can separate minor events that can wait to get fixed, from major accidents that require IT managers' immediate attention to prevent a major outage.

2. Notifications

Notifications can be forwarded to IT managers using email, IM, or SMS, ensuring that the right individuals are alerted about any potential problems right away.

3. Historical Data Collection

Historical Data Collection allows IT managers to generate reports on past events, analyze them, and draw conclusions to prevent similar problems from happening in the future.

4. End-user Monitoring

End-user Monitoring enables IT managers to ensure that the end users are not experiencing application performance issues.

ITSM practices can help organizations create flexible and productive IT environments aligned with each organization's unique business goals. There are a lot of solutions that offer a wealth of monitoring features to enable businesses to implement some of the basic principles of ITSM straight away.

Dennis Rietvink is Co-Founder and VP of Product Management at Savision

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 ...

4 Key ITSM Solutions

Dennis Rietvink

To stay competitive, organizations need to constantly evolve and improve all aspects of their businesses. They also have to engage measurable practices to ensure that all implemented changes are cost-effective and vital for their businesses.

ITSM, or IT Service Management, is a modern approach to planning, implementing and managing IT services of an agile, service-oriented organization. The practice is business, rather than technology-centered. IT services add the most value when they are in complete alignment with the needs of an organization. Otherwise, they impede a company's ability to react to market changes, put a strain on the budget, and, ultimately, result in dissatisfied customers and lost business opportunities.

The ability to measure progress and calculate ROI of IT projects is an important part of ITSM. Without a clear idea of project costs, organizations can't plan for the future and choose projects that would add the most strategic value at the lowest cost.

Organizations interested in implementing ITSM practices can follow the ITSM guidelines presented in three frameworks:

ITIL (Information Technology Infrastructure Library) consists of five books - Service Strategy, Service Design, Service Transition, Service Operation and Continual Service Improvement. The books are published to help organizations design, deploy, as well as measure the impact of their ITSM projects.

MOF (Microsoft Operations Framework) includes a number of guides to help design and deploy IT services in the most effective and affordable way. The guides break down the process into three phases - the Plan Phase, the Deliver Phase, and the Operate Phase.

COBIT (Control Objective for Information and Related Technology) offers guides on the ways to align IT objectives with business goals. It breaks down the process into four steps - Plan and Organize, Acquire and Implement, Deliver and Support, and Monitor and Evaluate.

ITSM frameworks are not dependent on one particular technology. The idea is to choose systems and applications that fit best the unique needs of each organization. The winning combination can include several products and services that deliver the best result at the lowest cost.

Some IT solutions can support a number of objectives of ITSM. A comprehensive infrastructure monitoring solution enables organizations to oversee in real time the performance of critical applications to ensure that all business processes are running smoothly.

Four key solutions that help deliver ITSM benefits include the following:

1. Distributed Application Monitoring

By monitoring groups of applications and processes, rather than individual components, an organization can get a better insight into its current business situation, since IT managers can instantly see how the monitored items are connected. The system can separate minor events that can wait to get fixed, from major accidents that require IT managers' immediate attention to prevent a major outage.

2. Notifications

Notifications can be forwarded to IT managers using email, IM, or SMS, ensuring that the right individuals are alerted about any potential problems right away.

3. Historical Data Collection

Historical Data Collection allows IT managers to generate reports on past events, analyze them, and draw conclusions to prevent similar problems from happening in the future.

4. End-user Monitoring

End-user Monitoring enables IT managers to ensure that the end users are not experiencing application performance issues.

ITSM practices can help organizations create flexible and productive IT environments aligned with each organization's unique business goals. There are a lot of solutions that offer a wealth of monitoring features to enable businesses to implement some of the basic principles of ITSM straight away.

Dennis Rietvink is Co-Founder and VP of Product Management at Savision

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 ...