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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

Performance bottlenecks aren't uncommon when it comes to rolling out new technology, regardless of how capable or game-changing that technology might be. Every generation of new tech has encountered roadblocks that had to be overcome before it was truly able to shine. Virtualization forced organizations to rethink resource allocation, cloud transformation had us shift our focus toward scalability and elasticity, and microservices introduced entirely new challenges around observability and distributed systems. There's something different about AI, however ...

Consider a single order represented across order-management, execution, and settlement systems. Each database, message broker, and application may be online and processing its own records correctly. Yet the workflow has failed if related events arrive on different clocks, rely on inconsistent state, or cannot be reconciled before an operational decision must be made ...

AI now exists in almost every IT workflow. In a recent survey of more than 800 IT service professionals, all respondents indicated the use of AI in some form within their organization. But there's a growing paradox: if dashboards are clearing faster and alerts are resolved at unprecedented speed, why aren't IT service desks reporting lighter workloads? The research found that 71% of IT teams said their actual workload has remained flat or increased since adopting AI. This reality appears to contradict what we’ve been told about AI ...

Two years ago, almost every customer conversation about AI started with the same questions: Which model should we use? What can it do? Is it ready for the enterprise? Today, those discussions have moved on. CIOs are far more interested in how to govern AI, integrate it with existing systems, prepare their workforce and make it part of everyday operations. The challenge is no longer to prove that AI can deliver value. It's instead about how to embed AI into the business in a way that's secure, scalable and delivers measurable outcomes ...

Two things happened to production incidents between 2023 and now, and they did not happen at the same speed. The first is that a class of dependency that barely existed three years ago now accounts for one incident in ten. Incidents disclosed by AI model and AI application providers rose from 1.7% of all disclosed unplanned incidents in 2023 to 10.7% in 2026 year to date, roughly a sixfold rise; that counts only incidents at AI companies themselves, so the true share is higher. The second is that the time to close an incident has not come down ...

When an AI assistant gives an incomplete or incorrect answer, teams often blame the model. They adjust prompts, switch models, increase context windows or test a new retrieval strategy. However the model may not be a problem. In many enterprise AI workflows, the problem begins inside the document-ingestion pipeline ...

If you talk to any security or observability teams right now, they're all fighting the same fire: their tooling was built to ingest X, but their sources are pumping Y and soon to be doing Z. The knee-jerk reaction is always the same: we need more platform. However, this reaction is wrong. Let me explain why, because the solution to this problem is foundational, not financial. Instead of hurling yet more money at the problem, make sure you've done what's needed upstream ...

Rapid AI adoption and the unique ways AI workloads operate is redefining the scope and structure of what these teams must deliver. This shift is forcing organizations to rethink how they manage scale, automation, and control, according to The State of SRE and Platform Engineering 2026, a new report from Dynatrace ...

AI is usually talked about as a software tool, but it also depends heavily on the network behind it. Whether a company is using AI for chatbots, automation, monitoring, analytics, or employee support, all of that information has to move across the network in a reliable and secure way. That means AI is not just an application decision. It is also an infrastructure decision. Before organizations rush into AI, they should ask a simple question: Is our network ready to support it? ...

Enterprise AI often lacks governed access to where business processes actually execute. Without that access, AI agents may be able to reason, but they cannot operate reliably across enterprise workflows. For AI agents to effectively carry out workflows, they will require integration-layer context and controls. Organizations can implement these prerequisites by providing AI with managed access to the middleware layer ...

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

Performance bottlenecks aren't uncommon when it comes to rolling out new technology, regardless of how capable or game-changing that technology might be. Every generation of new tech has encountered roadblocks that had to be overcome before it was truly able to shine. Virtualization forced organizations to rethink resource allocation, cloud transformation had us shift our focus toward scalability and elasticity, and microservices introduced entirely new challenges around observability and distributed systems. There's something different about AI, however ...

Consider a single order represented across order-management, execution, and settlement systems. Each database, message broker, and application may be online and processing its own records correctly. Yet the workflow has failed if related events arrive on different clocks, rely on inconsistent state, or cannot be reconciled before an operational decision must be made ...

AI now exists in almost every IT workflow. In a recent survey of more than 800 IT service professionals, all respondents indicated the use of AI in some form within their organization. But there's a growing paradox: if dashboards are clearing faster and alerts are resolved at unprecedented speed, why aren't IT service desks reporting lighter workloads? The research found that 71% of IT teams said their actual workload has remained flat or increased since adopting AI. This reality appears to contradict what we’ve been told about AI ...

Two years ago, almost every customer conversation about AI started with the same questions: Which model should we use? What can it do? Is it ready for the enterprise? Today, those discussions have moved on. CIOs are far more interested in how to govern AI, integrate it with existing systems, prepare their workforce and make it part of everyday operations. The challenge is no longer to prove that AI can deliver value. It's instead about how to embed AI into the business in a way that's secure, scalable and delivers measurable outcomes ...

Two things happened to production incidents between 2023 and now, and they did not happen at the same speed. The first is that a class of dependency that barely existed three years ago now accounts for one incident in ten. Incidents disclosed by AI model and AI application providers rose from 1.7% of all disclosed unplanned incidents in 2023 to 10.7% in 2026 year to date, roughly a sixfold rise; that counts only incidents at AI companies themselves, so the true share is higher. The second is that the time to close an incident has not come down ...

When an AI assistant gives an incomplete or incorrect answer, teams often blame the model. They adjust prompts, switch models, increase context windows or test a new retrieval strategy. However the model may not be a problem. In many enterprise AI workflows, the problem begins inside the document-ingestion pipeline ...

If you talk to any security or observability teams right now, they're all fighting the same fire: their tooling was built to ingest X, but their sources are pumping Y and soon to be doing Z. The knee-jerk reaction is always the same: we need more platform. However, this reaction is wrong. Let me explain why, because the solution to this problem is foundational, not financial. Instead of hurling yet more money at the problem, make sure you've done what's needed upstream ...

Rapid AI adoption and the unique ways AI workloads operate is redefining the scope and structure of what these teams must deliver. This shift is forcing organizations to rethink how they manage scale, automation, and control, according to The State of SRE and Platform Engineering 2026, a new report from Dynatrace ...

AI is usually talked about as a software tool, but it also depends heavily on the network behind it. Whether a company is using AI for chatbots, automation, monitoring, analytics, or employee support, all of that information has to move across the network in a reliable and secure way. That means AI is not just an application decision. It is also an infrastructure decision. Before organizations rush into AI, they should ask a simple question: Is our network ready to support it? ...

Enterprise AI often lacks governed access to where business processes actually execute. Without that access, AI agents may be able to reason, but they cannot operate reliably across enterprise workflows. For AI agents to effectively carry out workflows, they will require integration-layer context and controls. Organizations can implement these prerequisites by providing AI with managed access to the middleware layer ...