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You Have 40 Monitoring Tools, Make the Next One Count

Richard Whitehead
Moogsoft

In our growing digital economy, end users have no tolerance for downtime. Consequently, IT leaders invest heavily in availability: DevOps and SRE (site reliability engineering) teams to ensure digital apps and services are continuously available and digital tools built to influence uptime.

As recent research uncovered, IT leaders invest in a lot of single-domain monitoring tools. In fact, teams rely on an average of 16 monitoring tools — and up to 40 — according to the Moogsoft State of Availability Report.

Despite this heavy investment, teams are not achieving positive availability outcomes. Perhaps most telling, monitoring tools only catch performance issues or outages about half of the time. Customers flag the rest.

In other words, monitoring tool investments are not paying dividends. They are not helping teams quickly catch data anomalies and expediently fix incidents, and they certainly are not creating a positive customer experience. Yet, DevOps and SREs need monitoring solutions as manually monitoring ever-complex IT ecosystems with ever more data would be impossible.

So what's the secret to modern availability? How can teams better leverage their tools?

The Point Solution Problem: Partial Information

Part of the proliferation of monitoring tools in the IT stack is due to a proliferation of tools in the incident management space in general. Over the past few years, software vendors have introduced a slew of specific point solutions that solve specific problems.

On the positive side, point solutions specialize in monitoring certain aspects of an organization's IT ecosystem: the network, application, IT infrastructure or digital experience. But, problematically, point solutions do not integrate and cannot enable continuous insights across an IT stack. This siloed approach to monitoring:

Costs time and resources

Licensing copious amounts of monitoring tools is expensive. Perhaps even more expensive, human teams need to spend time managing and maintaining these monitoring solutions. And that is likely why research finds engineers spend more time monitoring over any other activity, innovation and value creation included.

Expands operational risk

Siloed approaches to anything — monitoring included — increase operational efficiencies and slow progress. When knowledge sits in one tool, the information tends to get orphaned and this lengthens communication lines and delays incident triage and resolution.

Increases downtime

Issues within the IT ecosystem are typically connected. But, because point solutions lack insight across the entire system, alerts tend to show up in multiple tools, creating a lot of unnecessary noise and further compounding and slowing incident remediation.

The Availability Answer: Use AIOps to Connect Monitoring Tools

To extract value out of monitoring tools and ensure more uptime, engineering teams need to connect their point solutions, creating a single line of sight across the entire incident lifecycle. Domain-agnostic artificial intelligence for IT operations (AIOps) can be this connective tissue. By converging data from all aspects of the incident lifecycle, AIOps connects otherwise siloed point solutions. This integrated approach to monitoring:

Provides a unified dashboard

Point solutions require engineers to hop from tool and tool, monitoring and maintaining various dashboards and charts. AIOps, on the other hand, integrates and aggregates data from across an organization's entire tool stack. As a result, engineering teams can look at one single dashboard that summarizes the health of all of their systems.

Streamlines the incident lifecycle

In addition to providing a summary of system health, AIOps solutions provide one single system of incident engagement. In this incident home base, engineering teams can track the incident lifecycle: detection, notification and resolution. Seeing the full picture of the incident lifecycle in one platform simplifies and speeds the response, and in the meantime, helps engineers understand — and then reduce — the amount of time each phase takes.

Optimizes overall systems

Because AIOps tools take a holistic approach to monitoring, they act as the connective tissue between an organization's monitoring data and help fill data gaps. These solutions make sense of data pulled from multiple point solutions, deduplicating and correlating alerts, enriching data and adding context across systems. This helps teams eliminate noise and identify root causes faster.

Instead of adding another point solution to a growing monitoring toolbox, IT leaders should make their next investment count. And AIOps could be the key. By adopting an AIOps tool, teams understand the whole picture of system health and can sidestep unnecessary noise and alerts to expediently respond to service-disrupting incidents. DevOps and SREs, facing less unplanned work, can invest in the future, paying down technical debt and further increasing system stability.

Richard Whitehead is Chief Evangelist at Moogsoft

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You Have 40 Monitoring Tools, Make the Next One Count

Richard Whitehead
Moogsoft

In our growing digital economy, end users have no tolerance for downtime. Consequently, IT leaders invest heavily in availability: DevOps and SRE (site reliability engineering) teams to ensure digital apps and services are continuously available and digital tools built to influence uptime.

As recent research uncovered, IT leaders invest in a lot of single-domain monitoring tools. In fact, teams rely on an average of 16 monitoring tools — and up to 40 — according to the Moogsoft State of Availability Report.

Despite this heavy investment, teams are not achieving positive availability outcomes. Perhaps most telling, monitoring tools only catch performance issues or outages about half of the time. Customers flag the rest.

In other words, monitoring tool investments are not paying dividends. They are not helping teams quickly catch data anomalies and expediently fix incidents, and they certainly are not creating a positive customer experience. Yet, DevOps and SREs need monitoring solutions as manually monitoring ever-complex IT ecosystems with ever more data would be impossible.

So what's the secret to modern availability? How can teams better leverage their tools?

The Point Solution Problem: Partial Information

Part of the proliferation of monitoring tools in the IT stack is due to a proliferation of tools in the incident management space in general. Over the past few years, software vendors have introduced a slew of specific point solutions that solve specific problems.

On the positive side, point solutions specialize in monitoring certain aspects of an organization's IT ecosystem: the network, application, IT infrastructure or digital experience. But, problematically, point solutions do not integrate and cannot enable continuous insights across an IT stack. This siloed approach to monitoring:

Costs time and resources

Licensing copious amounts of monitoring tools is expensive. Perhaps even more expensive, human teams need to spend time managing and maintaining these monitoring solutions. And that is likely why research finds engineers spend more time monitoring over any other activity, innovation and value creation included.

Expands operational risk

Siloed approaches to anything — monitoring included — increase operational efficiencies and slow progress. When knowledge sits in one tool, the information tends to get orphaned and this lengthens communication lines and delays incident triage and resolution.

Increases downtime

Issues within the IT ecosystem are typically connected. But, because point solutions lack insight across the entire system, alerts tend to show up in multiple tools, creating a lot of unnecessary noise and further compounding and slowing incident remediation.

The Availability Answer: Use AIOps to Connect Monitoring Tools

To extract value out of monitoring tools and ensure more uptime, engineering teams need to connect their point solutions, creating a single line of sight across the entire incident lifecycle. Domain-agnostic artificial intelligence for IT operations (AIOps) can be this connective tissue. By converging data from all aspects of the incident lifecycle, AIOps connects otherwise siloed point solutions. This integrated approach to monitoring:

Provides a unified dashboard

Point solutions require engineers to hop from tool and tool, monitoring and maintaining various dashboards and charts. AIOps, on the other hand, integrates and aggregates data from across an organization's entire tool stack. As a result, engineering teams can look at one single dashboard that summarizes the health of all of their systems.

Streamlines the incident lifecycle

In addition to providing a summary of system health, AIOps solutions provide one single system of incident engagement. In this incident home base, engineering teams can track the incident lifecycle: detection, notification and resolution. Seeing the full picture of the incident lifecycle in one platform simplifies and speeds the response, and in the meantime, helps engineers understand — and then reduce — the amount of time each phase takes.

Optimizes overall systems

Because AIOps tools take a holistic approach to monitoring, they act as the connective tissue between an organization's monitoring data and help fill data gaps. These solutions make sense of data pulled from multiple point solutions, deduplicating and correlating alerts, enriching data and adding context across systems. This helps teams eliminate noise and identify root causes faster.

Instead of adding another point solution to a growing monitoring toolbox, IT leaders should make their next investment count. And AIOps could be the key. By adopting an AIOps tool, teams understand the whole picture of system health and can sidestep unnecessary noise and alerts to expediently respond to service-disrupting incidents. DevOps and SREs, facing less unplanned work, can invest in the future, paying down technical debt and further increasing system stability.

Richard Whitehead is Chief Evangelist at Moogsoft

Hot Topics

The Latest

Significant improvements in operational resilience, more effective use of automation and faster time to market are driving optimism about IT spending in 2025, with a majority of leaders expecting their budgets to increase year-over-year, according to the 2025 State of Digital Operations Report from PagerDuty ...

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Are they simply number crunchers confined to back-office support, or are they the strategic influencers shaping the future of your enterprise? The reality is that data analysts are far more the latter. In fact, 94% of analysts agree their role is pivotal to making high-level business decisions, proving that they are becoming indispensable partners in shaping strategy ...

Today's enterprises exist in rapidly growing, complex IT landscapes that can inadvertently create silos and lead to the accumulation of disparate tools. To successfully manage such growth, these organizations must realize the requisite shift in corporate culture and workflow management needed to build trust in new technologies. This is particularly true in cases where enterprises are turning to automation and autonomic IT to offload the burden from IT professionals. This interplay between technology and culture is crucial in guiding teams using AIOps and observability solutions to proactively manage operations and transition toward a machine-driven IT ecosystem ...

Gartner identified the top data and analytics (D&A) trends for 2025 that are driving the emergence of a wide range of challenges, including organizational and human issues ...

Traditional network monitoring, while valuable, often falls short in providing the context needed to truly understand network behavior. This is where observability shines. In this blog, we'll compare and contrast traditional network monitoring and observability — highlighting the benefits of this evolving approach ...

A recent Rocket Software and Foundry study found that just 28% of organizations fully leverage their mainframe data, a concerning statistic given its critical role in powering AI models, predictive analytics, and informed decision-making ...

What kind of ROI is your organization seeing on its technology investments? If your answer is "it's complicated," you're not alone. According to a recent study conducted by Apptio ... there is a disconnect between enterprise technology spending and organizations' ability to measure the results ...

In today’s data and AI driven world, enterprises across industries are utilizing AI to invent new business models, reimagine business and achieve efficiency in operations. However, enterprises may face challenges like flawed or biased AI decisions, sensitive data breaches and rising regulatory risks ...

In MEAN TIME TO INSIGHT Episode 12, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses purchasing new network observability solutions.... 

There's an image problem with mobile app security. While it's critical for highly regulated industries like financial services, it is often overlooked in others. This usually comes down to development priorities, which typically fall into three categories: user experience, app performance, and app security. When dealing with finite resources such as time, shifting priorities, and team skill sets, engineering teams often have to prioritize one over the others. Usually, security is the odd man out ...

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