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Businesses Are Double-Invested in Monitoring – and Leaders Don't See It

Phil Tee

Our digital economy is intolerant of downtime. But consumers haven't just come to expect always-on digital apps and services. They also expect continuous innovation, new functionality and lightening fast response times.


Organizations have taken note, investing heavily in teams and tools that supposedly increase uptime and free resources for innovation. But leaders have not realized this "throw money at the problem" approach to monitoring is burning through resources without much improvement in availability outcomes.

The Moogsoft State of Availability Report — which helps engineering teams and leaders uncover insights about availability KPIs, teams and tools — found that businesses are double-investing in monitoring. Organizations spend too much money on too many tools, and teams spend the majority of their days monitoring their monitoring tools.

This over-investment in incident management goes largely unnoticed by management. So does the fact that monitoring cycles siphon resources from the future-driven work that delights customers and keeps engineers engaged.

We identify a few common causes of the spend for less approach here:

1. Sprawling single-domain monitoring tools

In a noble attempt to keep digital apps and services available to end users at all times, business leaders buy tools that monitor their increasingly large and complex IT infrastructures. In theory, these tools should speed fixes to performance-affecting issues by continuously scanning systems and notifying engineers about anomalies.

The problem is: Teams have far too many tools. On average, engineers manage 16 monitoring tools. And that number can creep up to 40 as SLAs increase. Sprawling tools like this are unwieldy and license, management and maintenance overheads are expensive. But the over-investment in monitoring doesn't stop there.

2. Days spend in monitoring cycles

IT monitoring tools should bear the brunt of monitoring itself. In principle, these tools relieve engineers from spending too much time on a fairly tedious task and enable them to deliver what customers want: bigger and better technology.

Unfortunately, teams spend by far the most time monitoring over any other task. Why? Engineers spin their wheels managing single-domain tools that are not integrated cross stack. and produce huge volumes of largely useless data. Teams facing a critical outage or incident waste valuable time investigating data from disparate tools and connecting the dots themselves.

3. Leadership-team misalignment

Business leaders do not see just how much time their teams spend on monitoring, and likely believe they're making sound monitoring investments. Leaders believe their teams spend about the same amount of their time on monitoring as they do on other daily (and often future-driven) responsibilities like automation, cloud transformation and development.

4. Stalling innovation and experimentation

With engineering teams stuck in monitoring cycles, something has to give. And unfortunately, that thing is innovation and experimentation — the very activities that delight customers and engage engineering teams. In other words, not only do organizations over-invest in monitoring, they do so to the detriment of customer experience improvements.

The solution: steps to tech stability

If you are part of an engineering team or team leader, chances are you're facing modern-day monitoring problems. Consider these best practices for breaking wasteful monitoring cycles and building your tech stability:

1. Baseline your tools. Audit your existing tools, understand their utilization and what they cost. Then, you can determine which of these assets advance availability goals and which just create more noise.

2. Consolidate your tools. Hold on to only those monitoring tools that provide value. Otherwise, try to shrink your monitoring tools' footprint to decrease total cost of ownership (TCO) and reduce noise.

3. Implement an artificial intelligence for IT Operations (AIOps) solution. Make your next monitoring investment one that makes engineer's jobs less toilsome, not more. AIOps connects cloud and on-prem monitoring tools, giving engineers a central system of engagement for all monitoring activities. The platform alerts engineers to data anomalies and their root cause and automates the entire incident lifecycle.

4. Pay down your technical debt. With time back on your side, tackle the most relevant tech debt and increase system stability. Free even more time by automating away toil and continue to increase availability with chaos engineering.

5. Invest in the future. With time and money saved, refocus your investments on company-differentiating initiatives.

Monitoring tools are essential to uptime. But monitoring cannot be the only thing teams do — especially when it hinders innovation and experimentation. Leaders must make more informed investments to monitor more effectively. Only then can organizations move from maintaining the customer experience to innovating the customer experience.

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Businesses Are Double-Invested in Monitoring – and Leaders Don't See It

Phil Tee

Our digital economy is intolerant of downtime. But consumers haven't just come to expect always-on digital apps and services. They also expect continuous innovation, new functionality and lightening fast response times.


Organizations have taken note, investing heavily in teams and tools that supposedly increase uptime and free resources for innovation. But leaders have not realized this "throw money at the problem" approach to monitoring is burning through resources without much improvement in availability outcomes.

The Moogsoft State of Availability Report — which helps engineering teams and leaders uncover insights about availability KPIs, teams and tools — found that businesses are double-investing in monitoring. Organizations spend too much money on too many tools, and teams spend the majority of their days monitoring their monitoring tools.

This over-investment in incident management goes largely unnoticed by management. So does the fact that monitoring cycles siphon resources from the future-driven work that delights customers and keeps engineers engaged.

We identify a few common causes of the spend for less approach here:

1. Sprawling single-domain monitoring tools

In a noble attempt to keep digital apps and services available to end users at all times, business leaders buy tools that monitor their increasingly large and complex IT infrastructures. In theory, these tools should speed fixes to performance-affecting issues by continuously scanning systems and notifying engineers about anomalies.

The problem is: Teams have far too many tools. On average, engineers manage 16 monitoring tools. And that number can creep up to 40 as SLAs increase. Sprawling tools like this are unwieldy and license, management and maintenance overheads are expensive. But the over-investment in monitoring doesn't stop there.

2. Days spend in monitoring cycles

IT monitoring tools should bear the brunt of monitoring itself. In principle, these tools relieve engineers from spending too much time on a fairly tedious task and enable them to deliver what customers want: bigger and better technology.

Unfortunately, teams spend by far the most time monitoring over any other task. Why? Engineers spin their wheels managing single-domain tools that are not integrated cross stack. and produce huge volumes of largely useless data. Teams facing a critical outage or incident waste valuable time investigating data from disparate tools and connecting the dots themselves.

3. Leadership-team misalignment

Business leaders do not see just how much time their teams spend on monitoring, and likely believe they're making sound monitoring investments. Leaders believe their teams spend about the same amount of their time on monitoring as they do on other daily (and often future-driven) responsibilities like automation, cloud transformation and development.

4. Stalling innovation and experimentation

With engineering teams stuck in monitoring cycles, something has to give. And unfortunately, that thing is innovation and experimentation — the very activities that delight customers and engage engineering teams. In other words, not only do organizations over-invest in monitoring, they do so to the detriment of customer experience improvements.

The solution: steps to tech stability

If you are part of an engineering team or team leader, chances are you're facing modern-day monitoring problems. Consider these best practices for breaking wasteful monitoring cycles and building your tech stability:

1. Baseline your tools. Audit your existing tools, understand their utilization and what they cost. Then, you can determine which of these assets advance availability goals and which just create more noise.

2. Consolidate your tools. Hold on to only those monitoring tools that provide value. Otherwise, try to shrink your monitoring tools' footprint to decrease total cost of ownership (TCO) and reduce noise.

3. Implement an artificial intelligence for IT Operations (AIOps) solution. Make your next monitoring investment one that makes engineer's jobs less toilsome, not more. AIOps connects cloud and on-prem monitoring tools, giving engineers a central system of engagement for all monitoring activities. The platform alerts engineers to data anomalies and their root cause and automates the entire incident lifecycle.

4. Pay down your technical debt. With time back on your side, tackle the most relevant tech debt and increase system stability. Free even more time by automating away toil and continue to increase availability with chaos engineering.

5. Invest in the future. With time and money saved, refocus your investments on company-differentiating initiatives.

Monitoring tools are essential to uptime. But monitoring cannot be the only thing teams do — especially when it hinders innovation and experimentation. Leaders must make more informed investments to monitor more effectively. Only then can organizations move from maintaining the customer experience to innovating the customer experience.

Hot Topics

The Latest

AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...

Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...

A Gartner analyst recently suggested that GenAI tools could create 25% time savings for network operational teams. Where might these time savings come from? How are GenAI tools helping NetOps teams today, and what other tasks might they take on in the future as models continue improving? In general, these savings come from automating or streamlining manual NetOps tasks ...

IT and line-of-business teams are increasingly aligned in their efforts to close the data gap and drive greater collaboration to alleviate IT bottlenecks and offload growing demands on IT teams, according to The 2025 Automation Benchmark Report: Insights from IT Leaders on Enterprise Automation & the Future of AI-Driven Businesses from Jitterbit ...

A large majority (86%) of data management and AI decision makers cite protecting data privacy as a top concern, with 76% of respondents citing ROI on data privacy and AI initiatives across their organization, according to a new Harris Poll from Collibra ...

According to Gartner, Inc. the following six trends will shape the future of cloud over the next four years, ultimately resulting in new ways of working that are digital in nature and transformative in impact ...

2020 was the equivalent of a wedding with a top-shelf open bar. As businesses scrambled to adjust to remote work, digital transformation accelerated at breakneck speed. New software categories emerged overnight. Tech stacks ballooned with all sorts of SaaS apps solving ALL the problems — often with little oversight or long-term integration planning, and yes frequently a lot of duplicated functionality ... But now the music's faded. The lights are on. Everyone from the CIO to the CFO is checking the bill. Welcome to the Great SaaS Hangover ...

Regardless of OpenShift being a scalable and flexible software, it can be a pain to monitor since complete visibility into the underlying operations is not guaranteed ... To effectively monitor an OpenShift environment, IT administrators should focus on these five key elements and their associated metrics ...

An overwhelming majority of IT leaders (95%) believe the upcoming wave of AI-powered digital transformation is set to be the most impactful and intensive seen thus far, according to The Science of Productivity: AI, Adoption, And Employee Experience, a new report from Nexthink ...

Overall outage frequency and the general level of reported severity continue to decline, according to the Outage Analysis 2025 from Uptime Institute. However, cyber security incidents are on the rise and often have severe, lasting impacts ...