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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

According to Auvik's 2025 IT Trends Report, 60% of IT professionals feel at least moderately burned out on the job, with 43% stating that their workload is contributing to work stress. At the same time, many IT professionals are naming AI and machine learning as key areas they'd most like to upskill ...

Businesses that face downtime or outages risk financial and reputational damage, as well as reducing partner, shareholder, and customer trust. One of the major challenges that enterprises face is implementing a robust business continuity plan. What's the solution? The answer may lie in disaster recovery tactics such as truly immutable storage and regular disaster recovery testing ...

IT spending is expected to jump nearly 10% in 2025, and organizations are now facing pressure to manage costs without slowing down critical functions like observability. To meet the challenge, leaders are turning to smarter, more cost effective business strategies. Enter stage right: OpenTelemetry, the missing piece of the puzzle that is no longer just an option but rather a strategic advantage ...

Amidst the threat of cyberhacks and data breaches, companies install several security measures to keep their business safely afloat. These measures aim to protect businesses, employees, and crucial data. Yet, employees perceive them as burdensome. Frustrated with complex logins, slow access, and constant security checks, workers decide to completely bypass all security set-ups ...

Image
Cloudbrink's Personal SASE services provide last-mile acceleration and reduction in latency

In MEAN TIME TO INSIGHT Episode 13, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses hybrid multi-cloud networking strategy ... 

In high-traffic environments, the sheer volume and unpredictable nature of network incidents can quickly overwhelm even the most skilled teams, hindering their ability to react swiftly and effectively, potentially impacting service availability and overall business performance. This is where closed-loop remediation comes into the picture: an IT management concept designed to address the escalating complexity of modern networks ...

In 2025, enterprise workflows are undergoing a seismic shift. Propelled by breakthroughs in generative AI (GenAI), large language models (LLMs), and natural language processing (NLP), a new paradigm is emerging — agentic AI. This technology is not just automating tasks; it's reimagining how organizations make decisions, engage customers, and operate at scale ...

In the early days of the cloud revolution, business leaders perceived cloud services as a means of sidelining IT organizations. IT was too slow, too expensive, or incapable of supporting new technologies. With a team of developers, line of business managers could deploy new applications and services in the cloud. IT has been fighting to retake control ever since. Today, IT is back in the driver's seat, according to new research by Enterprise Management Associates (EMA) ...

In today's fast-paced and increasingly complex network environments, Network Operations Centers (NOCs) are the backbone of ensuring continuous uptime, smooth service delivery, and rapid issue resolution. However, the challenges faced by NOC teams are only growing. In a recent study, 78% state network complexity has grown significantly over the last few years while 84% regularly learn about network issues from users. It is imperative we adopt a new approach to managing today's network experiences ...

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From growing reliance on FinOps teams to the increasing attention on artificial intelligence (AI), and software licensing, the Flexera 2025 State of the Cloud Report digs into how organizations are improving cloud spend efficiency, while tackling the complexities of emerging technologies ...