Many Monitoring and Observability Tools Flood Enterprises with Noise, Not Insight

Learn more about BigPanda

According to an analysis from 130 enterprise organizations using the BigPanda platform, the Monitoring and Observability Tool Effectiveness for IT Event Management report, the average enterprise sends 9.6 million observability events annually to the platform, but fewer than 1 in 5 (18%) are ever acted upon.

Compounding the issue, 27% of alerts occur on weekends, creating unnecessary pressure on already overburdened on-call teams.

"The research confirms what many IT leaders already suspect," said Fred Koopmans, Chief Product Officer at BigPanda. "More monitoring coverage doesn't automatically mean more actionability. Enterprises are investing heavily in observability, but without context, correlation, and enrichment, the signal gets lost."

The report features a monitoring and observability tool effectiveness matrix that shows no monitoring and observability tools combined both widespread usage and consistently high actionability. This signals that even the strongest platforms have room to grow, and the observability industry is still evolving toward optimal performance at scale.

Other key trends and insights include:

Full monitoring coverage doesn't equal value

Most enterprises are drowning in data, creating millions of events (9.6 million, on average) annually. Yet only 18% of incidents were actioned on average, underscoring the disconnect between the belief that comprehensive observability coverage of applications, services, and infrastructure equates to better ITOps, incident management, and customer outcomes.

Some high-coverage tools fall short on signal quality

Some tools contributed a large share of incidents, yet struggle with their lower actionability, highlighting that high usage does not necessarily translate to high operational value. These scalable but noisy tools may benefit from improved configuration and tuning to reduce noise and enhance the precision of alerts.

Full-stack observability is still an illusion

Despite the notion that enterprise organizations are centralizing and consolidating observability with full-stack observability tools, our data shows that enterprises still have a median of 20+ tools they use to monitor on-premises and cloud infrastructure, application and digital experience monitoring.

Open-source remains low-impact at enterprise scale

Despite their popularity among developers, most open-source observability platforms and monitoring tools have yet to deliver high-value, enterprise-grade observability outcomes. Our report shows they frequently produce low-quality signals rather than actionable insights.

Purpose-built monitoring tools tend to align as either specialists or stragglers

They either fell in the top-left quadrant (optimized, high-performance tools) or the bottom-left quadrant (underutilized tools) with lower adoption and weaker signal quality. This indicates that while some purpose-built monitoring tools deliver substantial niche value, others have yet to evolve into broader observability assets.

These results highlight a clear opportunity for IT leaders: consolidate around high-performing tools, decommission low-value ones, and use enriched event data to guide smarter investments.

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Many Monitoring and Observability Tools Flood Enterprises with Noise, Not Insight

Learn more about BigPanda

According to an analysis from 130 enterprise organizations using the BigPanda platform, the Monitoring and Observability Tool Effectiveness for IT Event Management report, the average enterprise sends 9.6 million observability events annually to the platform, but fewer than 1 in 5 (18%) are ever acted upon.

Compounding the issue, 27% of alerts occur on weekends, creating unnecessary pressure on already overburdened on-call teams.

"The research confirms what many IT leaders already suspect," said Fred Koopmans, Chief Product Officer at BigPanda. "More monitoring coverage doesn't automatically mean more actionability. Enterprises are investing heavily in observability, but without context, correlation, and enrichment, the signal gets lost."

The report features a monitoring and observability tool effectiveness matrix that shows no monitoring and observability tools combined both widespread usage and consistently high actionability. This signals that even the strongest platforms have room to grow, and the observability industry is still evolving toward optimal performance at scale.

Other key trends and insights include:

Full monitoring coverage doesn't equal value

Most enterprises are drowning in data, creating millions of events (9.6 million, on average) annually. Yet only 18% of incidents were actioned on average, underscoring the disconnect between the belief that comprehensive observability coverage of applications, services, and infrastructure equates to better ITOps, incident management, and customer outcomes.

Some high-coverage tools fall short on signal quality

Some tools contributed a large share of incidents, yet struggle with their lower actionability, highlighting that high usage does not necessarily translate to high operational value. These scalable but noisy tools may benefit from improved configuration and tuning to reduce noise and enhance the precision of alerts.

Full-stack observability is still an illusion

Despite the notion that enterprise organizations are centralizing and consolidating observability with full-stack observability tools, our data shows that enterprises still have a median of 20+ tools they use to monitor on-premises and cloud infrastructure, application and digital experience monitoring.

Open-source remains low-impact at enterprise scale

Despite their popularity among developers, most open-source observability platforms and monitoring tools have yet to deliver high-value, enterprise-grade observability outcomes. Our report shows they frequently produce low-quality signals rather than actionable insights.

Purpose-built monitoring tools tend to align as either specialists or stragglers

They either fell in the top-left quadrant (optimized, high-performance tools) or the bottom-left quadrant (underutilized tools) with lower adoption and weaker signal quality. This indicates that while some purpose-built monitoring tools deliver substantial niche value, others have yet to evolve into broader observability assets.

These results highlight a clear opportunity for IT leaders: consolidate around high-performing tools, decommission low-value ones, and use enriched event data to guide smarter investments.

Hot Topics

The Latest

The Corporate Network Is Fading - Here's What Replaces It

For decades, enterprise networks were designed around a simple assumption: work happened inside the office. Applications lived in centralized data centers, employees connected through internal infrastructure, and security focused on protecting the perimeter that surrounded everything ... But the way organizations operate today bears little resemblance to that environment. Cloud platforms host critical applications, employees connect from homes and airports as often as they do from offices, and partners collaborate through shared systems that exist far beyond corporate walls. In short, the corporate network no longer resembles the environment it was designed to protect ...

IT Leaders Must Establish a Network Data Architecture Practice

As an analyst who researches how IT organizations design, build, and operate their networks, I find that network data is a constant source of pain. Network teams struggle with data quality, fragmentation, authority, access, and trust. And these issues undermine everything they try to do. Here are the numbers: Only 45% of network teams are completely confident in the accuracy of their network source of truth, which documents the intent of their network ...

Data Center Outages Are Decreasing but More Costly

The 2026 Global Data Center Survey from Uptime Institute reveals an industry navigating workforce constraints, escalating outage expenses, even as rising costs remain the top concern for management teams ...

Observability Has a Physical Layer Now: What AI Infrastructure Teaches IT Operations

The next observability gap may not be in the code. It may be under the rack. That sounds strange until you think about how AI incidents actually feel in the middle of an investigation ... The application dashboard may be accurate. It may also be stopping at the wrong boundary. AI systems depend on software, but they also depend on a dense physical stack: racks, power paths, thermal margin, maintenance activity and, in many environments, liquid cooling. Those physical dependencies can change slowly before they look like a software incident ...

TLS Certificate Expiration Is Becoming an Observability Problem

Certificate expiration is the rare outage you can see coming. Every TLS certificate carries the date it stops working, so the moment it will begin breaking connections is knowable in advance. That's what makes an expired certificate such a frustrating way to lose a service. What's changing now is how often that date comes around ...

Enterprise Cloud Observability: Choosing the Right Starting Point

Enterprises operate different combinations of workloads across cloud, hybrid and multicloud environments. For business-critical workloads, teams need to consider monitoring and observability early so they can detect health issues, investigate failures, and understand operational impact. Organizations place workloads on cloud platforms based on a combination of technical requirements, economics, existing dependencies, organizational standards, and business priorities. Their monitoring priorities therefore depend on what they operate and where those systems run. Those priorities will not look the same for every organization ...

AI Is Making Incident Management More Complex - Bad Data Makes It Harder

Top-performing businesses prioritize data-driven decision making, enabling leaders to move from intuition and gut feel towards evidence-based judgment. But that judgment is only sound when the data underpinning decisions is accurate. With incident management, data accuracy is particularly important. Long-term revenue, customer trust, and operational stability depend on high-quality data that enables teams to quickly identify and address the root cause of major incidents. Against this backdrop, governance becomes a critical endeavor to ensure the right data drives the right action ...

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Beyond Monitoring: Why IT Operations Must Evolve into Decision Operations

Enterprise IT environments have never been more observable ... Yet many organizations still grapple with outages, lengthy incident resolution cycles, and increasing complexity. Most teams do not suffer from a shortage of data. They struggle to determine what deserves attention and what action to take next ... Enterprise IT operations must move beyond monitoring and visibility. The next stage of maturity is decision operations, an approach that helps teams make faster, better-informed decisions ...