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Open Source Is Dominating Observability

Open source dominance continues in observability, according to the Observability Survey from Grafana Labs.

A remarkable 75% of respondents are now using open source licensing for observability, with 70% reporting that their organizations use both Prometheus and OpenTelemetry in some capacity. Half of all organizations increased their investments in both technologies for the second year in a row.

The 2025 Observability Survey reveals that OpenTelemetry has continued its trajectory toward mainstream status with half of all organizations increasing their investments in the open source project for the second year in a row.

More than two-thirds of organizations (67%) use Prometheus in production in some capacity and while OpenTelemetry has less production usage (41%), it appears to have more momentum for future growth, with more than a third (38%) of respondents investigating it and only 6% reporting they have no plans to use OpenTelemetry at all. The survey also found that vendor neutrality and flexibility remain the most cited requirements for compatible observability solutions, directly aligning with OpenTelemetry's core value proposition.

"Our survey data confirms what we're seeing in the field — organizations aren't choosing between observability technologies, they're embracing multiple approaches to solve real-world problems," said Ted Young, developer programs director at Grafana Labs, cofounder of OpenTelemetry, and member of the OpenTelemetry Governance Committee. "This includes the growing adoption of both OpenTelemetry and Prometheus, two tools that work great together."

Other report findings include:

C-Suite Sees Importance of Observability

Roughly three-quarters of all companies say observability is business-critical at either the CTO, VP, or director level, with CTO being the most common response (33%). Organizations whose C-suite sees observability as business-critical are more likely to adopt more advanced tools and practices such as traces, profiles, SLOs, OpenTelemetry, and unified application and infrastructure observability.

Desire for AI to Tame Complexity Rises

The number one observability concern for respondents is complexity, while alert fatigue is cited as the biggest obstacle to faster incident response, so it's no wonder training-based alerts and faster root cause analysis topped respondents' AI/ML wishlist for observability.

Cost Management Remains Important, But Not Critical

Three-quarters of companies say cost is an important criteria when selecting observability technologies, though less than a third say they're concerned about observability costing too much — meaning organizations are more focused on getting value from their tools and techniques than just selecting the cheapest option.

The Latest

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

In MEAN TIME TO INSIGHT Episode 26, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network compliance ... 

Most production autonomous agents do not run in a vacuum. They run inside cloud infrastructure: virtual machines, containers, pods, managed clusters or private servers. That is where most operations teams start monitoring. Is the VM alive? Is the container running? Did the pod restart? Is memory stable? Is CPU too high? Did the health check pass? Those signals are useful. They tell you whether the shell around the agent is alive. They do not tell you whether the agent inside is actually operational ...

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 ...

Open Source Is Dominating Observability

Open source dominance continues in observability, according to the Observability Survey from Grafana Labs.

A remarkable 75% of respondents are now using open source licensing for observability, with 70% reporting that their organizations use both Prometheus and OpenTelemetry in some capacity. Half of all organizations increased their investments in both technologies for the second year in a row.

The 2025 Observability Survey reveals that OpenTelemetry has continued its trajectory toward mainstream status with half of all organizations increasing their investments in the open source project for the second year in a row.

More than two-thirds of organizations (67%) use Prometheus in production in some capacity and while OpenTelemetry has less production usage (41%), it appears to have more momentum for future growth, with more than a third (38%) of respondents investigating it and only 6% reporting they have no plans to use OpenTelemetry at all. The survey also found that vendor neutrality and flexibility remain the most cited requirements for compatible observability solutions, directly aligning with OpenTelemetry's core value proposition.

"Our survey data confirms what we're seeing in the field — organizations aren't choosing between observability technologies, they're embracing multiple approaches to solve real-world problems," said Ted Young, developer programs director at Grafana Labs, cofounder of OpenTelemetry, and member of the OpenTelemetry Governance Committee. "This includes the growing adoption of both OpenTelemetry and Prometheus, two tools that work great together."

Other report findings include:

C-Suite Sees Importance of Observability

Roughly three-quarters of all companies say observability is business-critical at either the CTO, VP, or director level, with CTO being the most common response (33%). Organizations whose C-suite sees observability as business-critical are more likely to adopt more advanced tools and practices such as traces, profiles, SLOs, OpenTelemetry, and unified application and infrastructure observability.

Desire for AI to Tame Complexity Rises

The number one observability concern for respondents is complexity, while alert fatigue is cited as the biggest obstacle to faster incident response, so it's no wonder training-based alerts and faster root cause analysis topped respondents' AI/ML wishlist for observability.

Cost Management Remains Important, But Not Critical

Three-quarters of companies say cost is an important criteria when selecting observability technologies, though less than a third say they're concerned about observability costing too much — meaning organizations are more focused on getting value from their tools and techniques than just selecting the cheapest option.

The Latest

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

In MEAN TIME TO INSIGHT Episode 26, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network compliance ... 

Most production autonomous agents do not run in a vacuum. They run inside cloud infrastructure: virtual machines, containers, pods, managed clusters or private servers. That is where most operations teams start monitoring. Is the VM alive? Is the container running? Did the pod restart? Is memory stable? Is CPU too high? Did the health check pass? Those signals are useful. They tell you whether the shell around the agent is alive. They do not tell you whether the agent inside is actually operational ...

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 ...