Skip to main content

Bridging the Visibility Gap: A Path to Smarter Telecom Infrastructure

Jeff Collins
WanAware

Telecommunications is expanding at an unprecedented pace. With more than $300 billion invested in infrastructure since 2018, the industry is laying the groundwork for a new era powered by 5G, edge computing, AI-driven services, and smarter connectivity for everything from smart cities to remote healthcare. But progress brings complexity.

As WanAware's 2025 Telecom Observability Benchmark Report reveals, many operators are discovering that modernization requires more than physical build outs and CapEx — it also demands the tools and insights to manage, secure, and optimize this fast-growing infrastructure in real time.

The survey of 180 telecom leaders shows there's significant opportunity to enhance visibility across increasingly distributed, dynamic networks. While challenges persist, the data paints a clear path forward: intelligent observability is beneficial and foundational to unlocking the full return on infrastructure investments.

Investment Momentum Is Strong, But Oversight Must Keep Pace

The telecom sector is clearly in expansion mode. Over half (54%) of telecom leaders say their CapEx has increased over the past two years. Yet when it comes to investing in observability — the ability to monitor and act on network performance in real time — only 11% allocate more than 20% of their infrastructure budgets to it. This isn't due to a lack of interest. Rather, many leaders are navigating competing priorities. From expanding into rural markets to deploying new services and meeting customer demands, observability tools can sometimes fall behind in the investment queue.

Still, the connection is clear: visibility enables agility. Just 7% of respondents report having near-complete insight into their infrastructure today, while 62% say they can see less than half of their assets. Closing that gap isn't just about better monitoring. It's about maximizing the potential of every other initiative, from automation to sustainability.

Shared Infrastructure Is a Strategic Asset With New Visibility Requirements

The future of telecom lies in collaboration. Network-to-network interfaces (NNIs), which allow providers to share infrastructure and extend service reach, are now commonplace. Nearly 70% of respondents participate in at least one such arrangement, with some engaged in more than 10. These partnerships unlock powerful capabilities, but also introduce new layers of complexity. The survey found that 55% of operators have experienced service disruptions that could have been avoided with greater visibility, especially across shared or third-party infrastructure.

The good news? This is a solvable challenge. The more providers embrace observability as a shared priority — not just an internal one — the more resilient and high-performing these partnerships can become.

AI's Potential Is Real, But It Needs a Clear Line of Sight

There's widespread excitement about AI's role in telecom. From predictive maintenance to real-time anomaly detection, AI has the power to radically improve network operations. And adoption is growing: 57% of telecom leaders say they're piloting or beginning to implement AI-powered observability tools. Yet only 7% have fully deployed these solutions, and only 6% have seen a dramatic improvement in downtime.

What's holding things back? Respondents pointed to budget constraints, legacy system compatibility, and a need for specialized talent. But the biggest factor may be foundational visibility. AI is most effective when it operates on real-time, accurate data from across the network. AI can't optimize what it can't see. The solution lies in making observability a core component of AI strategies, not an afterthought.

Expansion Brings New Opportunities and Responsibilities

As the industry pushes to close the digital divide, providers are extending fiber, building towers, and deploying edge technologies in regions that have long lacked connectivity. These expansions are essential for equity and economic growth. At the same time, they present a new set of challenges. Roughly 40% of telecom leaders report that over a quarter of their network is currently insufficiently monitored, and one in four say they're not confident in their visibility into recently expanded areas.

Tool complexity is part of the issue. 30% of respondents use seven or more different tools to monitor their networks, making it harder to achieve a unified view. Simplifying and integrating observability can help providers stay ahead of operational demands, especially as networks become more decentralized.

Readiness for the Future Starts with Visibility Today

Telecom leaders are investing in next-generation architectures — from XaaS models to edge services — but many acknowledge they're not yet fully prepared to support these innovations with current visibility tools. Only 27% say they feel ready to provide observability for AI-intensive applications, and 80% report that their monitoring is still mostly manual.

Still, optimism is high. The majority of respondents recognize the need for change, and many are actively working to modernize their observability approach. As the industry continues to evolve, there's a clear appetite for solutions that are intelligent, integrated, and built to scale.

Building a Smarter, More Resilient Future

Observability is no longer optional. It's the key that unlocks everything else. When providers can see their networks clearly, they're better equipped to deliver reliable service, reduce downtime, detect threats early, and respond with speed and confidence. The good news from this year's benchmark report is that telecom leaders are asking the right questions, and many are taking steps toward better visibility. With the right tools and strategies, the industry has the opportunity to close the visibility gap and usher in a new era of efficient, AI-powered operations. As we continue building the networks of the future, observability will be the foundation we build on.

Jeff Collins is CEO of WanAware

The Latest

IT organizations have historically measured success by how quickly they can respond when something goes wrong. The entire discipline of Incident Management has been optimized around mean time to resolution, first-response SLAs and ticket closure rates. But new research suggests that even though this is a well-executed playbook, it's no longer enough to retain customers ...

Production incidents rarely announce themselves as database problems. They appear as slow transactions, timeouts, rising response times, or an application struggling under a workload it previously handled. APM provides an essential starting point. It can identify a slow transaction path, highlight an affected service, and show that a database dependency is consuming more time than expected. But identifying the database as part of the problem is not the same as explaining what is happening inside it ...

Cloud teams are under constant pressure to reduce spend without slowing development or increasing operational risk. They are deploying autoscalers, rightsizing workloads, enforcing resource requests, reviewing utilization dashboards, and building FinOps processes around cloud-native environments. Yet the results often disappoint ...

Ask most IT leaders about their biggest concern with AI and you'll hear the same answer: hallucinations ... Today, however, the conversation has shifted ... As organizations move beyond chatbots and experiments, they are increasingly deploying AI agents that perform multi-step tasks. These systems retrieve documents, query databases, call APIs, generate reports, write code, and make recommendations. The issue is not whether the model can reason. The issue is whether the organization can see, verify, and govern the decisions being made along the way ...

While organizations want to take control of their telemetry, building telemetry pipelines from scratch can be a very daunting, complicated task, even when leveraging open-source standards like OpenTelemetry. It requires specialized knowledge across distributed systems, data engineering, and security. This fragmented approach across systems causes higher operational costs; it puts a strain on resources and reduces efficiency as teams have to work with different interfaces and processes ...

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 ...

Bridging the Visibility Gap: A Path to Smarter Telecom Infrastructure

Jeff Collins
WanAware

Telecommunications is expanding at an unprecedented pace. With more than $300 billion invested in infrastructure since 2018, the industry is laying the groundwork for a new era powered by 5G, edge computing, AI-driven services, and smarter connectivity for everything from smart cities to remote healthcare. But progress brings complexity.

As WanAware's 2025 Telecom Observability Benchmark Report reveals, many operators are discovering that modernization requires more than physical build outs and CapEx — it also demands the tools and insights to manage, secure, and optimize this fast-growing infrastructure in real time.

The survey of 180 telecom leaders shows there's significant opportunity to enhance visibility across increasingly distributed, dynamic networks. While challenges persist, the data paints a clear path forward: intelligent observability is beneficial and foundational to unlocking the full return on infrastructure investments.

Investment Momentum Is Strong, But Oversight Must Keep Pace

The telecom sector is clearly in expansion mode. Over half (54%) of telecom leaders say their CapEx has increased over the past two years. Yet when it comes to investing in observability — the ability to monitor and act on network performance in real time — only 11% allocate more than 20% of their infrastructure budgets to it. This isn't due to a lack of interest. Rather, many leaders are navigating competing priorities. From expanding into rural markets to deploying new services and meeting customer demands, observability tools can sometimes fall behind in the investment queue.

Still, the connection is clear: visibility enables agility. Just 7% of respondents report having near-complete insight into their infrastructure today, while 62% say they can see less than half of their assets. Closing that gap isn't just about better monitoring. It's about maximizing the potential of every other initiative, from automation to sustainability.

Shared Infrastructure Is a Strategic Asset With New Visibility Requirements

The future of telecom lies in collaboration. Network-to-network interfaces (NNIs), which allow providers to share infrastructure and extend service reach, are now commonplace. Nearly 70% of respondents participate in at least one such arrangement, with some engaged in more than 10. These partnerships unlock powerful capabilities, but also introduce new layers of complexity. The survey found that 55% of operators have experienced service disruptions that could have been avoided with greater visibility, especially across shared or third-party infrastructure.

The good news? This is a solvable challenge. The more providers embrace observability as a shared priority — not just an internal one — the more resilient and high-performing these partnerships can become.

AI's Potential Is Real, But It Needs a Clear Line of Sight

There's widespread excitement about AI's role in telecom. From predictive maintenance to real-time anomaly detection, AI has the power to radically improve network operations. And adoption is growing: 57% of telecom leaders say they're piloting or beginning to implement AI-powered observability tools. Yet only 7% have fully deployed these solutions, and only 6% have seen a dramatic improvement in downtime.

What's holding things back? Respondents pointed to budget constraints, legacy system compatibility, and a need for specialized talent. But the biggest factor may be foundational visibility. AI is most effective when it operates on real-time, accurate data from across the network. AI can't optimize what it can't see. The solution lies in making observability a core component of AI strategies, not an afterthought.

Expansion Brings New Opportunities and Responsibilities

As the industry pushes to close the digital divide, providers are extending fiber, building towers, and deploying edge technologies in regions that have long lacked connectivity. These expansions are essential for equity and economic growth. At the same time, they present a new set of challenges. Roughly 40% of telecom leaders report that over a quarter of their network is currently insufficiently monitored, and one in four say they're not confident in their visibility into recently expanded areas.

Tool complexity is part of the issue. 30% of respondents use seven or more different tools to monitor their networks, making it harder to achieve a unified view. Simplifying and integrating observability can help providers stay ahead of operational demands, especially as networks become more decentralized.

Readiness for the Future Starts with Visibility Today

Telecom leaders are investing in next-generation architectures — from XaaS models to edge services — but many acknowledge they're not yet fully prepared to support these innovations with current visibility tools. Only 27% say they feel ready to provide observability for AI-intensive applications, and 80% report that their monitoring is still mostly manual.

Still, optimism is high. The majority of respondents recognize the need for change, and many are actively working to modernize their observability approach. As the industry continues to evolve, there's a clear appetite for solutions that are intelligent, integrated, and built to scale.

Building a Smarter, More Resilient Future

Observability is no longer optional. It's the key that unlocks everything else. When providers can see their networks clearly, they're better equipped to deliver reliable service, reduce downtime, detect threats early, and respond with speed and confidence. The good news from this year's benchmark report is that telecom leaders are asking the right questions, and many are taking steps toward better visibility. With the right tools and strategies, the industry has the opportunity to close the visibility gap and usher in a new era of efficient, AI-powered operations. As we continue building the networks of the future, observability will be the foundation we build on.

Jeff Collins is CEO of WanAware

The Latest

IT organizations have historically measured success by how quickly they can respond when something goes wrong. The entire discipline of Incident Management has been optimized around mean time to resolution, first-response SLAs and ticket closure rates. But new research suggests that even though this is a well-executed playbook, it's no longer enough to retain customers ...

Production incidents rarely announce themselves as database problems. They appear as slow transactions, timeouts, rising response times, or an application struggling under a workload it previously handled. APM provides an essential starting point. It can identify a slow transaction path, highlight an affected service, and show that a database dependency is consuming more time than expected. But identifying the database as part of the problem is not the same as explaining what is happening inside it ...

Cloud teams are under constant pressure to reduce spend without slowing development or increasing operational risk. They are deploying autoscalers, rightsizing workloads, enforcing resource requests, reviewing utilization dashboards, and building FinOps processes around cloud-native environments. Yet the results often disappoint ...

Ask most IT leaders about their biggest concern with AI and you'll hear the same answer: hallucinations ... Today, however, the conversation has shifted ... As organizations move beyond chatbots and experiments, they are increasingly deploying AI agents that perform multi-step tasks. These systems retrieve documents, query databases, call APIs, generate reports, write code, and make recommendations. The issue is not whether the model can reason. The issue is whether the organization can see, verify, and govern the decisions being made along the way ...

While organizations want to take control of their telemetry, building telemetry pipelines from scratch can be a very daunting, complicated task, even when leveraging open-source standards like OpenTelemetry. It requires specialized knowledge across distributed systems, data engineering, and security. This fragmented approach across systems causes higher operational costs; it puts a strain on resources and reduces efficiency as teams have to work with different interfaces and processes ...

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 ...