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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

I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...

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

I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...