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New Cisco ThousandEyes Capabilities Deliver Digital Experience Assurance

Cisco announced new Cisco ThousandEyes capabilities that deliver Digital Experience Assurance.

By utilizing robust telemetry data and AI-native technology, customers can now achieve digital resilience and transition from reactive to proactive operations by assuring user digital experience across domains for both owned and unowned environments.

“A majority of outages are caused by operator error. To empower our customers to achieve digital resilience, we harness more than 650 billion daily measurements and utilize the power of AI across the global area network to go beyond human-scale operations,” said Jonathan Davidson, EVP and GM, Cisco Networking. “Digital Experience Assurance powered by ThousandEyes enables proactive, automated event remediation and can even correlate configuration histories across owned infrastructure and your public cloud infrastructure with experiences, which can mean the difference between a 4-hour outage and a 4-minute disruption.”

Cisco ThousandEyes collects and processes billions of daily measurements from both customer owned and unowned networks. It provides automated insights, proactive recommendations, and closed-loop operations tailored to customers. Now powering Digital Experience Assurance for Cisco Networking Cloud, ThousandEyes ingests device and telemetry data from across Cisco networking platforms, including Meraki and Catalyst. Leveraging AI, ThousandEyes surfaces insights and recommendations, and automatically feeds them to customers’ domain controllers and management systems. According to a commissioned Total Economic Impact™ study conducted by Forrester Consulting on behalf of Cisco, a composite organization representative of interviewed ThousandEyes customers reported a significant improvement in IT productivity and user experience. Mean time to resolution (MTTR) of issues decreased by 50-80%, and IT team productivity increased by more than 50%.

ThousandEyes Digital Experience Assurance already delivers AI-native assurance capabilities across Cisco Networking, including AI radio resource management (RRM) for Cisco Catalyst wireless, capacity planning for Cisco Catalyst SD-WAN, and device profiling with AI-based signatures for Cisco Identity Services Engine.

The announcements include:

- ThousandEyes Cloud Insights extends end-to-end visibility deep into public cloud environments by providing topological mappings of its customers’ AWS environments, including service connectivity, configuration changes, and traffic characteristics. By correlating cloud infrastructure and services with user experience, application health, and end-to-end network paths, ThousandEyes delivers deep insight for network, SRE, and cloud operations teams, so they can rapidly identify and resolve their most challenging issues.

- ThousandEyes Traffic Insights extends ThousandEyes visibility deeper into on-premises networks by collecting and correlating traffic flows with its synthetics measurements, enabling customers to rapidly detect performance issues and pinpoint them to real traffic bottlenecks and anomalies within their networks. By providing a unified view of external and internal network conditions, customers can streamline their operational workflows and reduce their mean time to identify (MTTI) and remediate issues—regardless of whether they own the network or not.

- ThousandEyes will support flow collection for both Cisco and non-Cisco networking platforms.

- ThousandEyes Endpoint Experience is now enriched with Meraki Wi-Fi and Local Area Network (LAN) telemetry and device information, enabling customers to gain deeper insight into local network issues impacting user experience.

- Meraki Assurance Overview is now powered by ThousandEyes Internet and SaaS visibility, empowering customers with insight into performance beyond their Meraki Wi-Fi and LAN environment to rapidly pinpoint issues across owned and unowned domains.

The Latest

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 ...

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 ...

New Cisco ThousandEyes Capabilities Deliver Digital Experience Assurance

Cisco announced new Cisco ThousandEyes capabilities that deliver Digital Experience Assurance.

By utilizing robust telemetry data and AI-native technology, customers can now achieve digital resilience and transition from reactive to proactive operations by assuring user digital experience across domains for both owned and unowned environments.

“A majority of outages are caused by operator error. To empower our customers to achieve digital resilience, we harness more than 650 billion daily measurements and utilize the power of AI across the global area network to go beyond human-scale operations,” said Jonathan Davidson, EVP and GM, Cisco Networking. “Digital Experience Assurance powered by ThousandEyes enables proactive, automated event remediation and can even correlate configuration histories across owned infrastructure and your public cloud infrastructure with experiences, which can mean the difference between a 4-hour outage and a 4-minute disruption.”

Cisco ThousandEyes collects and processes billions of daily measurements from both customer owned and unowned networks. It provides automated insights, proactive recommendations, and closed-loop operations tailored to customers. Now powering Digital Experience Assurance for Cisco Networking Cloud, ThousandEyes ingests device and telemetry data from across Cisco networking platforms, including Meraki and Catalyst. Leveraging AI, ThousandEyes surfaces insights and recommendations, and automatically feeds them to customers’ domain controllers and management systems. According to a commissioned Total Economic Impact™ study conducted by Forrester Consulting on behalf of Cisco, a composite organization representative of interviewed ThousandEyes customers reported a significant improvement in IT productivity and user experience. Mean time to resolution (MTTR) of issues decreased by 50-80%, and IT team productivity increased by more than 50%.

ThousandEyes Digital Experience Assurance already delivers AI-native assurance capabilities across Cisco Networking, including AI radio resource management (RRM) for Cisco Catalyst wireless, capacity planning for Cisco Catalyst SD-WAN, and device profiling with AI-based signatures for Cisco Identity Services Engine.

The announcements include:

- ThousandEyes Cloud Insights extends end-to-end visibility deep into public cloud environments by providing topological mappings of its customers’ AWS environments, including service connectivity, configuration changes, and traffic characteristics. By correlating cloud infrastructure and services with user experience, application health, and end-to-end network paths, ThousandEyes delivers deep insight for network, SRE, and cloud operations teams, so they can rapidly identify and resolve their most challenging issues.

- ThousandEyes Traffic Insights extends ThousandEyes visibility deeper into on-premises networks by collecting and correlating traffic flows with its synthetics measurements, enabling customers to rapidly detect performance issues and pinpoint them to real traffic bottlenecks and anomalies within their networks. By providing a unified view of external and internal network conditions, customers can streamline their operational workflows and reduce their mean time to identify (MTTI) and remediate issues—regardless of whether they own the network or not.

- ThousandEyes will support flow collection for both Cisco and non-Cisco networking platforms.

- ThousandEyes Endpoint Experience is now enriched with Meraki Wi-Fi and Local Area Network (LAN) telemetry and device information, enabling customers to gain deeper insight into local network issues impacting user experience.

- Meraki Assurance Overview is now powered by ThousandEyes Internet and SaaS visibility, empowering customers with insight into performance beyond their Meraki Wi-Fi and LAN environment to rapidly pinpoint issues across owned and unowned domains.

The Latest

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 ...

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 ...