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Cisco Announces New Cloud Management Tools

Cisco announced new innovations in cloud-managed networking, delivering on its promise to help customers simplify their IT operations.

With new cloud management tools for industrial IoT applications, simplified dashboards to converge IT and OT operations, and flexible network intelligence to see and secure all industrial assets, Cisco delivers a unified experience that provides true business agility.

"The most effective way to manage growing complexity and provide more insight into business operations is through reliable connectivity and complete visibility across an organization’s operations and assets,” said Vikas Butaney, SVP/GM, SD-WAN, Cloud Connectivity, and Industrial IoT Networking, Cisco. “A strong partnership between all technology teams – security, networking, and operations – is essential.”

Cisco is introducing new cloud services in its IoT Operations Dashboard to increase industrial asset visibility and securely manage assets from anywhere.

- Cisco Cyber Vision is now integrated with Cisco IoT Operations Dashboard to grant IT and operations teams full visibility into IT and OT devices to manage threats across the organization, providing a unified security posture across the entire network.

- Secure Equipment Access Plus makes it easier for IT and OT teams to remotely deploy, manage, and troubleshoot connected equipment. This service now provides access to any connected equipment with IP connectivity, so operations teams can run native applications on their workstations to access remote assets more easily.

These innovations, along with Cisco’s extension of its portfolio of its Catalyst industrial wireless and switching portfolio, provide more common tooling and data so IT and OT teams can work more efficiently together to reduce downtime of critical infrastructure, drive greater business productivity and efficiencies, and enhance overall safety and security.

Having the relevant data at the right time is necessary to optimize users’ digital experiences, but data may not always be easy to collect and correlate. To help customers tackle this challenge, Cisco ThousandEyes now supports OpenTelemetry, the open-source framework and industry standard that partners, customers and providers rely on to generate, collect, process and export cloud-native and distributed telemetry data.

ThousandEyes is making it possible for customers to interconnect cloud and Internet intelligence across a wide range of solutions for unmatched data correlation and insight. With ThousandEyes OpenTelemetry, Cisco is enabling true end-to-end correlated insights across multiple domains, from user to application, for optimal digital experiences.

To simplify network security and policy management, Cisco’s unified SASE solution, Cisco+ Secure Connect, now supports integration into Cisco SD-WAN fabrics using Viptela technology. Cisco SD-WAN customers now have access to fast, secure private applications and internet access, enabling them to deliver a secure experience to their employees anywhere.

This unified solution converges networking and security to provide customers with a single platform and a streamlined operational model that simplifies and scales the visibility, management and control over a hybrid work environment. This converged operating model also provides IT teams with enhanced visibility and control over the network, making the experience easy for them to manage.

The Latest

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

Cisco Announces New Cloud Management Tools

Cisco announced new innovations in cloud-managed networking, delivering on its promise to help customers simplify their IT operations.

With new cloud management tools for industrial IoT applications, simplified dashboards to converge IT and OT operations, and flexible network intelligence to see and secure all industrial assets, Cisco delivers a unified experience that provides true business agility.

"The most effective way to manage growing complexity and provide more insight into business operations is through reliable connectivity and complete visibility across an organization’s operations and assets,” said Vikas Butaney, SVP/GM, SD-WAN, Cloud Connectivity, and Industrial IoT Networking, Cisco. “A strong partnership between all technology teams – security, networking, and operations – is essential.”

Cisco is introducing new cloud services in its IoT Operations Dashboard to increase industrial asset visibility and securely manage assets from anywhere.

- Cisco Cyber Vision is now integrated with Cisco IoT Operations Dashboard to grant IT and operations teams full visibility into IT and OT devices to manage threats across the organization, providing a unified security posture across the entire network.

- Secure Equipment Access Plus makes it easier for IT and OT teams to remotely deploy, manage, and troubleshoot connected equipment. This service now provides access to any connected equipment with IP connectivity, so operations teams can run native applications on their workstations to access remote assets more easily.

These innovations, along with Cisco’s extension of its portfolio of its Catalyst industrial wireless and switching portfolio, provide more common tooling and data so IT and OT teams can work more efficiently together to reduce downtime of critical infrastructure, drive greater business productivity and efficiencies, and enhance overall safety and security.

Having the relevant data at the right time is necessary to optimize users’ digital experiences, but data may not always be easy to collect and correlate. To help customers tackle this challenge, Cisco ThousandEyes now supports OpenTelemetry, the open-source framework and industry standard that partners, customers and providers rely on to generate, collect, process and export cloud-native and distributed telemetry data.

ThousandEyes is making it possible for customers to interconnect cloud and Internet intelligence across a wide range of solutions for unmatched data correlation and insight. With ThousandEyes OpenTelemetry, Cisco is enabling true end-to-end correlated insights across multiple domains, from user to application, for optimal digital experiences.

To simplify network security and policy management, Cisco’s unified SASE solution, Cisco+ Secure Connect, now supports integration into Cisco SD-WAN fabrics using Viptela technology. Cisco SD-WAN customers now have access to fast, secure private applications and internet access, enabling them to deliver a secure experience to their employees anywhere.

This unified solution converges networking and security to provide customers with a single platform and a streamlined operational model that simplifies and scales the visibility, management and control over a hybrid work environment. This converged operating model also provides IT teams with enhanced visibility and control over the network, making the experience easy for them to manage.

The Latest

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.