Skip to main content

Cisco Data Fabric Released

Cisco announced the Cisco Data Fabric, a new architecture that will empower organizations to harness the value of their machine data with AI. 

Powered by the Splunk platform, the Cisco Data Fabric is designed to dramatically reduce the cost and complexity of handling machine data at scale and leveraging it for AI applications, such as training custom AI models, powering agentic workflows, or correlating multiple streams of both machine and business data to extract insights and drive better decisions.

“Organizations everywhere are sitting on a gold mine of machine data that’s been too complex, cumbersome, and costly to leverage for AI, until today,” said Jeetu Patel, President and Chief Product Officer at Cisco. “From sensor readings and factory metrics to checkout system data and event updates from apps, servers, networks and more, machine data drives how businesses operate. Splunk revolutionized data and analytics for the cloud. And now, the Cisco Data Fabric is poised to do the same for AI by making it possible for enterprises to build AI models with their own proprietary machine data.”

The Cisco Data Fabric is purpose-built for the AI era, enabling organizations to innovate faster, strengthen security, and achieve greater business agility. By unifying and activating machine data from every corner of the enterprise, the framework delivers turnkey solutions that reduce cost and complexity while overcoming the challenges of managing distributed data at scale.

“Our goal is to give customers the fastest, most secure path from data to action,” said Kamal Hathi, SVP and GM, Splunk, a Cisco company. “By embedding AI across the platform and embracing open standards, we’re not just helping organizations analyze information faster—we're enabling them to anticipate change, scale innovation without unnecessary complexity, and deliver digital services that are more resilient, adaptive, and responsive to the needs of their users.”

The Cisco Data Fabric transforms streams of data into actionable intelligence that helps customers accelerate decision-making, reduce operational risk, and fuel innovation. The framework’s intelligent edge data management enables advanced data filtering, shaping, and tiering, while powerful federation capabilities correlate insights across various domains – helping to provide near real-time, end-to-end operational intelligence. With a next-generation experience layer driven by AI-assistants and agentic capabilities, organizations can achieve dramatic gains in speed to resolution, reduce administrative burden, and empower teams to make faster decisions.

With the power of the Cisco Data Fabric, organizations will be able to:

Operate on machine data at extreme scale

  • Unified, Intelligent Data Foundation: Simplify transformation of data across edge, cloud, and on-premises, including SecOps, ITOps, DevOps, and NetOps, into real-time, actionable insights while optimizing for cost and efficiency.
  • Cross-Domain Real-Time Search and Analysis: Quickly search and analyze data where it resides, federating across sources like Amazon S3 (available now), Apache Iceberg, Delta Lake (with Spark), Snowflake, and Microsoft Azure, while intelligently routing data to the most appropriate storage or analytic engine for the workload. Additional sources will be available in 2026.
  • Flexible, Open Architecture: Adapts to multiple environments, spanning on-premises and cloud deployments, including high compliance with open standards, plug-and-play integrations, and self-service tools to empower innovation without limitations.

Unlock the value of proprietary data

  • Time Series Foundation Model (coming soon): Powers advanced pattern analysis and temporal reasoning on time series data, enabling advanced anomaly detection, forecasting, and automated root cause analysis across the Cisco Data Fabric. It drives proactive operations, accelerates incident response, and turns machine data into actionable intelligence.
  • Fuel for AI Innovation: Unique capabilities such as Splunk Machine Data Lake provide a persistent, AI-ready foundation for both model training and enterprise analytics. Together with the Splunk AI Toolkit (formerly known as the Machine Learning Toolkit) and Splunk Model Context Protocol Server, these innovations help to transform machine data into a fuel source for advanced AI capabilities.

Unify the experiences for humans and AI agents

  • Cisco AI Canvas: Integrating with Splunk Cloud Platform, Cisco AI Canvas provides an AI agent to orchestrate the analysis workflow and a workspace for team collaboration. This new virtual war room experience helps teams discover deeper insights, collaborate in real-time, and take decisive action faster than ever before. Splunk users can access advanced investigation and visualization tools as well as effortlessly collaborate with peers and extend findings with new knowledge objects, alerts, and reports within a unified and intuitive interface.
  • AI-Native at Every Step: The Splunk platform includes built-in AI capabilities to help at every stage of the data lifecycle – from onboarding and data management to agentic search and user experience – driving unprecedented productivity, agility, and innovation.

The Cisco Data Fabric is built using Splunk Enterprise and Splunk Cloud Platform capabilities, and is available today. It will incorporate future advances across data management, federation and AI. Additional features will become available through 2026.

The Splunk AI Toolkit is available now, with newly hosted models available in 2026.

Replay S3 for Federated Analytics will be available in October 2025 across the Cisco Data Fabric.

The Time Series Foundation Model will be listed on Hugging Face, an open-source community, in November 2025.

The Cisco AI Canvas integration with Splunk and Splunk Machine Data Lake will be available in 2026.

The Latest

Every digital customer interaction, every cloud deployment, and every AI model depends on the same foundation: the ability to see, understand, and act on data in real time ... Recent data from Splunk confirms that 74% of the business leaders believe observability is essential to monitoring critical business processes, and 66% feel it's key to understanding user journeys. Because while the unknown is inevitable, observability makes it manageable. Let's explore why ...

Organizations that perform regular audits and assessments of AI system performance and compliance are over three times more likely to achieve high GenAI value than organizations that do not, according to a survey by Gartner ...

Kubernetes has become the backbone of cloud infrastructure, but it's also one of its biggest cost drivers. Recent research shows that 98% of senior IT leaders say Kubernetes now drives cloud spend, yet 91% still can't optimize it effectively. After years of adoption, most organizations have moved past discovery. They know container sprawl, idle resources and reactive scaling inflate costs. What they don't know is how to fix it ...

Artificial intelligence is no longer a future investment. It's already embedded in how we work — whether through copilots in productivity apps, real-time transcription tools in meetings, or machine learning models fueling analytics and personalization. But while enterprise adoption accelerates, there's one critical area many leaders have yet to examine: Can your network actually support AI at the speed your users expect? ...

The more technology businesses invest in, the more potential attack surfaces they have that can be exploited. Without the right continuity plans in place, the disruptions caused by these attacks can bring operations to a standstill and cause irreparable damage to an organization. It's essential to take the time now to ensure your business has the right tools, processes, and recovery initiatives in place to weather any type of IT disaster that comes up. Here are some effective strategies you can follow to achieve this ...

In today's fast-paced AI landscape, CIOs, IT leaders, and engineers are constantly challenged to manage increasingly complex and interconnected systems. The sheer scale and velocity of data generated by modern infrastructure can be overwhelming, making it difficult to maintain uptime, prevent outages, and create a seamless customer experience. This complexity is magnified by the industry's shift towards agentic AI ...

In MEAN TIME TO INSIGHT Episode 19, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA explains the cause of the AWS outage in October ... 

The explosion of generative AI and machine learning capabilities has fundamentally changed the conversation around cloud migration. It's no longer just about modernization or cost savings — it's about being able to compete in a market where AI is rapidly becoming table stakes. Companies that can't quickly spin up AI workloads, feed models with data at scale, or experiment with new capabilities are falling behind faster than ever before. But here's what I'm seeing: many organizations want to capitalize on AI, but they're stuck ...

On September 16, the world celebrated the 10th annual IT Pro Day, giving companies a chance to laud the professionals who serve as the backbone to almost every successful business across the globe. Despite the growing importance of their roles, many IT pros still work in the background and often go underappreciated ...

Artificial Intelligence (AI) is reshaping observability, and observability is becoming essential for AI. This is a two-way relationship that is increasingly relevant as enterprises scale generative AI ... This dual role makes AI and observability inseparable. In this blog, I cover more details of each side ...

Cisco Data Fabric Released

Cisco announced the Cisco Data Fabric, a new architecture that will empower organizations to harness the value of their machine data with AI. 

Powered by the Splunk platform, the Cisco Data Fabric is designed to dramatically reduce the cost and complexity of handling machine data at scale and leveraging it for AI applications, such as training custom AI models, powering agentic workflows, or correlating multiple streams of both machine and business data to extract insights and drive better decisions.

“Organizations everywhere are sitting on a gold mine of machine data that’s been too complex, cumbersome, and costly to leverage for AI, until today,” said Jeetu Patel, President and Chief Product Officer at Cisco. “From sensor readings and factory metrics to checkout system data and event updates from apps, servers, networks and more, machine data drives how businesses operate. Splunk revolutionized data and analytics for the cloud. And now, the Cisco Data Fabric is poised to do the same for AI by making it possible for enterprises to build AI models with their own proprietary machine data.”

The Cisco Data Fabric is purpose-built for the AI era, enabling organizations to innovate faster, strengthen security, and achieve greater business agility. By unifying and activating machine data from every corner of the enterprise, the framework delivers turnkey solutions that reduce cost and complexity while overcoming the challenges of managing distributed data at scale.

“Our goal is to give customers the fastest, most secure path from data to action,” said Kamal Hathi, SVP and GM, Splunk, a Cisco company. “By embedding AI across the platform and embracing open standards, we’re not just helping organizations analyze information faster—we're enabling them to anticipate change, scale innovation without unnecessary complexity, and deliver digital services that are more resilient, adaptive, and responsive to the needs of their users.”

The Cisco Data Fabric transforms streams of data into actionable intelligence that helps customers accelerate decision-making, reduce operational risk, and fuel innovation. The framework’s intelligent edge data management enables advanced data filtering, shaping, and tiering, while powerful federation capabilities correlate insights across various domains – helping to provide near real-time, end-to-end operational intelligence. With a next-generation experience layer driven by AI-assistants and agentic capabilities, organizations can achieve dramatic gains in speed to resolution, reduce administrative burden, and empower teams to make faster decisions.

With the power of the Cisco Data Fabric, organizations will be able to:

Operate on machine data at extreme scale

  • Unified, Intelligent Data Foundation: Simplify transformation of data across edge, cloud, and on-premises, including SecOps, ITOps, DevOps, and NetOps, into real-time, actionable insights while optimizing for cost and efficiency.
  • Cross-Domain Real-Time Search and Analysis: Quickly search and analyze data where it resides, federating across sources like Amazon S3 (available now), Apache Iceberg, Delta Lake (with Spark), Snowflake, and Microsoft Azure, while intelligently routing data to the most appropriate storage or analytic engine for the workload. Additional sources will be available in 2026.
  • Flexible, Open Architecture: Adapts to multiple environments, spanning on-premises and cloud deployments, including high compliance with open standards, plug-and-play integrations, and self-service tools to empower innovation without limitations.

Unlock the value of proprietary data

  • Time Series Foundation Model (coming soon): Powers advanced pattern analysis and temporal reasoning on time series data, enabling advanced anomaly detection, forecasting, and automated root cause analysis across the Cisco Data Fabric. It drives proactive operations, accelerates incident response, and turns machine data into actionable intelligence.
  • Fuel for AI Innovation: Unique capabilities such as Splunk Machine Data Lake provide a persistent, AI-ready foundation for both model training and enterprise analytics. Together with the Splunk AI Toolkit (formerly known as the Machine Learning Toolkit) and Splunk Model Context Protocol Server, these innovations help to transform machine data into a fuel source for advanced AI capabilities.

Unify the experiences for humans and AI agents

  • Cisco AI Canvas: Integrating with Splunk Cloud Platform, Cisco AI Canvas provides an AI agent to orchestrate the analysis workflow and a workspace for team collaboration. This new virtual war room experience helps teams discover deeper insights, collaborate in real-time, and take decisive action faster than ever before. Splunk users can access advanced investigation and visualization tools as well as effortlessly collaborate with peers and extend findings with new knowledge objects, alerts, and reports within a unified and intuitive interface.
  • AI-Native at Every Step: The Splunk platform includes built-in AI capabilities to help at every stage of the data lifecycle – from onboarding and data management to agentic search and user experience – driving unprecedented productivity, agility, and innovation.

The Cisco Data Fabric is built using Splunk Enterprise and Splunk Cloud Platform capabilities, and is available today. It will incorporate future advances across data management, federation and AI. Additional features will become available through 2026.

The Splunk AI Toolkit is available now, with newly hosted models available in 2026.

Replay S3 for Federated Analytics will be available in October 2025 across the Cisco Data Fabric.

The Time Series Foundation Model will be listed on Hugging Face, an open-source community, in November 2025.

The Cisco AI Canvas integration with Splunk and Splunk Machine Data Lake will be available in 2026.

The Latest

Every digital customer interaction, every cloud deployment, and every AI model depends on the same foundation: the ability to see, understand, and act on data in real time ... Recent data from Splunk confirms that 74% of the business leaders believe observability is essential to monitoring critical business processes, and 66% feel it's key to understanding user journeys. Because while the unknown is inevitable, observability makes it manageable. Let's explore why ...

Organizations that perform regular audits and assessments of AI system performance and compliance are over three times more likely to achieve high GenAI value than organizations that do not, according to a survey by Gartner ...

Kubernetes has become the backbone of cloud infrastructure, but it's also one of its biggest cost drivers. Recent research shows that 98% of senior IT leaders say Kubernetes now drives cloud spend, yet 91% still can't optimize it effectively. After years of adoption, most organizations have moved past discovery. They know container sprawl, idle resources and reactive scaling inflate costs. What they don't know is how to fix it ...

Artificial intelligence is no longer a future investment. It's already embedded in how we work — whether through copilots in productivity apps, real-time transcription tools in meetings, or machine learning models fueling analytics and personalization. But while enterprise adoption accelerates, there's one critical area many leaders have yet to examine: Can your network actually support AI at the speed your users expect? ...

The more technology businesses invest in, the more potential attack surfaces they have that can be exploited. Without the right continuity plans in place, the disruptions caused by these attacks can bring operations to a standstill and cause irreparable damage to an organization. It's essential to take the time now to ensure your business has the right tools, processes, and recovery initiatives in place to weather any type of IT disaster that comes up. Here are some effective strategies you can follow to achieve this ...

In today's fast-paced AI landscape, CIOs, IT leaders, and engineers are constantly challenged to manage increasingly complex and interconnected systems. The sheer scale and velocity of data generated by modern infrastructure can be overwhelming, making it difficult to maintain uptime, prevent outages, and create a seamless customer experience. This complexity is magnified by the industry's shift towards agentic AI ...

In MEAN TIME TO INSIGHT Episode 19, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA explains the cause of the AWS outage in October ... 

The explosion of generative AI and machine learning capabilities has fundamentally changed the conversation around cloud migration. It's no longer just about modernization or cost savings — it's about being able to compete in a market where AI is rapidly becoming table stakes. Companies that can't quickly spin up AI workloads, feed models with data at scale, or experiment with new capabilities are falling behind faster than ever before. But here's what I'm seeing: many organizations want to capitalize on AI, but they're stuck ...

On September 16, the world celebrated the 10th annual IT Pro Day, giving companies a chance to laud the professionals who serve as the backbone to almost every successful business across the globe. Despite the growing importance of their roles, many IT pros still work in the background and often go underappreciated ...

Artificial Intelligence (AI) is reshaping observability, and observability is becoming essential for AI. This is a two-way relationship that is increasingly relevant as enterprises scale generative AI ... This dual role makes AI and observability inseparable. In this blog, I cover more details of each side ...