The Cisco Data Fabric and Splunk Federated Search for Snowflake will enable enterprises to unify, analyze, and gain insights from distributed business and machine data.
At this week’s Splunk .conf25 event in Boston, Cisco unveiled a new data architecture that’s powered by the Splunk platform and designed to help enterprises glean AI-driven insights from machine-generated telemetry, such as metrics, events, logs and traces. The new Cisco Data Fabric integrates business and machine data for AI processing, and the Machine Data Lake delivers a virtual repository for federated data sources.
The Cisco Data Fabric is a framework designed to unify and integrate data from multiple sources, such as the cloud, on-premises, or across different platforms like Snowflake or Splunk Indexes, among other sources. Built using Splunk Enterprise and Splunk Cloud Platform capabilities, the data fabric can apply AI and machine learning to data for deeper insights, and it federates and connects disparate data silos to create a single view for analytics and AI applications.
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“This is really the notion of weaving data together wherever it is, leading AI into it, and delivering a turnkey solution that allows customers to leverage this machine data in a way they already have been with Splunk, which is what Splunk does, but also with this new class of AI,” says Kamal Hathi, senior vice president and general manager of the Splunk business unit at Cisco.
“We’re talking about going through these little ponds and bundles of data and combining them as a set into one federated, distributed view, so we can start to scale and work with data, literally infinite scales, because data can be in all kinds of places,” Hathi says.
Cisco Data Fabric provides enterprise customers with capabilities such as:
- Time Series Foundation Model (TSFM): Provides 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.
- Intelligent data foundation: Transforms data across edge, cloud, and on-premises, including SecOps, ITOps, DevOps, and NetOps, into real-time, actionable insights.
- Borderless real-time search and analysis: Search and analyze data wherever it resides, federating across sources like Amazon S3, Apache Iceberg, Delta Lake (with Spark), Snowflake, and Microsoft Azure, while routing data to the appropriate storage or analytic engine for the workload.
- Flexible and open architecture: Adapts to any environment with open standards, plug-and-play integrations, and self-service tools – empowering innovation without limitations.
Cisco also announced Splunk Federated Search for Snowflake, an integration between Splunk and cloud-based data storage company Snowflake. By building this integration with Snowflake, Cisco aims to empower enterprise customers to analyze and correlate data across multiple platforms in one unified workflow. It also enables enterprises to simplify data management and gain deeper business and operational insights by combining machine and business data.
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“We take data that’s in a business database, like Snowflake, along with data that’s in S3, along with data that’s in a Splunk index, and combine it all into a distributed query to answer questions about what the business impact might be of some change in performance or other telemetry, which is very complicated to do, but we’re going to make it easy and make sure our customers have a holistic view of the business,” Hathi says.
For Splunk Cloud AWS commercial customers, Splunk Federated Search for Snowflake will become generally available in July 2026.
The Cisco Data Fabric is available today; additional data management, federation and AI features will become available through 2026. The TSFM will be listed on the open-source Hugging Face community in November, Cisco says.
