Cisco Unveils AI-Powered Data Fabric to Revolutionize Machine Data Management

Cisco Unveils Data Fabric to Revolutionize AI-Driven Machine Data Management

Cisco Systems Inc. has announced a significant leap forward in its artificial intelligence strategy with the introduction of the Cisco Data Fabric, powered by its recently acquired Splunk subsidiary. This new network architecture aims to unify fragmented machine data, positioning Cisco as a key player in the AI era's control plane1

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Source: CRN

Time Series Foundation Model: The Core of Data Fabric

At the heart of the Cisco Data Fabric lies the Time Series Foundation Model, an AI engine optimized for time-series analytics and forecasting. This model enables:

1. Anomaly detection
2. Forecasting
3. Automated root-cause analysis

These capabilities are designed to facilitate proactive operations and rapid incident response, transforming ingested data into actionable insights in real-time1

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Unified Intelligent Data Foundation and Borderless Real-Time Search

The Data Fabric incorporates a data normalization layer called the Unified Intelligent Data Foundation, which consolidates data flows from various sources, including security, operations, development, and networking. This consolidation aims to enable more efficient cost management1

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Atop this foundation, Cisco has implemented Borderless Real-Time Search, a feature that federates queries across multiple data sources such as AWS S3, Apache Iceberg, Databricks Delta Lake, Snowflake Data Cloud, and Microsoft Azure1

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Splunk Machine Data Lake and AI Integration

The Splunk Machine Data Lake serves as a persistent substrate for model training and enterprise analytics. In conjunction with the Splunk AI Toolkit and MCP server, it manages AI-native services for onboarding, monitoring, and self-healing operations1

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Addressing AI Adoption Challenges

Jeetu Patel, Cisco's President and Chief Product Officer, highlighted three main constraints facing AI adoption during his keynote at the Splunk .conf25 event:

Source: SiliconANGLE

1. Infrastructure demands: Agentic AI requires sustained, continuous IT capacity.
2. Trust deficit: The need for visibility and security in AI systems.
3. Data gap: The increasing demand for diverse data sources2

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Patel emphasized that Cisco and Splunk are actively working to address these challenges, positioning their combined technologies as critical infrastructure for the AI era2

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Integration and Future Prospects

Cisco has been rapidly integrating Splunk's capabilities into its product portfolio since the $28 billion acquisition in March 2024. Notable integrations include:

• Cisco AI Canvas with Splunk Cloud Platform
• Free ingestion of security data from Cisco firewall systems for Splunk customers2

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These developments mark a significant shift in Cisco's strategy, moving from a hardware-focused approach to positioning itself as an integrated platform spanning network, compute, security, and analytics1

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