Open Source Summit Europe, Aug. 27, 2025 — The Linux Foundation’s networking arm, LF Networking (LFN), has officially rolled out Essedum Release 1.0, a modular, open source platform designed to bring AI-native capabilities to networking applications.
Contributed earlier this year by Infosys, Essedum is built to help developers and operators connect the dots between data ingestion, pipeline orchestration, and AI model deployment—essentially laying the foundation for intelligent, autonomous networks.
“This release accelerates the integration of artificial intelligence into the fabric of our networks, enabling smarter, more agile systems,” said Arpit Joshipura, general manager of Networking, Edge, and IoT at the Linux Foundation.
Why Essedum Matters
Networking vendors and telecom operators have been experimenting with AI for years—optimizing traffic flows, automating maintenance, and predicting outages. But the challenge has been fragmentation: AI tools often sit outside core networking environments. Essedum aims to change that by creating a common, open source framework purpose-built for networking workloads.
Infosys contributed the seed code, while Essedum also integrates components from the LFN AI Task Force’s Data Sharing Platform and Thoth (Anuket). The goal: give the industry a collaborative foundation for domain-specific AI, rather than each vendor reinventing the wheel.
What’s in Essedum 1.0
The first release introduces baseline capabilities for AI-powered networking, including:
- Connections – Secure links between software systems to enable multi-environment data exchange.
- Datasets – Ingestion and management from buckets, MySQL, REST APIs, and more.
- Pipelines – Tools to build and manage training and inference pipelines, including model fine-tuning.
- Models – Centralized access to AI models across on-prem and cloud (AWS SageMaker, Azure ML, GCP Vertex AI).
- Endpoints – A single dashboard to view and manage connected APIs and model services.
- Adapters – Streamlined integration with external services without host reconfiguration.
- Remote Executor – Run pipelines or programs on remote VMs and servers for compute-heavy workloads.
What’s Next
Future enhancements already on the roadmap include:
- Docker and Helm-based deployment automation
- Support for PDF and Excel data ingestion
- Secrets management
- Enhanced role-based access control
- Expanded multi-cloud support
The Bigger Picture
The launch of Essedum comes as telecoms and enterprises alike wrestle with how to embed AI directly into their networking stacks. Proprietary solutions from Cisco, Juniper, and Nokia are already pushing toward self-healing, autonomous networks. Essedum’s open source angle could give operators a standards-based alternative—especially important in a market where multi-vendor environments dominate.
If successful, Essedum could become the Kubernetes of AI-powered networking: not the only option, but the neutral ground where innovation gets standardized.
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