Abstract: In one embodiment, a device presents information regarding an upstream machine learning workload and a downstream machine learning workload via a user interface. The device receives, via the user interface, a request to form a combined machine learning workload by connecting the upstream machine learning workload and the downstream machine learning workload. The device identifies, after receiving the request, a node associated with the upstream machine learning workload and a node associated with the downstream machine learning workload. The device forms the combined machine learning workload by configuring the node associated with the upstream machine learning workload to use one or more connector application programming interfaces to send data from the upstream machine learning workload to the node associated with the downstream machine learning workload for consumption.

Abstract: In one embodiment, a device provides, to a user interface, data representing a topology of a federated learning system configured across nodes in a computer network. Each node in the topology has an assigned role and is connected to at least one other node via a connector that is dependent on its assigned role. The device receives, via the user interface, a requested change to the topology of the federated learning system. The device selects, based on assigned roles of those nodes affected by the requested change to the topology of the federated learning system, code for execution by those nodes. The device implements the requested change to the topology of the federated learning system in part by sending the code selected by the device to those nodes affected by the requested change.

Abstract: In one embodiment, a device presents information regarding an upstream machine learning workload and a downstream machine learning workload via a user interface. The device receives, via the user interface, a request to form a combined machine learning workload by connecting the upstream machine learning workload and the downstream machine learning workload. The device identifies, after receiving the request, a node associated with the upstream machine learning workload and a node associated with the downstream machine learning workload. The device forms the combined machine learning workload by configuring the node associated with the upstream machine learning workload to use one or more connector application programming interfaces to send data from the upstream machine learning workload to the node associated with the downstream machine learning workload for consumption.