JobRunner
An open-source job scheduling and cluster operations tool that supports a task failure rescue mechanism. Through an MCP server, it exposes cluster status inspection, fault diagnosis and job recovery capabilities to AI agents.
Timeline (last 90 days)
The open-source JobRunner project has added an MCP (Model Context Protocol) server, enabling AI agents to interact directly with the JobRunner cluster.
The rescue mechanism refers to marking a task as pending recovery after it fails due to node failure, insufficient resources or timeout, and reallocating it to an available node for execution when conditions are met.
For Java task teams using JobRunner, the most direct value of this feature is shortening failure recovery time; the agent can complete diagnosis and rescheduling within seconds, reducing delays from manual intervention.
The feature originated from a real customer request: the customer wanted the agent to talk directly to the JobRunner cluster when a task failed, locate the problem and automatically recover the task.
JobRunner chose to build the documentation server first and the cluster operations server second, reflecting the ordering consideration of first letting the agent understand the tool, then letting the agent use the tool.
All Facts (5)
The rescue mechanism refers to marking a task as pending recovery after it fails due to node failure, insufficient resources or timeout, and reallocating it to an available node for execution when conditions are met.
50%UnverifiedFor Java task teams using JobRunner, the most direct value of this feature is shortening failure recovery time; the agent can complete diagnosis and rescheduling within seconds, reducing delays from manual intervention.
50%UnverifiedThe feature originated from a real customer request: the customer wanted the agent to talk directly to the JobRunner cluster when a task failed, locate the problem and automatically recover the task.
50%UnverifiedJobRunner chose to build the documentation server first and the cluster operations server second, reflecting the ordering consideration of first letting the agent understand the tool, then letting the agent use the tool.
50%UnverifiedThe open-source JobRunner project has added an MCP (Model Context Protocol) server, enabling AI agents to interact directly with the JobRunner cluster.
50%