Schedulers failing for ML service
We've now resolved the incident. Thank you for your patience.
We are currently experiencing an issue with scheduled notebooks on all clusters, which is causing the latest execution to get stuck in an incorrect status. This is preventing new schedules from being triggered as long as there is a running execution. Our team is working on resolving this issue as soon as possible, and we apologize for any inconvenience caused. We will keep you updated on the progress and appreciate your patience while we work to address this matter.
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