Evolving Cluster Management
summary
Meta replaces ad hoc per-task tweaks with a new stateful control service called the Twine job control plane that accepts high-level intents from Conveyor and autoscaling systems and reconciles them into task plans. The rewrite eliminates freeform task customization, cuts conflict between pushes and canaries, handles a 10-fold rise in job churn, already manages over 95% of services and enabled a scheduler feature that saved about 30% of GPU capacity for inference.
AI-written summary · about
chapters (8)
- 0:00Cluster management at Meta
- 2:31Key trends in cluster management
- 5:40Task customization today
- 8:30Challenges with customization
- 9:12Twine Job Control Plane
- 10:56Automations with JCP
- 13:04New features with JCP
- 14:29Future of cluster management
related talks
27mKeynote Panel: Future of Cluster Management
25mOpening Keynote
30mMgmt Config: The future of your autonomous datacenter
25m8 Million Tasks Daily: Driving Efficiency in Multi-Tenant Data Platforms at Ho...
22mAsynchronous Computing at Scale: Overview and Learning
18mReal-time adaptive controls for resilient container workloads
27mControl Plane for Large Mesh in a Heterogeneous Environment
27mEvolving and Scaling Ray for the Next Generation of AI Workloads
