RAS: Continuously Optimized Region-Wide Datacenter Resource Allocation

Capacity reservation is a common offering in public clouds and on-premise infrastructure. However, no prior work provides capacity reservation with SLO guarantees that takes into account random and correlated hardware failures, datacenter maintenance, and heterogeneous hardware. In this paper, we describe how Facebook's region-scale Resource Allowance System (RAS) addresses these issues and provides guaranteed capacity. RAS uses a capacity abstraction called reservation to represent a set of servers dynamically assigned to a logical cluster. We take a two-level approach to scale resource allocation to all datacenters in a region, where a mixed-integer-programming solver continuously optimizes server-to-reservation assignments off the critical path, and a traditional container allocator does real-time placement of containers on servers in a reservation. As a relatively new component of Facebook's 10-year old cluster manager Twine, RAS has been running in production for almost two years, continuously optimizing the allocation of millions of servers to thousands of reservations. We describe the design of RAS and share our experience of deploying it at scale.