Server consolidation is critical for energy efficiency of cloud-scale computing. In production environments like Aliyun, which is one of the largest public cloud platforms in the world, server consolidation has several challenges. First, the widespread use of local storage remarkably increases the migration cost (time). Second, the resource utilization of service instances varies over time, which may result in migration oscillation. Third, server consolidation must follow practical constraints. E.g., instances can only be migrated within a maintenance window, and both the resource utilization and the number of instances on a server are bounded. This paper designs and implements C4, a Cost-Efficient Consolidating Service for Aliyun’s Cloud-Scale Computing, which Aliyun uses to consolidate servers. We analyze user pattern, resource utilization, and migration cost in Aliyun, showing that traditional utilization-based consolidation approaches cannot meet the needs in production environments, especially for the local-storage-based computing. This motivates us to propose the migration cost model, by which to select servers with the minimum migration time to release. We use the Worst-Fit heuristic to migrate instances to balance the load. Evaluation shows that C4 achieves cost-efficient, load-balanced, and oscillation-free consolidating service. We describe experience with over one year of C4 production deployment, lessons learned, and areas for future work.