ABase: the Multi-Tenant NoSQL Serverless Database for Diverse and Dynamic Workloads in Large-scale Cloud Environments
Multi-tenant architectures enhance the elasticity and resource utilization of NoSQL databases by allowing multiple tenants to co-locate and share resources. However, in large-scale cloud environments, the diverse and dynamic nature of workloads poses significant challenges for multi-tenant NoSQL databases. Based on our practical observations, we have identified three crucial challenges: (1) the impact of caching on performance isolation, as cache hits alter request execution and resource consumption, leading to inaccurate traffic control; (2) the dynamic changes in traffic, with changes in tenant traffic trends causing throttling or resource wastage, and changes in access distribution causing hot key pressure or cache hit ratio drops; and (3) the imbalanced layout of data nodes due to tenants' diverse resource requirements, leading to low resource utilization. To address these challenges, we introduce ABase, a multi-tenant NoSQL serverless database developed at ByteDance. ABase introduces a two-layer caching mechanism with a cache-aware isolation mechanism to ensure accurate resource consumption estimates. Furthermore, ABase employs a predictive autoscaling policy to dynamically adjust resources in response to tenant traffic changes and a multi-resource rescheduling algorithm to balance resource utilization across data nodes. With these innovations, ABase has successfully served ByteDance's large-scale cloud environment, supporting a total workload that has achieved a peak QPS of over 13 billion and total storage exceeding 1 EB.
Authors
- Yanbin Chen
- Fuxin Jiang (ORCID: https://orcid.org/0000-0002-7522-061X)
- Lei Zhang (ORCID: https://orcid.org/0009-0004-1681-1956)
- Rong Kang (ORCID: https://orcid.org/0009-0005-8449-0223)
- Qingshuo Li (ORCID: https://orcid.org/0009-0006-2372-6797)
- Jianjun Chen (ORCID: https://orcid.org/0000-0002-3734-892X)
- Guangliang Zhao (ORCID: https://orcid.org/0009-0004-8853-3588)
- Tieying Zhang (ORCID: https://orcid.org/0009-0003-2250-5528)
- Miao Ma (ORCID: https://orcid.org/0009-0005-4274-5849)
- Juanjuan Li (ORCID: https://orcid.org/0000-0002-5323-5343)
- Ye Liu (ORCID: https://orcid.org/0009-0002-6601-4141)
Institutions
- CE Technologies (United Kingdom) (GB)
Publication Details
- Published
- 2025-06-17
- DOI
- https://doi.org/10.1145/3722212.3724426
- Citations
- 1
- Primary Topic
- Cloud Computing and Resource Management
- Type
- article
- Field-Weighted Citation Impact
- 3.25