TY - JOUR
T1 - Resource Management in Aurora Serverless
AU - Barnhart, Bradley
AU - Brooker, Marc
AU - Chinenkov, Daniil
AU - Hooper, Tony
AU - Im, Jihoun
AU - Jha, Prakash Chandra
AU - Kraska, Tim
AU - Kurakula, Ashok
AU - Kuznetsov, Alexey
AU - McAlister, Grant
AU - Muthukrishnan, Arjun
AU - Narayanan, Aravinthan
AU - Terry, Douglas
AU - Urgaonkar, Bhuvan
AU - Yan, Jiaming
N1 - Publisher Copyright:
© 2024, VLDB Endowment. All rights reserved.
PY - 2024
Y1 - 2024
N2 - Amazon Aurora Serverless is an on-demand, autoscaling configuration for Amazon Aurora with full MySQL and PostgreSQL compatibility. It automatically offers capacity scale-up/down (i.e., vertical scaling) based on a customer database application's needs. For customers with time-varying workloads, it offers cost savings compared to provisioned Aurora or other alternatives due to its agile and granular scaling and its usage-based charging model. This paper describes the key ideas underlying Aurora Serverless's resource management. To help meet its goals, Aurora Serverless adapts and fine tunes well-established ideas related to resource over-subscription; reactive control informed by recent measurements; distributed & hierarchical decision-making; and innovations in the DB engine, OS, and hypervisor for efficiency. Perhaps the most challenging goal is to offer a consistent resource elasticity experience while operating hosts at high degrees of utilization. Aurora Serverless implements several novel ideas for striking a balance between these opposing needs. Its technique for mapping workloads to hosts ensures that, in the common case, there is adequate spare capacity within a host to support fast scale-up for a workload. In the rare event this is not so, it live migrates workloads to ensure seamless scale-up. Its load distribution strategy is characterized by "unbalancing" of load across hosts to enable agile live migrations. Finally, it employs a token bucket-based rate regulation mechanism to prevent a growing workload from saturating its host faster than live migration-based remedial actions.
AB - Amazon Aurora Serverless is an on-demand, autoscaling configuration for Amazon Aurora with full MySQL and PostgreSQL compatibility. It automatically offers capacity scale-up/down (i.e., vertical scaling) based on a customer database application's needs. For customers with time-varying workloads, it offers cost savings compared to provisioned Aurora or other alternatives due to its agile and granular scaling and its usage-based charging model. This paper describes the key ideas underlying Aurora Serverless's resource management. To help meet its goals, Aurora Serverless adapts and fine tunes well-established ideas related to resource over-subscription; reactive control informed by recent measurements; distributed & hierarchical decision-making; and innovations in the DB engine, OS, and hypervisor for efficiency. Perhaps the most challenging goal is to offer a consistent resource elasticity experience while operating hosts at high degrees of utilization. Aurora Serverless implements several novel ideas for striking a balance between these opposing needs. Its technique for mapping workloads to hosts ensures that, in the common case, there is adequate spare capacity within a host to support fast scale-up for a workload. In the rare event this is not so, it live migrates workloads to ensure seamless scale-up. Its load distribution strategy is characterized by "unbalancing" of load across hosts to enable agile live migrations. Finally, it employs a token bucket-based rate regulation mechanism to prevent a growing workload from saturating its host faster than live migration-based remedial actions.
UR - http://www.scopus.com/inward/record.url?scp=85205286174&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85205286174&partnerID=8YFLogxK
U2 - 10.14778/3685800.3685825
DO - 10.14778/3685800.3685825
M3 - Conference article
AN - SCOPUS:85205286174
SN - 2150-8097
VL - 17
SP - 4038
EP - 4050
JO - Proceedings of the VLDB Endowment
JF - Proceedings of the VLDB Endowment
IS - 12
T2 - 50th International Conference on Very Large Data Bases, VLDB 2024
Y2 - 24 August 2024 through 29 August 2024
ER -