Workload autoscaling is widely used in public and private cloud systems to maintain stable service performance and save resources. However, it remains challenging to set the optimal resource limits and dynamically scale each workload at runtime. …
Multi-agent reinforcement learning (MARL) has primarily focused on solving a single task in isolation, while in practice the environment is often evolving, leaving many related tasks to be solved. In this paper, we investigate the benefits of …
Serverless Function-as-a-Service (FaaS) offers improved programmability for customers, yet it is not server-"less" and comes at the cost of more complex infrastructure management (e.g., resource provisioning and scheduling) for cloud providers. To …
Reinforcement learning (RL) has gained increasing popularity for resource management in cloud services such as serverless computing. As self-interested users compete for shared resources in a cluster, the multi-tenancy nature of serverless platforms …
Serverless Function-as-a-Service (FaaS) is an emerging cloud computing paradigm that frees application developers from infrastructure management tasks such as resource provisioning and scaling. To reduce the tail latency of functions and improve …