Name
Abstract | ||
|---|---|---|
Auto-scaling is the capability of Function as a Service systems, that supports dynamic scaling of the function instances according to the incoming load. Auto-scalers fire scaling events when a certain threshold is exceeded. However, if this threshold is not set properly, the function can suffer from under or over-provisioning. In this paper we introduce an autoscaling solution for compute intensive functions that calculates the scaling threshold according to the user needs and keeps the completion times predictable even when the function is scaled out. The scaling threshold is given by a simulator that determines the completion time distribution of the function for a given load. We also show which load-balancing algorithm is recommended to use for our auto-scaler. We compare our auto-scaler to existing ones implemented in open source serverless projects. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1109/NOMS54207.2022.9789777 | PROCEEDINGS OF THE IEEE/IFIP NETWORK OPERATIONS AND MANAGEMENT SYMPOSIUM 2022 |
Keywords | DocType | ISSN |
Auto-scaling, FaaS, Simulator, Load-balancing | Conference | 1542-1201 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| David Balla | 1 | 5 | 2.43 |
| Markosz Maliosz | 2 | 0 | 0.34 |
| Csaba Simon | 3 | 4 | 4.18 |