Package, experimentation results, and other artifacts for our serverless computing performance modeling paper. Using the presented performance model, the serverless computing platform provider and their users can optimize their workload and configurations to adapt to each workload being executed on them. The presented model uses analytical model to calculate steady-state system characteristics.
Here is a list of different artifacts for the proposed model:
- Deployment Code for Experimental Data Collection
- Experimentation and Parsing Code
- Workload Profile Extraction Code
- Workloads and Results
- Model Implementation
- Python 3.7+
- PIP
To run the experiments, you need to install Knative on your cluster.
For details on the Knative installation, please visit its dedicated documentation.
Unless otherwise specified:
MIT (c) 2020 Nima Mahmoudi & Hamzeh Khazaei
You can find the paper with details of the proposed model in PACS lab website. You can use the following bibtex entry:
coming soon...