Predictive Application Scaling with Prometheus and ML
Schireson, a New York City based data science and engineering firm, overcame a challenge in how to properly scale kubernetes services for their application stack. Consuming data from several tools i …
| Talk Title | Predictive Application Scaling with Prometheus and ML |
| Speakers | Chris Dutra (Director, Site Reliability Engineering, Schireson) |
| Conference | KubeCon + CloudNativeCon North America |
| Conf Tag | |
| Location | Seattle, WA, USA |
| Date | Dec 9-14, 2018 |
| URL | Talk Page |
| Slides | Talk Slides |
| Video | |
Schireson, a New York City based data science and engineering firm, overcame a challenge in how to properly scale kubernetes services for their application stack. Consuming data from several tools in the CNCF portfolio (such as Envoy and Prometheus), Schireson developed home-grown machine learning to actively predict the resource requirements for its services at any given time. The models act in a semi-supervised state to ensure the overall stability of their data science platform. This talk will illustrate the steps taken to construct the models, and offer suggestions to the larger DevOps community on how to implement Predictive Application Scaling in their organization.
