---
title: 'Humanless Oncalls'
tags:
- example
- tags
- for the paper
authors:
- name: Tapasweni Pathak
orcid: 0000-0001-6286-3088
affiliation: "0"
Date: 19 July 2019
- name: Mayank Singh
orcid: 0000-0003-4108-424X
affiliation: "0"
Date: 19 July 2019
bibliography: paper.bib
---
After experiencing and watching people being on calls for few months, I created a package where oncalls might be human less. Recently this has become huge area for distributed computing researches. In this paper we publish 190GB of sample on call alarms that humans receive. We have picked the information from AWS Clusters, PagerDuty APIs, Elastic Search Watcher, HP Sitescope and many more alarm delivering service. We publish a poll where we asked companies in different areas on how they implement urgency and escalation for anything in their organisation. How much Pagers help them in implementing them, this can be any scenario. We have made machine learning implementation where the alarms response are learned from humans action. Any alarm goes in a pipeline with 0 and 1. The 0 machine are responded using multi fixes than 1 which are fixed using our implementation. As futher implementataion we publish a service where using our APIs you can make any of your Pagers response human less, we are just keeping out doctors pagers obviously.