Hi Marlon, Here is the link that I have created. https://docs.google.com/document/d/1qtFvg4-usT4D_1TDNBsQDFQGZIkH99ideYQ1T3HU9nY/edit?usp=sharing The draft is created under the GSoC proposal site under Apache foundation with the same title.
Thanks Pankaj On Mon, Mar 21, 2016 at 4:47 PM, Pierce, Marlon <[email protected]> wrote: > Hi Pankaj, > > I have some comments, but it would be easier if you created a proposal > draft in the GSOC site. The google doc option for your draft is better than > pointing to the Airavata wiki. Please make sure you give comment and > suggestion permissions. > > Marlon > > > From: Pankaj Saha <[email protected]> > Reply-To: "[email protected]" <[email protected]> > Date: Monday, March 21, 2016 at 11:16 AM > To: dev <[email protected]> > Subject: [GSoC Proposal] - Integrating Resource Information from Apache > Mesos with Apache Airavata’s Job Management Modules > > Hi Dev Team, > > Please review the following GSoC proposal that I plan to submit: > Title: Integrating Resource Information from Apache Mesos with Apache > Airavata’s Job Management Modules > > Abstract: > Apache Airavata provides gateway computing capability across clustered > environments for scientific users. It abstracts away the complexities of > submitting jobs to HPC platforms and provides users with an intuitive and > elegant web-based interface to submit jobs. Apache Mesos is a distributed > kernel that manages distributed computing resources as a single computer. > As Airavata is being extended to use Big Data and Cloud tools to launch > jobs in cloud environments, it needs to retrieve the resource and job > execution information from the Big Data framework back to the Apache portal > accessible to the end user. In this project we will develop code and > scripts to be integrated with the Airavata that will use the HTTP API of > Mesos to continuously fetch the complete resource and scheduling > information. This information can then be used by Airavata to dynamically > monitor and improve its job submission strategy in cloud environments such > as Jetstream. > > Introduction: > Apache Mesos provides HTTP API endpoints for scheduler, executor, internal > and admin related queries. To fetch information regarding a clustered > environment that is managed by the Mesos master, the API can be accessed > via curl requests over HTTP. The response to such requests will be received > as well formed json document. We will parse the json response and present > the information in the format desired. The retrieved information will > include resource usage, resource available for further jobs, job status, > time elapsed since the job started, etc. Airavata, in turn, will use this > information to determine the resource usage, performance of the jobs on a > job submission, rapid diagnosis on the health of the submitted jobs. > > We will use the observer pattern to continuously pull information from > Cloud and big Data Resource Managers, such as Apache Mesos, to Airavata. > > Any comment and suggestions would be very helpful. > > Thanks > Pankaj > >
