Hi Imesh, Here[1] is our proposal. We would share the design diagrams of our project soon.
On 26 May 2015 at 23:38, Supun Bhathiya <bhathiya...@cse.mrt.ac.lk> wrote: > Hi, > cc'ing to Dr. Dilum Bandara and Dr. Srinath Perera who would act as > internal and external mentors for our project respectively. > > > On 26 May 2015 at 23:23, Supun Bhathiya <bhathiya...@cse.mrt.ac.lk> wrote: > >> >> >> On 26 May 2015 at 09:35, Imesh Gunaratne <im...@apache.org> wrote: >> >>> Hi Bhathiya, >>> >>> It's good to see your proposal on improving current Autoscaling >>> functionality. This would definitely add value to Stratos. We could plan >>> and deliver this functionality in a future version. >>> >>> It would be great if you could prepare a implementation design for your >>> project proposal and discuss it in detail. >>> >>> Thanks >>> >>> On Mon, May 25, 2015 at 10:35 PM, Supun Bhathiya < >>> bhathiya...@cse.mrt.ac.lk> wrote: >>> >>>> Hi Imesh,Lakmal, Lahiru, Devs, >>>> >>>> This is intended to formalize the discussion we had on $subject, on >>>> behalf of our final year project, " *Workload and Resource Aware, >>>> Proactive Auto-scaling for PaaS Sytems* ". >>>> >>>> Our project is aimed at adding the following features and improvements >>>> to Apache Stratos. >>>> >>>> 1 - Improved Workload Prediction >>>> >>>> Currently Stratos autoscaler predict *immediate future load* based on >>>> current (in memory) health statistic. >>>> >>>> We propose to improve the auto-scaling mechanism to *predict workload >>>> for larger period of time by persisting and analyzing past statistics.* >>>> >>>> 2 - Smart resource allocation and deallocation >>>> >>>> Currently Stratos is not fully aware of all the resources provided by >>>> various IaaS and its pricing models. Therefore when scaling up, Stratos >>>> always spin-up an instance of same type. On the other hand kill a randomly >>>> selected instance when scaling down. >>>> >>>> We propose to improve this mechanism by selecting resources based on >>>> application workload patterns, available resource types and pricing of >>>> resources. For example allocating memory optimized instance would be cost >>>> effective for some application while some other application require high >>>> CPU but less memory. Also scale down mechanism can be improved by >>>> introducing features like "smart killing". >>>> >>>> 3 - Visualizing >>>> >>>> We propose to implement graph base view of >>>> >>>> - Predicted vs actual workloads >>>> - Optimized vs normal resource usage >>>> - Cost prediction >>>> >>>> We are glad to share our preliminary design concerns with the community >>>> and value your feedback and suggestions on our attempt. >>>> >>>> Thanks >>>> -Bhathiya >>>> >>> >>> >>> >>> -- >>> Imesh Gunaratne >>> >>> Senior Technical Lead, WSO2 >>> Committer & PMC Member, Apache Stratos >>> >> >> >
