Even clustered, one must look at the specific event generating work loads, as well as monitoring the target systems for utilization.
<======> "Who do you think made the first stone spear? The Asperger guy. If you get rid of the autism genetics, there would be no Silicon Valley" Temple Grandin *Daemeon C.M. ReiydelleSan Francisco 1.415.501.0198London 44 020 8144 9872* On Thu, Mar 22, 2018 at 2:26 PM, Karan Pradhan <[email protected]> wrote: > Hi All, > > I had the following questions: > 1. > I was wondering if it is possible to have multiple Mesos masters as > elected masters in a Mesos cluster so that the load can be balanced amongst > the masters. Is there a way to achieve this? > In general, can there be a load balancer for the Mesos masters? > > 2. > I have seen spikes in the Mesos event queues while running spark SQL > workloads with multiple stages. So I was wondering what is a better way to > handle these scalability issues. I noticed that compute intensive machines > were able to deal with those workloads better. Is there a particular > hardware requirement or requirement for the number of masters for scaling a > Mesos cluster horizontally? After reading success stories which mention > that Mesos is deployed for ~10K machines, I was curious about the hardware > used and the number of masters in this case. > > It would be awesome if I could get some insight into these questions. > > Thanks, > Karan > >
