But of course the actual memory requirement will largely depend on the type of job, statebackend , number of task slots etc
Production TM/JMs usually have much more resources allocated than 2gb/1cpu as you never want to run out of it :) Gyula On Sat, 21 Jan 2023 at 11:17, Gyula Fóra <gyula.f...@gmail.com> wrote: > Hi! > > I think the examples allocate too many resources by default and we should > reduce it in the yamls. > > 1gb memory and 0.5 cpu should be more than enough , we could probably get > away with even less for example purposes. > > Would you have time trying this out and maybe contributing this > improvement? :) > > Thanks > Gyula > > > On Fri, 20 Jan 2023 at 05:32, Lee Parayno <leepara...@gmail.com> wrote: > >> For application mode FlinkDeployments (maybe even session mode) in >> Kubernetes from the Flink Kubernetes Operator what is the absolute minimum >> amount of CPU and RAM that is required to run the JobManager and >> TaskManager processes? >> >> Some of the example deployment yaml examples have CPU set at 1 full vCPU >> and memory at 2GB (2048 MB). If you factor in JobManager HA, and 1 or more >> TaskManagers (not sure what is the bounding limit for these processes), you >> can be at 3 vCPU and 6 GB memory used just by the “Flink Infrastructure” >> not counting the Job pods. >> >> Has anyone seen a need to have more resources dedicated to these >> processes for some reason? Has anyone run it leaner than this (like with >> 0.5 vCPU and less than 1GB memory) in production? >> >> Comparing this to Google Cloud Platform and the Dataflow Runner, AFAIK >> the only resources utilized (that customers pay for) are the Job instances. >> >> Lee Parayno >> Sent from my iPhone > >
