Hi All, After installing Heapster with the custom docker image [1], I was able to get historical data of 1 hour.
But these data have to be examined to understand which data can be used to detect the idle containers in Kubernetes cluster. So one approach would be to store these data periodically in an external database, examine the data and get which data would give the needed information to detect the idle containers. [1] https://hub.docker.com/r/malmee/malmee2heapster/ Thank you. On Tue, Apr 19, 2016 at 12:09 PM, Imesh Gunaratne <[email protected]> wrote: > > > On Tue, Apr 19, 2016 at 11:58 AM, Malmee Weerasinghe <[email protected]> > wrote: > >> Hi All, >> >> As there is a default database 'InfluxDB' that comes with 'Heapster' >> using the same database would be a better approach than an external >> database. >> > > Yes IMO it is better to use InfluxDB for this. > > Thanks > >> >> Default Heapster gives only up to 15 minutes of historical data for any >> Container. Would using a custom Heapster docker image be a better approach >> on this? >> >> In Heapster Repository, Heapster.go file contains these configurations. >> >> - stats_resolution (Deafult 1*time.Second) The resolution at which >> heapster will retain stats >> - sink_frequency (Default 10*time.Second) Frequency at which data >> will be pushed to sinks >> - cache_duration (Default 4*time.Minute) The total duration of the >> historical data that will be cached by heapster >> - use_model (Default true) When true, the internal model >> representation will be used >> - model_resolution (Default 1*time.Minute) The resolution of the >> time series stored in the model. >> - model_frequency (Default 145*time.Second) Frequency at which model >> will be updated. >> >> >> >> * 1 second < stats_resolution < model_resolution < model_frequency >> sink_frequency < cache_duration* >> >> If these configuration are changed as below, build a custom docker image >> and use that docker image instead of default Heapster image >> Heapster:canary, would that be a better approach on this? Or is there any >> other approaches for this? >> >> - stats_resolution 1*time.Hour >> - sink_frequency 2*time.Hour >> - cache_duration 3*time.Hour >> - use_model true >> - model_resolution 2*time.Hour >> - model_frequency 3*time.Hour >> >> I highly appreciate your suggestions regarding this. >> >> Thank you. >> >> On Fri, Apr 8, 2016 at 5:05 PM, Malmee Weerasinghe <[email protected]> >> wrote: >> >>> Hi All, >>> I have been working on detecting the idle containers in appcloud. I have >>> installed Heapster on Kubernetes and Heapster Metric Model gives only up to >>> 15 minutes of historical data for any Container. >>> >>> I have tried adding the flag "-model_resolution" and making it more >>> than 30s, but the flag can not be set as it gives errors when installing >>> the replication controller of heapster. >>> >>> Then I have tried adding "start=X&end=Y" to the end of the API >>> endpoint, but it gives the same response that gives without adding that >>> part. >>> >>> AFAIU if the database of heapster, influxdb stores all the data from 30s >>> to 30s, it needs a huge storage. Therefore it stores only up to 15 minutes >>> of historical data at any moment. >>> >>> To find the idle containers of appcloud, the resource usage details of >>> the containers have to be stored for a longer period than 15 minutes. One >>> of the approaches would be to use another database and store the resource >>> usage details of containers checking whether the container has been idle >>> for a period of 5 days. >>> >>> I highly appreciate your suggestions on the approaches that can be taken >>> regarding this. >>> >>> Thank you. >>> >>> -- >>> Malmee Weerasinghe >>> WSO2 Intern >>> mobile : (+94)* 71 7601905* | email : <[email protected]> >>> [email protected] >>> >> >> >> >> -- >> Malmee Weerasinghe >> WSO2 Intern >> mobile : (+94)* 71 7601905* | email : <[email protected]> >> [email protected] >> > > > > -- > *Imesh Gunaratne* > Senior Technical Lead > WSO2 Inc: http://wso2.com > T: +94 11 214 5345 M: +94 77 374 2057 > W: http://imesh.io > Lean . Enterprise . Middleware > > -- Malmee Weerasinghe WSO2 Intern mobile : (+94)* 71 7601905* | email : <[email protected]> [email protected]
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