Using the JON Remote API    [and why you might want to]            Andy Redhead  (andy.redhead@advanced365.com)
JON Deployment     Production Server (1)                Production Server (x)                    JON                      ...
The Goal - View Behaviour of Multiple              Machines
Approach (1/2) – Client Appmachine             datetime                        low      av        maxservername1:1099    2...
Approach (2/2) - R http://www.r-project.org/#Read datasetajpConnActiveThreads <- read.table(dataSetFile, header=TRUE, sep=...
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Using the JON Remote API by Andy Redhead

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Lightning talk by Andy Redhead presented on the 17th of October at JBoss jBPM JBUG event.
More info about the event: http://www.meetup.com/JBoss-User-Group/events/34561072/

Published in: Technology, Education
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Using the JON Remote API by Andy Redhead

  1. 1. Using the JON Remote API [and why you might want to] Andy Redhead (andy.redhead@advanced365.com)
  2. 2. JON Deployment Production Server (1) Production Server (x) JON JON JBoss JBoss Agent Agent All the Remote JON Remote other JON ClientDatabase Java API RHQ bits App JON Server Client
  3. 3. The Goal - View Behaviour of Multiple Machines
  4. 4. Approach (1/2) – Client Appmachine datetime low av maxservername1:1099 2011-09-01T00:00:00.000+01:00 31.0 31.0 31.0servername2:1099 2011-09-01T00:05:00.000+01:00 NaN NaN NaNhttp://docs.redhat.com/docs/en-US/JBoss_Operations_Network/2.4/html/CLI_Guide/index.htmlhttp://docs.redhat.com/docs/en-US/JBoss_Operations_Network/2.4/html/API_Guides/client-api/index.html
  5. 5. Approach (2/2) - R http://www.r-project.org/#Read datasetajpConnActiveThreads <- read.table(dataSetFile, header=TRUE, sep="")ajpConnActiveThreads$datetime <- as.POSIXct(ajpConnActiveThreads$datetime, tz="", %Y-%m-%dT%H:%M:%OS)#Calculate “Trimmed” MeanallMachineTrimmedMean <- apply(justNumbers, 1, mean, trim=0.1)#Draw Graphjpeg(outputGraphFileName) plot(threadActiveXRange, threadActiveYRange, type="n", …, col.lab="darkblue") axis.POSIXct(1, at=seq(r[1], r[2], by="hour"), format="%H:%M", las=2) axis(2, at=yAxisAt, las=2) lines(finalData$datetime, finalData[[dataIndex]], col="red") lines(finalData$datetime, allMachineTrimmedMean, col="blue")dev.off()
  6. 6. Thanks for Listening 
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