Help with JNLP-agent lost connections, Nothing on Google helps.

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Help with JNLP-agent lost connections, Nothing on Google helps.

Ruslan Zasukhin
Hi Everbody

I am fighting with this about 2 weeks and so far no any success. 
I have read dozen answers on internet about similar troubles - nothing helps.

I have upgrade today Java on master and all windows-slave machines to latest 8_211, not helps.
Jenkins also is latest 2.183 and all plugins up to date.

** So, problem is that windows-slave machines SOMETIMES get closed JNLP connection.
The same machines sometimes are able to execute job with success.

** May be jenkins-gurus can check Exception-stack below and point where to search?

** This failure happens at any time at any place of a job. 
** MASTER computer is Mac OS X
** We have around few windows computers (mostly VM on virtual Box,) 
    few Linux machines (also virtual bog) and few Macs - physical macs are used.

** Linux and Mac works fine.
** For years Windows also was fine, glitches have started about 2 weeks ago,
    On that day we was yet on 2.163


=========================
FATAL: command execution failed
java.nio.channels.ClosedChannelException
	at org.jenkinsci.remoting.protocol.NetworkLayer.onRecvClosed(NetworkLayer.java:154)
	at org.jenkinsci.remoting.protocol.impl.NIONetworkLayer.ready(NIONetworkLayer.java:179)
	at org.jenkinsci.remoting.protocol.IOHub$OnReady.run(IOHub.java:795)
	at jenkins.util.ContextResettingExecutorService$1.run(ContextResettingExecutorService.java:28)
	at jenkins.security.ImpersonatingExecutorService$1.run(ImpersonatingExecutorService.java:59)
	at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
	at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
	at java.lang.Thread.run(Thread.java:745)
Caused: java.io.IOException: Backing channel 'JNLP4-connect connection from 192.168.2.160/192.168.2.160:1112' is disconnected.
	at hudson.remoting.RemoteInvocationHandler.channelOrFail(RemoteInvocationHandler.java:214)
	at hudson.remoting.RemoteInvocationHandler.invoke(RemoteInvocationHandler.java:283)
	at com.sun.proxy.$Proxy81.isAlive(Unknown Source)
	at hudson.Launcher$RemoteLauncher$ProcImpl.isAlive(Launcher.java:1150)
	at hudson.Launcher$RemoteLauncher$ProcImpl.join(Launcher.java:1142)
	at hudson.tasks.CommandInterpreter.join(CommandInterpreter.java:155)
	at hudson.tasks.CommandInterpreter.perform(CommandInterpreter.java:109)
	at hudson.tasks.CommandInterpreter.perform(CommandInterpreter.java:66)
	at hudson.tasks.BuildStepMonitor$1.perform(BuildStepMonitor.java:20)
	at hudson.model.AbstractBuild$AbstractBuildExecution.perform(AbstractBuild.java:741)
	at hudson.model.Build$BuildExecution.build(Build.java:206)
	at hudson.model.Build$BuildExecution.doRun(Build.java:163)
	at hudson.model.AbstractBuild$AbstractBuildExecution.run(AbstractBuild.java:504)
	at hudson.model.Run.execute(Run.java:1818)
	at hudson.model.FreeStyleBuild.run(FreeStyleBuild.java:43)
	at hudson.model.ResourceController.execute(ResourceController.java:97)
	at hudson.model.Executor.run(Executor.java:429)
FATAL: Unable to delete script file C:\Users\Ruslan\AppData\Local\Temp\jenkins4887328775441465037.bat
java.nio.channels.ClosedChannelException
	at org.jenkinsci.remoting.protocol.NetworkLayer.onRecvClosed(NetworkLayer.java:154)
	at org.jenkinsci.remoting.protocol.impl.NIONetworkLayer.ready(NIONetworkLayer.java:179)
	at org.jenkinsci.remoting.protocol.IOHub$OnReady.run(IOHub.java:795)
	at jenkins.util.ContextResettingExecutorService$1.run(ContextResettingExecutorService.java:28)
	at jenkins.security.ImpersonatingExecutorService$1.run(ImpersonatingExecutorService.java:59)
	at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
	at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
	at java.lang.Thread.run(Thread.java:745)
Caused: hudson.remoting.ChannelClosedException: Channel "unknown": Remote call on JNLP4-connect connection from 192.168.2.160/192.168.2.160:1112 failed. The channel is closing down or has closed down
	at hudson.remoting.Channel.call(Channel.java:950)
	at hudson.FilePath.act(FilePath.java:1072)
	at hudson.FilePath.act(FilePath.java:1061)
	at hudson.FilePath.delete(FilePath.java:1542)
	at hudson.tasks.CommandInterpreter.perform(CommandInterpreter.java:123)
	at hudson.tasks.CommandInterpreter.perform(CommandInterpreter.java:66)
	at hudson.tasks.BuildStepMonitor$1.perform(BuildStepMonitor.java:20)
	at hudson.model.AbstractBuild$AbstractBuildExecution.perform(AbstractBuild.java:741)
	at hudson.model.Build$BuildExecution.build(Build.java:206)
	at hudson.model.Build$BuildExecution.doRun(Build.java:163)
	at hudson.model.AbstractBuild$AbstractBuildExecution.run(AbstractBuild.java:504)
	at hudson.model.Run.execute(Run.java:1818)
	at hudson.model.FreeStyleBuild.run(FreeStyleBuild.java:43)
	at hudson.model.ResourceController.execute(ResourceController.java:97)
	at hudson.model.Executor.run(Executor.java:429)



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Re: Help with JNLP-agent lost connections, Nothing on Google helps.

tlnarayana
Eagerly , I'm waiting for the root cause and resolution ....

On Thursday, July 4, 2019 at 7:47:00 PM UTC+5:30 ruslan_zasukhin wrote:
Hi Everbody

I am fighting with this about 2 weeks and so far no any success. 
I have read dozen answers on internet about similar troubles - nothing helps.

I have upgrade today Java on master and all windows-slave machines to latest 8_211, not helps.
Jenkins also is latest 2.183 and all plugins up to date.

** So, problem is that windows-slave machines SOMETIMES get closed JNLP connection.
The same machines sometimes are able to execute job with success.

** May be jenkins-gurus can check Exception-stack below and point where to search?

** This failure happens at any time at any place of a job. 
** MASTER computer is Mac OS X
** We have around few windows computers (mostly VM on virtual Box,) 
    few Linux machines (also virtual bog) and few Macs - physical macs are used.

** Linux and Mac works fine.
** For years Windows also was fine, glitches have started about 2 weeks ago,
    On that day we was yet on 2.163


=========================
FATAL: command execution failed
java.nio.channels.ClosedChannelException
	at org.jenkinsci.remoting.protocol.NetworkLayer.onRecvClosed(NetworkLayer.java:154)
	at org.jenkinsci.remoting.protocol.impl.NIONetworkLayer.ready(NIONetworkLayer.java:179)
	at org.jenkinsci.remoting.protocol.IOHub$OnReady.run(IOHub.java:795)
	at jenkins.util.ContextResettingExecutorService$1.run(ContextResettingExecutorService.java:28)
	at jenkins.security.ImpersonatingExecutorService$1.run(ImpersonatingExecutorService.java:59)
	at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
	at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
	at java.lang.Thread.run(Thread.java:745)
Caused: java.io.IOException: Backing channel 'JNLP4-connect connection from 192.168.2.160/192.168.2.160:1112' is disconnected.
	at hudson.remoting.RemoteInvocationHandler.channelOrFail(RemoteInvocationHandler.java:214)
	at hudson.remoting.RemoteInvocationHandler.invoke(RemoteInvocationHandler.java:283)
	at com.sun.proxy.$Proxy81.isAlive(Unknown Source)
	at hudson.Launcher$RemoteLauncher$ProcImpl.isAlive(Launcher.java:1150)
	at hudson.Launcher$RemoteLauncher$ProcImpl.join(Launcher.java:1142)
	at hudson.tasks.CommandInterpreter.join(CommandInterpreter.java:155)
	at hudson.tasks.CommandInterpreter.perform(CommandInterpreter.java:109)
	at hudson.tasks.CommandInterpreter.perform(CommandInterpreter.java:66)
	at hudson.tasks.BuildStepMonitor$1.perform(BuildStepMonitor.java:20)
	at hudson.model.AbstractBuild$AbstractBuildExecution.perform(AbstractBuild.java:741)
	at hudson.model.Build$BuildExecution.build(Build.java:206)
	at hudson.model.Build$BuildExecution.doRun(Build.java:163)
	at hudson.model.AbstractBuild$AbstractBuildExecution.run(AbstractBuild.java:504)
	at hudson.model.Run.execute(Run.java:1818)
	at hudson.model.FreeStyleBuild.run(FreeStyleBuild.java:43)
	at hudson.model.ResourceController.execute(ResourceController.java:97)
	at hudson.model.Executor.run(Executor.java:429)
FATAL: Unable to delete script file C:\Users\Ruslan\AppData\Local\Temp\jenkins4887328775441465037.bat
java.nio.channels.ClosedChannelException
	at org.jenkinsci.remoting.protocol.NetworkLayer.onRecvClosed(NetworkLayer.java:154)
	at org.jenkinsci.remoting.protocol.impl.NIONetworkLayer.ready(NIONetworkLayer.java:179)
	at org.jenkinsci.remoting.protocol.IOHub$OnReady.run(IOHub.java:795)
	at jenkins.util.ContextResettingExecutorService$1.run(ContextResettingExecutorService.java:28)
	at jenkins.security.ImpersonatingExecutorService$1.run(ImpersonatingExecutorService.java:59)
	at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
	at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
	at java.lang.Thread.run(Thread.java:745)
Caused: hudson.remoting.ChannelClosedException: Channel "unknown": Remote call on JNLP4-connect connection from 192.168.2.160/192.168.2.160:1112 failed. The channel is closing down or has closed down
	at hudson.remoting.Channel.call(Channel.java:950)
	at hudson.FilePath.act(FilePath.java:1072)
	at hudson.FilePath.act(FilePath.java:1061)
	at hudson.FilePath.delete(FilePath.java:1542)
	at hudson.tasks.CommandInterpreter.perform(CommandInterpreter.java:123)
	at hudson.tasks.CommandInterpreter.perform(CommandInterpreter.java:66)
	at hudson.tasks.BuildStepMonitor$1.perform(BuildStepMonitor.java:20)
	at hudson.model.AbstractBuild$AbstractBuildExecution.perform(AbstractBuild.java:741)
	at hudson.model.Build$BuildExecution.build(Build.java:206)
	at hudson.model.Build$BuildExecution.doRun(Build.java:163)
	at hudson.model.AbstractBuild$AbstractBuildExecution.run(AbstractBuild.java:504)
	at hudson.model.Run.execute(Run.java:1818)
	at hudson.model.FreeStyleBuild.run(FreeStyleBuild.java:43)
	at hudson.model.ResourceController.execute(ResourceController.java:97)
	at hudson.model.Executor.run(Executor.java:429)



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Re: Help with JNLP-agent lost connections, Nothing on Google helps.

Björn Pedersen
Current Weekly ( that is what it seems you are using) is 2.257 now. There were some changes to remoting, so make sure  the agent.jar on the the client machines is up-to-date  as well. 

And how do you connect to the windows clients? Running it as a windows service, manually starting it , ssh ???

Björn

[hidden email] schrieb am Dienstag, 22. September 2020 um 09:00:07 UTC+2:
Eagerly , I'm waiting for the root cause and resolution ....

On Thursday, July 4, 2019 at 7:47:00 PM UTC+5:30 ruslan_zasukhin wrote:
Hi Everbody

I am fighting with this about 2 weeks and so far no any success. 
I have read dozen answers on internet about similar troubles - nothing helps.

I have upgrade today Java on master and all windows-slave machines to latest 8_211, not helps.
Jenkins also is latest 2.183 and all plugins up to date.

** So, problem is that windows-slave machines SOMETIMES get closed JNLP connection.
The same machines sometimes are able to execute job with success.

** May be jenkins-gurus can check Exception-stack below and point where to search?

** This failure happens at any time at any place of a job. 
** MASTER computer is Mac OS X
** We have around few windows computers (mostly VM on virtual Box,) 
    few Linux machines (also virtual bog) and few Macs - physical macs are used.

** Linux and Mac works fine.
** For years Windows also was fine, glitches have started about 2 weeks ago,
    On that day we was yet on 2.163


=========================
FATAL: command execution failed
java.nio.channels.ClosedChannelException
	at org.jenkinsci.remoting.protocol.NetworkLayer.onRecvClosed(NetworkLayer.java:154)
	at org.jenkinsci.remoting.protocol.impl.NIONetworkLayer.ready(NIONetworkLayer.java:179)
	at org.jenkinsci.remoting.protocol.IOHub$OnReady.run(IOHub.java:795)
	at jenkins.util.ContextResettingExecutorService$1.run(ContextResettingExecutorService.java:28)
	at jenkins.security.ImpersonatingExecutorService$1.run(ImpersonatingExecutorService.java:59)
	at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
	at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
	at java.lang.Thread.run(Thread.java:745)
Caused: java.io.IOException: Backing channel 'JNLP4-connect connection from 192.168.2.160/192.168.2.160:1112' is disconnected.
	at hudson.remoting.RemoteInvocationHandler.channelOrFail(RemoteInvocationHandler.java:214)
	at hudson.remoting.RemoteInvocationHandler.invoke(RemoteInvocationHandler.java:283)
	at com.sun.proxy.$Proxy81.isAlive(Unknown Source)
	at hudson.Launcher$RemoteLauncher$ProcImpl.isAlive(Launcher.java:1150)
	at hudson.Launcher$RemoteLauncher$ProcImpl.join(Launcher.java:1142)
	at hudson.tasks.CommandInterpreter.join(CommandInterpreter.java:155)
	at hudson.tasks.CommandInterpreter.perform(CommandInterpreter.java:109)
	at hudson.tasks.CommandInterpreter.perform(CommandInterpreter.java:66)
	at hudson.tasks.BuildStepMonitor$1.perform(BuildStepMonitor.java:20)
	at hudson.model.AbstractBuild$AbstractBuildExecution.perform(AbstractBuild.java:741)
	at hudson.model.Build$BuildExecution.build(Build.java:206)
	at hudson.model.Build$BuildExecution.doRun(Build.java:163)
	at hudson.model.AbstractBuild$AbstractBuildExecution.run(AbstractBuild.java:504)
	at hudson.model.Run.execute(Run.java:1818)
	at hudson.model.FreeStyleBuild.run(FreeStyleBuild.java:43)
	at hudson.model.ResourceController.execute(ResourceController.java:97)
	at hudson.model.Executor.run(Executor.java:429)
FATAL: Unable to delete script file C:\Users\Ruslan\AppData\Local\Temp\jenkins4887328775441465037.bat
java.nio.channels.ClosedChannelException
	at org.jenkinsci.remoting.protocol.NetworkLayer.onRecvClosed(NetworkLayer.java:154)
	at org.jenkinsci.remoting.protocol.impl.NIONetworkLayer.ready(NIONetworkLayer.java:179)
	at org.jenkinsci.remoting.protocol.IOHub$OnReady.run(IOHub.java:795)
	at jenkins.util.ContextResettingExecutorService$1.run(ContextResettingExecutorService.java:28)
	at jenkins.security.ImpersonatingExecutorService$1.run(ImpersonatingExecutorService.java:59)
	at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
	at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
	at java.lang.Thread.run(Thread.java:745)
Caused: hudson.remoting.ChannelClosedException: Channel "unknown": Remote call on JNLP4-connect connection from 192.168.2.160/192.168.2.160:1112 failed. The channel is closing down or has closed down
	at hudson.remoting.Channel.call(Channel.java:950)
	at hudson.FilePath.act(FilePath.java:1072)
	at hudson.FilePath.act(FilePath.java:1061)
	at hudson.FilePath.delete(FilePath.java:1542)
	at hudson.tasks.CommandInterpreter.perform(CommandInterpreter.java:123)
	at hudson.tasks.CommandInterpreter.perform(CommandInterpreter.java:66)
	at hudson.tasks.BuildStepMonitor$1.perform(BuildStepMonitor.java:20)
	at hudson.model.AbstractBuild$AbstractBuildExecution.perform(AbstractBuild.java:741)
	at hudson.model.Build$BuildExecution.build(Build.java:206)
	at hudson.model.Build$BuildExecution.doRun(Build.java:163)
	at hudson.model.AbstractBuild$AbstractBuildExecution.run(AbstractBuild.java:504)
	at hudson.model.Run.execute(Run.java:1818)
	at hudson.model.FreeStyleBuild.run(FreeStyleBuild.java:43)
	at hudson.model.ResourceController.execute(ResourceController.java:97)
	at hudson.model.Executor.run(Executor.java:429)



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Re: Help with JNLP-agent lost connections, Nothing on Google helps.

tlnarayana
Here is my current setup

Jenkins ver. 2.190.1 hosted on Windows 10 VM (ie deployed jenkins war file in apache tomcat container which run as windows service)
Same version of java 1.8 has been installed in both master and slave
Slave configuration like below , run from bat file
<img 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" alt="" data-iml="296273.9750000001">

Please find log from tomcat

10-Dec-2020 07:33:53.506 INFO [IOHub#1: Worker[channel:java.nio.channels.SocketChannel[connected local=/172.18.52.73:62525 remote=10.115.65.23/10.115.65.23:58973]] / Computer.threadPoolForRemoting [#475718]] jenkins.slaves.DefaultJnlpSlaveReceiver.channelClosed IOHub#1: Worker[channel:java.nio.channels.SocketChannel[connected local=/172.18.52.73:62525 remote=10.115.65.23/10.115.65.23:58973]] / Computer.threadPoolForRemoting [#475718] for Win10_DCP_JEN_10 terminated: java.nio.channels.ClosedChannelException
10-Dec-2020 07:33:53.551 INFO [IOHub#1: Worker[channel:java.nio.channels.SocketChannel[connected local=/172.18.52.73:62525 remote=10.115.65.25/10.115.65.25:55324]] / Computer.threadPoolForRemoting [#475718]] jenkins.slaves.DefaultJnlpSlaveReceiver.channelClosed IOHub#1: Worker[channel:java.nio.channels.SocketChannel[connected local=/172.18.52.73:62525 remote=10.115.65.25/10.115.65.25:55324]] / Computer.threadPoolForRemoting [#475718] for Win10_DCP_JEN_12 terminated: java.nio.channels.ClosedChannelException
10-Dec-2020 07:33:54.014 INFO [IOHub#1: Worker[channel:java.nio.channels.SocketChannel[connected local=/172.18.52.73:62525 remote=USRDCA02QAJEN03.user.ngahr.int/10.0.83.74:52189]] / Computer.threadPoolForRemoting [#475718]] jenkins.slaves.DefaultJnlpSlaveReceiver.channelClosed IOHub#1: Worker[channel:java.nio.channels.SocketChannel[connected local=/172.18.52.73:62525 remote=USRDCA02QAJEN03.user.ngahr.int/10.0.83.74:52189]] / Computer.threadPoolForRemoting [#475718] for Win10_DCA_JEN_03 terminated: java.nio.channels.ClosedChannelException
10-Dec-2020 07:33:54.293 INFO [IOHub#1: Worker[channel:java.nio.channels.SocketChannel[connected local=/172.18.52.73:62525 remote=MACHINE02QAJEN02.user.ngahr.int/10.0.83.73:55089]] / Computer.threadPoolForRemoting [#475718]] jenkins.slaves.DefaultJnlpSlaveReceiver.channelClosed IOHub#1: Worker[channel:java.nio.channels.SocketChannel[connected local=/172.18.52.73:62525 remote=MACHINE02QAJEN02.user.ngahr.int/10.0.83.73:55089]] / Computer.threadPoolForRemoting [#475718] for Win10_DCA_JEN_02 terminated: java.nio.channels.ClosedChannelException
10-Dec-2020 07:33:54.670 INFO [IOHub#1: Worker[channel:java.nio.channels.SocketChannel[connected local=/172.18.52.73:62525 remote=MACHINE02QAJEN01.user.ngahr.int/10.0.83.72:52038]] / Computer.threadPoolForRemoting [#475648]] jenkins.slaves.DefaultJnlpSlaveReceiver.channelClosed IOHub#1: Worker[channel:java.nio.channels.SocketChannel[connected local=/172.18.52.73:62525 remote=MACHINE02QAJEN01.user.ngahr.int/10.0.83.72:52038]] / Computer.threadPoolForRemoting [#475648] for Win10_DCA_JEN_01 terminated: java.nio.channels.ClosedChannelException
10-Dec-2020 07:33:56.381 INFO [IOHub#1: Worker[channel:java.nio.channels.SocketChannel[connected local=/172.18.52.73:62525 remote=MACHINE02QAJEN07.user.ngahr.int/10.0.83.26:61456]] / Computer.threadPoolForRemoting [#475728]] jenkins.slaves.DefaultJnlpSlaveReceiver.channelClosed IOHub#1: Worker[channel:java.nio.channels.SocketChannel[connected local=/172.18.52.73:62525 remote=MACHINE02QAJEN07.user.ngahr.int/10.0.83.26:61456]] / Computer.threadPoolForRemoting [#475728] for Win10_DCA_JEN_07 terminated: java.nio.channels.ClosedChannelException


On Tuesday, September 22, 2020 at 4:35:29 PM UTC+5:30 [hidden email] wrote:
Current Weekly ( that is what it seems you are using) is 2.257 now. There were some changes to remoting, so make sure  the agent.jar on the the client machines is up-to-date  as well. 

And how do you connect to the windows clients? Running it as a windows service, manually starting it , ssh ???

Björn

[hidden email] schrieb am Dienstag, 22. September 2020 um 09:00:07 UTC+2:
Eagerly , I'm waiting for the root cause and resolution ....

On Thursday, July 4, 2019 at 7:47:00 PM UTC+5:30 ruslan_zasukhin wrote:
Hi Everbody

I am fighting with this about 2 weeks and so far no any success. 
I have read dozen answers on internet about similar troubles - nothing helps.

I have upgrade today Java on master and all windows-slave machines to latest 8_211, not helps.
Jenkins also is latest 2.183 and all plugins up to date.

** So, problem is that windows-slave machines SOMETIMES get closed JNLP connection.
The same machines sometimes are able to execute job with success.

** May be jenkins-gurus can check Exception-stack below and point where to search?

** This failure happens at any time at any place of a job. 
** MASTER computer is Mac OS X
** We have around few windows computers (mostly VM on virtual Box,) 
    few Linux machines (also virtual bog) and few Macs - physical macs are used.

** Linux and Mac works fine.
** For years Windows also was fine, glitches have started about 2 weeks ago,
    On that day we was yet on 2.163


=========================
FATAL: command execution failed
java.nio.channels.ClosedChannelException
	at org.jenkinsci.remoting.protocol.NetworkLayer.onRecvClosed(NetworkLayer.java:154)
	at org.jenkinsci.remoting.protocol.impl.NIONetworkLayer.ready(NIONetworkLayer.java:179)
	at org.jenkinsci.remoting.protocol.IOHub$OnReady.run(IOHub.java:795)
	at jenkins.util.ContextResettingExecutorService$1.run(ContextResettingExecutorService.java:28)
	at jenkins.security.ImpersonatingExecutorService$1.run(ImpersonatingExecutorService.java:59)
	at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
	at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
	at java.lang.Thread.run(Thread.java:745)
Caused: java.io.IOException: Backing channel 'JNLP4-connect connection from 192.168.2.160/192.168.2.160:1112' is disconnected.
	at hudson.remoting.RemoteInvocationHandler.channelOrFail(RemoteInvocationHandler.java:214)
	at hudson.remoting.RemoteInvocationHandler.invoke(RemoteInvocationHandler.java:283)
	at com.sun.proxy.$Proxy81.isAlive(Unknown Source)
	at hudson.Launcher$RemoteLauncher$ProcImpl.isAlive(Launcher.java:1150)
	at hudson.Launcher$RemoteLauncher$ProcImpl.join(Launcher.java:1142)
	at hudson.tasks.CommandInterpreter.join(CommandInterpreter.java:155)
	at hudson.tasks.CommandInterpreter.perform(CommandInterpreter.java:109)
	at hudson.tasks.CommandInterpreter.perform(CommandInterpreter.java:66)
	at hudson.tasks.BuildStepMonitor$1.perform(BuildStepMonitor.java:20)
	at hudson.model.AbstractBuild$AbstractBuildExecution.perform(AbstractBuild.java:741)
	at hudson.model.Build$BuildExecution.build(Build.java:206)
	at hudson.model.Build$BuildExecution.doRun(Build.java:163)
	at hudson.model.AbstractBuild$AbstractBuildExecution.run(AbstractBuild.java:504)
	at hudson.model.Run.execute(Run.java:1818)
	at hudson.model.FreeStyleBuild.run(FreeStyleBuild.java:43)
	at hudson.model.ResourceController.execute(ResourceController.java:97)
	at hudson.model.Executor.run(Executor.java:429)
FATAL: Unable to delete script file C:\Users\Ruslan\AppData\Local\Temp\jenkins4887328775441465037.bat
java.nio.channels.ClosedChannelException
	at org.jenkinsci.remoting.protocol.NetworkLayer.onRecvClosed(NetworkLayer.java:154)
	at org.jenkinsci.remoting.protocol.impl.NIONetworkLayer.ready(NIONetworkLayer.java:179)
	at org.jenkinsci.remoting.protocol.IOHub$OnReady.run(IOHub.java:795)
	at jenkins.util.ContextResettingExecutorService$1.run(ContextResettingExecutorService.java:28)
	at jenkins.security.ImpersonatingExecutorService$1.run(ImpersonatingExecutorService.java:59)
	at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
	at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
	at java.lang.Thread.run(Thread.java:745)
Caused: hudson.remoting.ChannelClosedException: Channel "unknown": Remote call on JNLP4-connect connection from 192.168.2.160/192.168.2.160:1112 failed. The channel is closing down or has closed down
	at hudson.remoting.Channel.call(Channel.java:950)
	at hudson.FilePath.act(FilePath.java:1072)
	at hudson.FilePath.act(FilePath.java:1061)
	at hudson.FilePath.delete(FilePath.java:1542)
	at hudson.tasks.CommandInterpreter.perform(CommandInterpreter.java:123)
	at hudson.tasks.CommandInterpreter.perform(CommandInterpreter.java:66)
	at hudson.tasks.BuildStepMonitor$1.perform(BuildStepMonitor.java:20)
	at hudson.model.AbstractBuild$AbstractBuildExecution.perform(AbstractBuild.java:741)
	at hudson.model.Build$BuildExecution.build(Build.java:206)
	at hudson.model.Build$BuildExecution.doRun(Build.java:163)
	at hudson.model.AbstractBuild$AbstractBuildExecution.run(AbstractBuild.java:504)
	at hudson.model.Run.execute(Run.java:1818)
	at hudson.model.FreeStyleBuild.run(FreeStyleBuild.java:43)
	at hudson.model.ResourceController.execute(ResourceController.java:97)
	at hudson.model.Executor.run(Executor.java:429)



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