To enable and disable Portal Trace

本文介绍如何将门户服务器的日志级别从默认的*=info调整为更详细的级别以诊断问题。通过更改日志级别,可以收集到特定组件的详细跟踪信息,这对于定位和解决门户问题非常有用。操作步骤包括登录应用服务器、导航到WebSphere Portal设置并修改日志详情级别。
To find out the root cause of portal problem, it is always useful to enable trace of portal server. Normally, for performance reasons, portal log level is set to *=info.

To change the log level, following the steps below:
1. Login to the AppServer
2. Navigate to Application Servers -> WebSphere_Portal -> WebSphere_Portal -> Change Log Detail Level
3. To enable trace, repace *=info with:

*=info:com.ibm.wps.engine.*=all:com.ibm.wps.services.puma.*=all:
com.ibm.wps.puma.*=all:com.ibm.wps.sso.*=all:com.ibm.wps.services. authentication.*=all:com.ibm.websphere.wmm.*=all =enabled:com.ibm.ws.wmm.*=all=enabled:WSMM=all= enabled:com.ibm.ws.security.*=all

4. Restart App and Portal Server

It is done!

 

Usage: cliclientd cmdName cmdArg [cmdName] specify the target name, such as pingstart, pingstop, tcpdumpstart, tcpdumpstop, tdb, debug, iwpriv, wltool. [cmdArg] arg of the command. [--help/-h] show usage info. for example: cliclientd pingstart "-c 5 192.168.0.254" cliclientd pingstop cliclientd locate --input again to stop locate cliclientd getcc cliclientd tcpdumpstart "-n -i eth0 icmp" cliclientd tcpdumpstop cliclientd tdb "-p [pid] -s" cliclientd iwpriv "ath0 dbgLVL 1" cliclientd setctrladdr "test.controller.com?dPort=29810?mPort=443?omadacId=c21f969b5f03d33d43e04f8f136e7682" cliclientd unix_sock_cli "-t 26 -v int:13" cliclientd debug "portal show <module name>" --show all portal user mode and kernel entries, 0:all 1:kernel 2:uclite 3:auth time cliclientd debug "portal config [0/1]" --set the kernel debug level, 0:disable 1:enable cliclientd debug "radius show configuration" --show radius configuration cliclientd debug "radius show statistics" --show radius statistics cliclientd debug "radius debug config [0/1]" --set radius debug level, 0:disable 1:enable cliclientd debug "uclite -m lan -e 1 -l 1" cliclientd debug "hostapd log_level [excessive/msgdump/debug/info/warning/error] [0/1]" --get/set hostapd log level and timestamp cliclientd debug "bonjour cmdValue" --show bonjour info or configuration, use dmesg|grep mdns to view the log printed by kernel module, for method to pack cmdValue, refer to tp_mdns.c cliclientd debug "hostapd log_type [stdout/file] [0/1]" --get/set hostapd log type and timestamp cliclientd debug "hostapd log_size [size]" --get/set hostapd log size (256k-10M) cliclientd debug "hostapd get_ptk <mac_addr> -i ifname" --get the PTK key for STA cliclientd debug "PPSK show radius config" --show PPSK radius server config in process radius cliclientd wltool sta --show brief info for all stations in this EAP cliclientd wltool "sta xx-xx-xx-xx-xx-xx" --show detailed info for sta xx-xx-xx-xx-xx-xx cliclientd wltool scan --show brief info for scan result cliclientd wltool "ifname stats" --show statistic info for if cliclientd wltool "ifname config" --show config info for if cliclientd diagnostics "[0/1] station_trace [0/1] <mac_addr>" --set diagnostics switch and station_trace for sta xx-xx-xx-xx-xx-xx, 0:stop, 1, start cliclientd diagnostics "[0/1] panicLog [0/1/2/3]" --set diagnostics switch and panic log type, 0:stop, 1:panic/die, 2:panic/die and sysrq, 3:all cliclientd diagnostics "saveLog [1]" --save log, 1:panicLog cliclientd --help 请解释这些用法
11-20
根据原作 https://pan.quark.cn/s/459657bcfd45 的源码改编 Classic-ML-Methods-Algo 引言 建立这个项目,是为了梳理和总结传统机器学习(Machine Learning)方法(methods)或者算法(algo),和各位同仁相互学习交流. 现在的深度学习本质上来自于传统的神经网络模型,很大程度上是传统机器学习的延续,同时也在不少时候需要结合传统方法来实现. 任何机器学习方法基本的流程结构都是通用的;使用的评价方法也基本通用;使用的一些数学知识也是通用的. 本文在梳理传统机器学习方法算法的同时也会顺便补充这些流程,数学上的知识以供参考. 机器学习 机器学习是人工智能(Artificial Intelligence)的一个分支,也是实现人工智能最重要的手段.区别于传统的基于规则(rule-based)的算法,机器学习可以从数据中获取知识,从而实现规定的任务[Ian Goodfellow and Yoshua Bengio and Aaron Courville的Deep Learning].这些知识可以分为四种: 总结(summarization) 预测(prediction) 估计(estimation) 假想验证(hypothesis testing) 机器学习主要关心的是预测[Varian在Big Data : New Tricks for Econometrics],预测的可以是连续性的输出变量,分类,聚类或者物品之间的有趣关联. 机器学习分类 根据数据配置(setting,是否有标签,可以是连续的也可以是离散的)和任务目标,我们可以将机器学习方法分为四种: 无监督(unsupervised) 训练数据没有给定...
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