KLFA USER MANUAL
Contents
1. sitioned in the log line using regex grouping exportRules rules properties Export the patterns detected by SLCT to file rules properties in the current dir workingDir trainingCsvGen Generates component files in folder trainingCsvGen componentsDefinitionFile compo save components ids to file nents training properties components training properties events correct txt events correct csv Original log file the one that we generated in the previous step The destination file Application Level Analysis and Action Level Analysis 16 4 1 Glassfish deployment failure java cp path to klfa it unimib disco lta alfa preprocessing eventTypesDetection AutomatedEventTypesDetector dontSplitComponents replacement CORE5076 Using x Using Java replacement domains domain1 config domains domainl config replacement service jmx rmi jndi rmi 8686 jmxrmi replacement service jmx rmi jndi rmi 8686 jmxrmi replacement INFO replacement FINE replacement DEBUG replacement FINEST replacement FINER dataExpression 2008 1 oe L I componentExpression 2008 I ee L xA ANT NI exportRules rules properties workingDir trainingCsvGen componentsDefinitionFile components training properties even2. Anomaly 8 Anomaly 8 indicates that a new component appeared Ifwe open components fail properties we see that component id 23 correspond to component com sun org apache commons modeler Regist By looking for it in the failure log we see that it appears because of an event occurred as a conse quence of the failure 26 Bibliography CPMP07 Domenico Cotroneo Roberto Pietrantuono Leonardo Mariani and Fabrizio Pastore In vestigation of failure causes in workload driven reliability testing In proceedings of the Fourth international workshop on Software quality assurance pages 78 85 ACM 2007 Gla Glassfish user forum Glassfish configuration issue http forum java sun com thread jspa threadID 5249570 visited in 2010 MP07 L Mariani and M Pezz Dynamic detection of COTS components incompatibility IEEE Software 24 5 76 85 September October 2007 MP08 Leonardo Mariani and Fabrizio Pastore Automated identification of failure causes in system logs In Proceedings of the 19th IEEE International Symposium on Software Re liability Engineering ISSRE 08 pages 117 126 Washington DC USA 2008 IEEE Computer Society Sun10a Sun visited in 2010 Java PetStore http java sun com developer releases petstore Sun10b Sun visited in 2010 GlassFish v3 Application Server Administration Guide http docs sun com doc 820 4495 Vaa03 R Vaarandi A data clustering algorithm for mining patterns from ev
3. generates models of legal behaviors and compares log files col lected during failing executions with the generated models to detect anomalous event sequences that are presented to users Experimental results show the effectiveness of the technique in supporting developers and testers to identify failure causes kLFA has been described in and MP08 Figure 1 1 shows the three steps of the technique while Figure 1 2 focus on the model generation Detailed information about the technique can be found in MPO8 Following chapters describe for every step of the technique the tools involved and give examples of the usage of the tools Introduction step 1 Monitoring in the field uses l test cases target system monitoring Y IN log step 2 Model Generation NN log model inference models step 3 Failure Analysis in the field uses SA target system D LAA e log automated model analysis S 4 teser inference suspicious g sequences models Figure 1 1 Automated log analysis 1 Event Detection mappings event component and event actions 1 log for each component log file l 1 event per line E log file gt S a application level analysis gt Splitter 1 annotated log file log file 1 event per line log file a
4. gt 1 event per line component level analysis Simple y Logfile l Clustering gt sees Tool event types I action level analysis Rule l gt l as Matcher I I l Es Data it Data log file Inference ReWiting 4 Swing W AE clustered j log file NI events Inference with data NU i Engine flow info l IX SA 2 Data Transformation Legend sw module data log file Figure 1 2 Model generation Chapter 2 Installing and Compiling KLFA 2 1 Installing a compiled version of KLFA If you received the KLFA distribution zip something like klfa 201010141601 zip just uncompress it in the location you prefer e g home fabrizio Programs k1fa201010141601 Once you uncompressed it you just need to do the following commands 1 Gf using Linux or OSX make scripts executables e g chmod a x home fabrizio Programs k1fa 201010141601 bin x 2 for any OS set the environment variable KLFA_HOME to point to the folder where you installed klfa e g home fabrizio Programs k1fa 201010141601 If you are using Linux or OSX with the BASH shell you could add the following line to file HOME bashrc export KLFA_HOME home fabrizio Programs klfa 201010141601 Change the path according to your KLFA installation path 3 for any OS add the bin folder in KLFA_HOME to the PATH environment
5. all messages of this type with a de Java fault message We need to replace this mes sage because it causes a false positive due to the different versions of VM used during training and checking thus we removed the info about the VM replacement domains domain1 config Removes the part of the path that generates domains domain1 config a false positive 15 Examples replacement ser Remove this information because the path is vice jmx rmi jndi rmi 8686 jmxrmi system dependent and we do not have enough cl tests to permit SLCT to understand that the service string is a parameter replacement ser Same as above vice jmx rmi jndi rmi 8686 jmxrmi nn replacement DEBUG Removes the information about the logging granularity We remove this information not because it introduces false positives but be cause make events regular expressions less readable replacement FINE Same as above replacement NA FINER Same as above replacement F INEST Same as above replacement ZN FO Same as above dataExpression 2008 LAA NN l AA AE A Tells KLFA where the useful information about the event is positioned using regex grouping componentExpression 2008 RANIA AAN AA 174 Tells KLFA where the component name is po
6. phase we preprocess the original log files in order to generate a model of the correct log file format 13 Examples Table 4 1 RegexBasedRawEventsSeparator parameters Parameters description eventsStartExpression indicates that log messages start with A correct Logs server log expands to all the correct log files Raw Events Separation Glassfish records logs in the Uniform Log Format Sun10b Logging messages witten in this for mat start with and end with and can span over different lines For this reason we need to preprocess the original log files in order to obtain a file in which each log message is recorded in a line In order to do this we descend into folder examples glassfishForumUserIssue analysis and run RegexBasedRawEventsSeparator with the following command all in a line java cp path to klfa preprocessing rawEventsSeparation RegexBasedRawEventsSeparator eventStartExpression 2008 correctlLogs server logx events correct txt From examples glassfishForumUserIssue analysis you can simply run bin runRawEvent Table explains the options used Events Types Detection Event types detection is performed using the AutomatedEvent TypesDetector tool which uses SLCT to detect the event types and then parses the given log to produce a final csv file in which component names events and parameters are separated
7. variable If you are using Linux or OSX with the BASH shell you could add the following line to file bashrc change the path according to your path export PATH PATH home fabrizio Programs kl1fa 201010141601 bin You can check if the previous command succeeded by running the following command and check ing that you have an output similar to the one reported below Installing and Compiling KLFA which klfaCsvAnalysis sh home fabrizio Programs kl1fa 201010141601 bin k1faCsvAnalysis sh Check if klfa is correctly installed by running klfaCsvAnalysis sh The command will output KLFA command help Like in the following paragraph This program builds models of the application behavior by analyzing a trace file The trace file must be a collection of lines each one in the format COMPONENT EVENT PARAMETER Multiple traces can be defined in a file to separate a trace from another put a line with the symbol Usage it unimib disco lta alfa klfa LogTraceAnalyzer options lt analysisType gt lt phase gt lt valueTranformersConfigFile gt lt preprocessingRules gt lt traceFile gt KLFA includes several programs and utilities described in the following Sections The most common utilities can be run by using the shell scripts in KLFA_HOME bin We suggest to go through the examples in folder KLFA_HOME examples to understand how to use KLFA Some exam
8. 14 R0020 java petstore2 0ea5 14 FinalState 1 q4 Existing 14_R0020_0 21 14_R0023 14 R0020 java petstore 2 0 ea5 4 Tail 7 q12 Existing 4_289331648 24 4 289331648 4_ 1628344215 4 _R0073 4_1573705168 4 _R0075 17 Tail 1 q3 Existing 17_ 811928006 25 17 17_R0008 811928006 3 Tail 5 q10 Existing 3_ 1648356848 27 3 3_R0032 1648356848 3_R0031 23 New Com ponent 24 4 1 Glassfish deployment failure cp path to klfa tools ShowFSA klfaoutput 5 fsa we can see that many more events are expected Furthermore by looking at the faulty log file we can see that the file is very short so we can deduce that it was truncated by the user or the application was blocked The Event column in this case do not represent the wrong event occurred but the last event seen The id of this last event is R0065 which correspond to the event regex JBIFW0010 JBI framework ready to accept requests Anomaly 2 Anomaly 2 regards component javax enterprise system core also in this case the anomaly is caused by the premature end of messages Anomaly 3 Anomaly 3 regards component GLOBAL This is not a real component it is a key word used to indicate the automata that describes the way components execution alternate The anomaly type is Tail it indicates that an unseen tail was added to the state q109 The first anomalous event seen is 14 R0020_0 while it expected 3_R0032 3_R0031 13_1
9. 394096499 or 2 2135717321 the last three are detected following the e transition The more interesting is the first one which indicates that a deploy message from component 3 javax enterprise system to ols admin is missing from the log We do not know if it indicates the cause of the failure This anomaly could depend on the fact that in one case it was used the Glassfish asadmin tool while in the other not Anomaly 4 Anomaly 4 regards component 14 the component recorded less messages than expected This is because the premature end of the log file KLFA expected a message of type R0023 AutoDeploy Disabling AutoDeployment service before stopping the Glass fish server We have an anomaly because in this log the stopping phase of the server is not recorded Anomaly 5 Anomaly 5 indicates that at line 24 an anomalous event 4_289331648 occurs The event ID in this case is an hash The AutomatedEventTypesExtractor assigns to a raw event line its hashcode as its id when the raw event is an outlier We have an outlier when a raw event does not match any event regexp The occurrence of an hashcode as an anomalous event can have two meanings the specific event was never seen in the correct logs analyzed or the event was present in the logs analyzed but its was present very few time and it was not considered an event type by default this happens when an event occurs just once In the first case it can be an exceptional event that appear as a c
10. KLFA USER MANUAL Contents 1 Introduction 2 Installing and Compiling KLFA 2 1 Installing a compiled version of KLFA 02 20 2000 eee 2 2 Compiling KLFA from a source distribution 20 000008 2 3 Compiling KLFA from CVS e 2 4 Installing SLOT 3_ Tools SA sees a ee he dade e BR we ae Re we eS ke ah a he HR RE ae Be ae a eS vb MS eee Os eS ee Oe eS ee See eS ee eed PERE EERE TAYE RS AAA SERGE dd AAA 4 Examples 4 1 Glassfish deployment failurel ee es 4 11 Monitoring s e v6 4 2 aaya eh Pace Sw ES we dose eae Oe Ew phe Goh OES ee ae eee a a aE G ES Ghee ee 4 1 3 Failure analysis soed ioi a a ai aa aa a k aa i OEA a ea i at a aa Bibliography XA XA O O a Chapter 1 Introduction Log files are commonly inspected by system administrators and developers to detect suspicious be haviors and diagnose failure causes Since size of log files grows fast thus making manual analysis impractical different automatic techniques have been proposed to analyze log files Unfortunately accuracy and effectiveness of these techniques are often limited by the unstructured nature of logged messages and the variety of data that can be logged KLFA is a tool that automatically analyzes log files and retrieves important information to iden tify failure causes KLFA automatically identifies dependencies between events and values in logs corresponding to legal executions
11. e analysis phase 20 4 1 Glassfish deployment failure Raw Events Separation The command used to separate raw events is the same as in the ModelGeneration phase except from the input and output parameters java cp path to klfa preprocessing rawEventsSeparation RegexBasedRawEventsSeparator eventStartExpression 2008 faultyLogs server fail log events fail txt From examples glassfishForumUserIssue analysis you can simply run bin run RawEventsSeparationChecking sh Events Types Detection The command is similar as in the Model Generation phase except from the fact that we tell the tool to use the component and rules ids used in the Model Generation phase Component Level Analysis java cp path to klfa it unimib disco lta alfa preprocessing eventTypesDetection AutomatedEventTypesDete replacement CORE5076 Using Using Java replacement x domains domain1 config domains domainl config replacement service jmx rmi jndi rmi 8686 jmxrmi replacement service jmx rmi jndi rmi 8686 jmxrmi replacement INFO replacement FINE replacement DEBUG replacement FINEST replacement FINER dataExpression 2008 1 L I componentExpression 2008 1 AAA LANA loadComponents components training properties exportRules rules checking prope
12. ent logs In Proceed ings of the 3rd IEEE Workshop on IP Operations and Management 2003 27
13. he components must be called from command line and the user has to set parameters according to the analysis type and the log file analyzed Following sections describe the functionality of each component Tools Figure 3 1 Components involved in the model generation phase 10 3 3 Failure Analysis 3 3 Failure Analysis In this fail the logs recorded during faulty executions are first preprocessed following the criterion adopted in the model inference phase and then are compared with the inferred models Figure 4 1 shows the components involved in this phase wer lt P From Model Inference Figure 3 2 Components involved in the failure analysis phase The results of this phase are a set of extended models and an anomaly file 11 Tools Column name Description Component Anomaly Line State StateType Event Original log line Original log event To state Branch length Expected Expected incoming Name of the component that presents this anomaly Anomaly type can be branch tail or final state Position in the trace in which the anomaly starts This number corresponds to the position of the event in the trace named checking_ lt componentName gt trace State of the component FSA in which the anoamly has been found State type can be existing if it is a state present in the component FSA or newif it is a state added during a pre vious extension Seq
14. in different columns The usage of the AutomatedEventTypesDetector depends on the kind of analysis you want to perform on your log file Following Sections list the different options used for the distinct analysis Component Level Analysis java cp path to klfa 14 4 1 Glassfish deployment failure it unimib disco lta alfa preprocessing eventTypesDetection AutomatedEventTypesDetector slctExecutablePath path to slct replacement CORE5076 Using x Using Java replacement domains domain1 config domains domainl config replacement service jmx rmi jndi rmi 8686 jmxrmi replacement service jmx rmi jndi rmi 8686 jmxrmi replacement INFO replacement FINE replacement DEBUG replacement FINEST replacement FINER dataExpression 2008 1 ee LE IT componentExpression 2008 ee Ae xA ANT EAI exportRules rules properties workingDir trainingCsvGen componentsDefinitionFile components training properties events correct txt events correct csv From examples glassfishForumUserIssue analysis you can simply run bin runComponen Table 4 2Jexplains the parameters used Table 4 2 AutomatedEventsDetector parameters Parameters description slctExecutablePath path to slct Path to the SLCT executable replacement CORE5076 Using Using Replaces
15. king sh or bin runActionLevelEventsDetectionChecking sh Comparison against the models Comparison against the model is done calling the LogTraceAnalyzer tool and giving the analysis type used in the model generation phase and specifying that we are now doing the comparison Component Level Analysis java cp path to klfa tools kLFAEngine LogTraceAnalyzer separator minimizationLimit 100 componentlevel checking transformersConfig txt preprocessingRules txt events fail csv 22 4 1 Glassfish deployment failure From examples glassfishForumUserIssue analysis you can simply run bin runCom ponentLevelAnomalyDetection sh Action Level Analysis java cp path to klfa tools kLFAEngine LogTraceAnalyzer separator minimizationLimit 100 actionLevel checking transformersConfig txt preprocessingRules txt events correct csv From examples glassfishForumUserIssue analysis you can simply run bin runAc tionLevelAnomalyDetection sh Application Level Analysis java cp path to klfa tools kLFAEngine LogTraceAnalyzer separator minimizationLimit 100 applicationLevel checking transformersConfig txt preprocessingRules txt events correct csv From examples glassfishForumUserIssue analysis you can simply run bin runAppli cationLevelAnomalyDetection sh Anomalies interpretation In the model comparison phase the tool detects the anomalies present in the fau
16. low the instructions described in Section 2 1 to install KLFA Other klfa ant compilation options are described by the build xml help To see the other compi lation options just run ant 2 4 Installing SLCT In order to identify event types AVA uses SLCT Vaa03 In order to install SLCT you need to change your current directory to src native slct 0 5 and compile slct If you use Linux or OsX you can run the following commands cd SAVA_HOME src native slct 0 5 gcc o slct 02 D_LARGEFILE_ SOURCE D_FILE_OFFSET_BITS 64 slct c sudo mkdir opt slct 0 5 sudo mv slct opt slct 0 5 Chapter 3 Tools 3 1 Monitoring In the monitoring phase the user is supposed to collect log files relative to correct system executions These log files can be collected at testing time during functional system tests or during correct runs of the system We do not provide any logging tool because the system can work with any logging systems 3 2 Model Generation In this phase the log files collected are analyzed by the system to derive a model that generalizes the application behavior In this phase the initial logs files are preprocessed with different tools in order to e contain a complete event in a single line e automatically detect event types and associated parameters e detect rewriting strategies for parameters e infer a model of the log file structure Figure 3 1 shows the components involved in this phase All t
17. lty log files and report them to the user by saving them in the file kl faoutput anomalies csv The last phase of the technique involves actively the user who has to inspect the reported anoma lies and use them as a guide to inspect correct and faulty files to detect the problem Table 4 1 3 shows the anomalies detected by the tool in the given case study We imported the csv file produced by the tool anomalies csv and sorted the items according to the column Original Event Line In the next paragraphs we are going to interpret them to give an exhaustive explana tion of the problem Anomaly 1 Anomaly 1 appears in line 15 of the faulty log file The anomaly regards com ponent com sun Jjbi framewor the id 5 correspond to this component as you can see from file components training properties In this case the anomaly is not caused by an unexpected event but the system detects that the events regarding component 5 stopped before expected In fact a new final state was added to the automaton By opening the automaton with the command java 23 Examples Table 4 5 Anomalies detected by KLFA for the Glassfish case study Comp Anomaly Line State State Event Original log line Original Expected Type log event 5 FinalState 1 q2 Existing 5_R0065 15 5 R0065 5_R0064 5_R0066_0_0 0 FinalState 5 q8 Existing 0_R0055 20 0 R0055 0_R0052 0_R0057 GLOBAL Tail 13 q109 Existing 14 R0020_0 21 3_R0032 A
18. oad data from Table 4 4 LogTraceAnalyzer Component Level Analysis options preprocessingRules txt events correct csv From examples glass ponentLevelInference sh Table explains the Action Level Analysis fishForumUserIssue analysis you can simply run bin runCom options used java cp path to klfa tools kLFAEngine LogTraceAnalyzer separator splitActionLines actionLines actions correct properties minimizationLimit 100 actionLevel train ing transformersConfig txt preprocessingRules txt events correct csv From examples glassfishForumUserIssue analysis you can simply run bin runAc tionLevelInference sh Application Level Analysis java cp path to klfa tools kLFAEngine LogTraceAnalyzer separator minimizationLimit 100 applicationLevel training transformersConfig txt preprocessingRules txt t events correct csv 19 Examples From examples glassfishForumUserIssue analysis you can simply run bin runAppli cationLevelInference sh 4 1 3 Failure analysis Once the failure occurs the faulty log file can be compared with the inferred models to detect anoma lies To do this we have to process the faulty log file in a similar manner as in the model inference phase Figure 4 1 shows the required steps a From Model Inference lt lt A Lae OO swe ES Figure 4 1 Components involved in the failur
19. onsequence of a failure or it can be a false positive caused by event regexp that do not generalize enough the data This should happen if in the correct log files we have events in which a parameter remains constant over all their occurrences in this case the parameter will be considered by SLCT as part of the event regex and in case the value change in the faulty execution because of environmental reasons e g domain of a web server it will be detected as an anomaly which may be not related to 25 Examples the experienced failure pay attention it should also be the case in which in the correct execution the system was behaving correctly because of this constant value In this case to further inspect the anomalous event we need to take a look at the faulty log file events fail txt we see that there is an exception in line 24 which is related to the failure The exception was never seen in the correct log files search for 289331648 in the correct log Anomaly 6 Anomaly 6 occur at line 25 the event 17_ 811928006 was unexpected As in the previous case the hashcode id was generate because of a message never seen before the exception Anomaly 7 Anomaly 7 is detected in line 27 of the trace file Also in this case if we take a look at the faulty log file events fail txt in line 27 we see that there is an exception which is related with the failure The technique has detected an useful information for the root cause analysis
20. pesDetector you can generate the transformation rules by running java cp path to klfa it unimib disco lta alfa parametersAnalysis TransformationRulesGenerator signatureElements 0 1 events correct csv Table explains the options used Inference of the models Model inference is done using the LogTraceAnalyzer tool It first applies the data transformation rules detected by the TransformationRulesGenerator Then it builds models using the kBehavior inference engine MPO7 The analysis type is selected by the user providing the corresponding parameters to the Log TraceAnalyzer In the following paragraphs we explain how to do the different analysis Component Level Analysis java cp path to klfa tools kLFAEngine LogTraceAnalyzer separator minimizationLimit 100 componentLevel training transformersConfig txt 18 4 1 Glassfish deployment failure Parameters description n separator separator char used in the csv file minimizationLimit 100 do not minimize FSA if they have more than 100 states componentLevel do component level analysis training learn the models transformersConfig txt file with the rewriting rules defined for the different data clusters preprocessingRules txt file with the association between the different instances of rewriting strategies and the different parameters events correct csv csv file to l
21. ples are described in Chapter 4 others are described in the file README txt that you find in each example folder 2 2 Compiling KLFA from a source distribution If you received a source distribution zip of KLFA something like klfa src 201010141601 zip un compress it in the location you prefer e g home fabrizio Programs klfa sre201010141601 In order to compile an installable version of klfa from sources run the following command within the folder where you uncompressed klfa ant distribution so you could do cd home fabrizio Programs klfa src 201010141601 ant distribution 2 3 Compiling KLFA from CVS The command will create the KLFA distribution zip in the dist folder e g home fabrizio Programs k1fa src201010141601 dist k1fa201010141601 zip After creating the distribution zip you can follow the commands described in Section 2 3 Compiling KLFA from CVS In order to install the head version of klfa stored on the UniMiB CVS repository you need to down load the following CVS modules e LogFileAnalysis LFA e BCT you need to download the TPTPIntegration branch LogFileAnalysis LFA is klfa BCT provides the libraries to infer automata The first step is the compilation of klfa dependencies To do so run ant buildDependencies The command will create the library bct jar in folder lib Next step is to run the command ant distribution This command builds the klfa distribution zip Fol
22. rties workingDir checkingCsvGen Ta EventPatterns patternsDir trainingCsvGen load componentsDefinitionFile components fail properties events fail txt events fail csv 21 Examples From examples glassfishForumUserIssue analysis you can simply run bin runCom ponentLevelEventsDetectionChecking sh Application Level Analysis and Action Level Analysis java cp path to klfa it unimib disco lta alfa preprocessing eventTypesDetection AutomatedEventTypesDete dontSplitComponents replacement CORE5076 Using Using Java replacement x domains domain1 config domains domainl config replacement service jmx rmi jndi rmi x 8686 jmxrmi replacement service jmx rmi jndi rmi x 8686 jmxrmi replacement INFO replacement FINE replacement DEBUG replacement FINEST replacement FINER dataExpression 2008 1 eA AJ componentExpression 2008 I1 L L ANI EAI loadComponents components training properties exportRules rules checking properties workingDir checkingCsvGen loadEventPatterns patternsDir trainingCsvGen componentsDefinitionFile components fail properties events fail txt events fail csv From examples glassfishForumUserIssue analysis you can simply run bin runAppli cationtLevelEventsDetectionChec
23. ts correct txt events correct csv From examples glassfishForumUserIssue analysis you can simply run bin run ActionLevelEventsDetectionTraining sh As you can see for both Application and Action Level Analysis the options are the same of the Component Level Analysis except from the additional parameter dontSplitComponents This happens because the log file format is the same so the parsing options do not change the only differ ence is in the way events are detected in this case we do not need to detect events for components separately Transformation Rules Generation The next step is the automatic detection of the rewriting strategies to be used with the engine This is achieved by running TransformationRulesGenerator java cp path to klfa 17 Examples Parameters description patterns rules properties load events regex from file rules properties signatureElements 0 1 do not threat columns 0 and 1 as parameters events correct csv name of the csv file to analyze Table 4 3 TransformationRulesgenerator options it unimib disco lta alfa parametersAnalysis TransformationRulesGenerator patterns rules properties signatureElements 0 1 events correct csv From examples glassfishForumUserIssue analysis you can simply run bin run TransformationRulesGeneration sh If you already had a CSV file and for this reason you did not run class EventTy
24. uence of anomalous preprocessed events observed Position in the original log Sequence of anomalous events observed State in which the anomaly ends makes sense only if it is a branch added anomaly Lenght of the added branch Expected event going out from the anomalous state Events expected before state To state 12 Chapter 4 Examples 4 1 Glassfish deployment failure This section describe a real case study in which we analyzed log files generated by the Glassfish J2EE application server to detect the cause of a failure while deploying the Petstore web application In this case study we collected the log files produced by glassfish during system tests derived models from the log files we applied the three different approaches and compared the log file produced during the failure This log file was provided by a user of the system who was not able to deploy the Petstore web application using Netbeans Gla All the files described in this example can be found in folder examples glassfishForumUserIssue 4 1 1 Monitoring In the monitoring phase we collected log files produced by Glassfish while it was performing dif ferent functionalities start up shutdown web application deploy and response to web application requests The log files were recorded with the default log verbosity Log files are stored in folder examples glassf ForumUserIssue correctLogs 4 1 2 Model Generation In the model generation
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