A typical issue which i faced during web log analysis...
While conducting Performance testing for applications which are falling into the category of Post-Production case, the most important activity that needs to be done is web log analysis. The web server logs are the gold mines which hold all the information about the server during the load condition.
During the web log analysis, look for the peak hour traffic time and identify what is the server load in terms of hits/sec and in terms of users. Based on this statistics, derive performance test goals by considering the business forecasts.
I would like to share a typical issue which I faced while doing web log analysis for a typical post production category of an application. The application under test uses a shared web-app server (IIS) in which there was 2 other applications deployed. Now, the problem is the web server log files have the traces of all 3 applications together as these files are common for a server and not specific for each of the applications running on the server.
The web log analyzer tool which I was using doesn’t have any option to set filters. In that case, I tried using a web log analyzer tool (123LogAnalyzer tool) which provides a filter option to filter out the traces pertaining to a specific application and export the filtered log file into a text file. For example, if the application under test has a context root as ‘methodologies’ (http://132.23.34.21/methodologies/......), then try setting up this URL in the filter and create the text files for your application of interest.
Now you could use the newly generated text file to feed it into any of the log analyzer tool which you are confident enough and proceed with your performance goal setting. My kind advice is that before choosing the log analysis tool of your choice, analyze the accuracy of log analysis thoroughly.
A Comprehensive Report on Web Log Analysis
In today’s dynamic world, the IT sector of all the businesses want to use more sophisticated techniques to support their application scalability. All the web site owners are interested to know the usage pattern of their site in order to make any business decisions. The necessity to know the visitor profile is very high in any web site as most of time the visitors are anonymous & unpredictable for any open systems (which uses internet).
The Web analytics activity deals with measuring the end user behaviors on a web site. Of the two major web analytics techniques (Web server log analysis & Page Tagging) available, this paper deals with the Web Server Log Analysis concepts. This paper provides an overview of various log analyzer tools available in the market & their comparative ratings.
The Web log analysis is used by various types of users with different backgrounds. The different sets of users are interested to know about specific data from the web server log. This has lead to the development of lot of log analyzer tools with specific extra features, though the basic features are available in most of the tools.
While conducting Performance testing for applications which are falling into the category of Post-Production case, the most important activity that needs to be done is web log analysis. The web server logs are the gold mines which hold all the information about the server during the load condition.
During the web log analysis, look for the peak hour traffic time and identify what is the server load in terms of hits/sec and in terms of users. Based on this statistics, derive performance test goals by considering the business forecasts.
I would like to share a typical issue which I faced while doing web log analysis for a typical post production category of an application. The application under test uses a shared web-app server (IIS) in which there was 2 other applications deployed. Now, the problem is the web server log files have the traces of all 3 applications together as these files are common for a server and not specific for each of the applications running on the server.
The web log analyzer tool which I was using doesn’t have any option to set filters. In that case, I tried using a web log analyzer tool (123LogAnalyzer tool) which provides a filter option to filter out the traces pertaining to a specific application and export the filtered log file into a text file. For example, if the application under test has a context root as ‘methodologies’ (http://132.23.34.21/methodologies/......), then try setting up this URL in the filter and create the text files for your application of interest.
Now you could use the newly generated text file to feed it into any of the log analyzer tool which you are confident enough and proceed with your performance goal setting. My kind advice is that before choosing the log analysis tool of your choice, analyze the accuracy of log analysis thoroughly.
In today’s dynamic world, the IT sector of all the businesses want to use more sophisticated techniques to support their application scalability. All the web site owners are interested to know the usage pattern of their site in order to make any business decisions. The necessity to know the visitor profile is very high in any web site as most of time the visitors are anonymous & unpredictable for any open systems (which uses internet).
The Web analytics activity deals with measuring the end user behaviors on a web site. Of the two major web analytics techniques (Web server log analysis & Page Tagging) available, this paper deals with the Web Server Log Analysis concepts. This paper provides an overview of various log analyzer tools available in the market & their comparative ratings.
The Web log analysis is used by various types of users with different backgrounds. The different sets of users are interested to know about specific data from the web server log. This has lead to the development of lot of log analyzer tools with specific extra features, though the basic features are available in most of the tools.
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