eG Monitoring
 

Measures reported by RUMCityTest

The RUMCityTest test provides an aggregate of the experience of users from different cities. If the users to your web site/web application are spread across different cities, you can use this test to know:

  • Which cities your users are coming from;

  • Which are the cities in which your web site/web application is very popular

  • How is the experience of users from each of these cities.

Moreover, if multiple users to a web site/web application are seeing slow page loads or error responses at around the same time, administrators can use this test to figure out if the problem is specific to a particular city; if so, the test further pinpoints which exact city is impacted and why is the experience of users from that city poor - is the front end used by the users in this city inefficient? Is the WAN connection between the browser clients in this city and the backend server hosting the web site/web application latent? or is the problem with the backend? Detailed diagnostics provided by the test also point to the specific pages that are slow or have encountered JavaScript errors.

Note:

By default, the eG agent can send a maximum of 50 million characters to the eG manager, when reporting detailed diagnostics for a test for a single measurement period. If this limit is exceeded by a test during a measurement period, then the detailed diagnostics reported by that test will be automatically truncated and the additional characters dropped. Moreover, a message to this effect will also be logged in the eG agent's error log. If such errors are logged frequently for a particular test, you may want to seriously consider increasing this character limit of the detailed metrics collected by that test. For this purpose, do the following:

  • Edit the eg_tests.ini in the <EG_INSTALL_MANAGER}DIR>\manager\config directory of the eG manager installation.

  • Go to the [MAX_DD_UPLOAD_LENGTH] section of the file.

  • In this section, look for the parameter that corresponds to the <Internal_test_name> of the test for which the character limit has to be increased.

  • Once you find the parameter, set the value of that parameter to a number of your choice.

  • Finally, save the file.

The measures made by this test are as follows:

Measurement Description Measurement Unit Interpretation
Page_Requests Indicates the total number of times pages were viewed by users from this city. Number This is a good measure of the traffic from a specific city.

Sudden, but significant spikes in the page view count could be a cause for concern, as it could be owing to a malicious virus attack or an unscrupulous attempt to hack your web site/web application.
Apdex_Score Indicates the apdex score of the web site/web application based on the experience of users from this city. Number Apdex (Application Performance Index) is an open standard developed by an alliance of companies. It defines a standard method for reporting and comparing the performance of software applications in computing. Its purpose is to convert measurements into insights about user satisfaction, by specifying a uniform way to analyze and report on the degree to which measured performance meets user expectations.

The Apdex method converts many measurements into one number on a uniform scale of 0-to-1 (0 = no users satisfied, 1 = all users satisfied). The resulting Apdex score is a numerical measure of user satisfaction with the performance of enterprise applications. This metric can be used to report on any source of end-user performance measurements for which a performance objective has been defined.

The Apdex formula is:

Apdext = (Satisfied Count + Tolerating Count / 2) / Total Samples

This is nothing but the number of satisfied samples plus half of the tolerating samples plus none of the frustrated samples, divided by all the samples.

A score of 1.0 means all responses were satisfactory. A score of 0.0 means none of the responses were satisfactory. Tolerating responses half satisfy a user. For example, if all responses are tolerating, then the Apdex score would be 0.50.

Ideally therefore, the value of this measure should be 1.0. A value less than 1.0 indicates that the experience of users to this page group has been less than satisfactory.
Avg_Page_Load_Time Indicates the average time that pages accessed by users from this city took to load completely on the browser. ms This is the average interval between the time that a user initiates a request and the completion of the page load of the response in the user's browser. In the context of an Ajax request, it ends when the response has been completely processed.

By comparing the value of this measure across cities, you will be able to tell if the page load time is significantly higher for any one city - this is the first sign that the problem could be city-specific. Next, check the detailed diagnosis of this measure for this city to find out which pages are slow. Then, look up the detailed measures for the other cities to ascertain whether users from those cities also experienced slowness when accessing the same pages. If not, it is a sure sign that the problem is specific to the city.

So, proceed to compare the values of the Avg_Front_End_Time, Avg_Network_Time, and Avg_Response_Avail_Time time measures for that city, to know why the users in that city are seeing slowness - is it the front end? network? or the backend?

If the Avg_Front_End_Time is the maximum, then the problem is the front end used by the users in that city. If the Avg_Network_Time is the highest, then the network connection between the user's browser and the web site/web application is the one contributing to the slowness. A very high Avg_Response_Avail_Time on the other hand, reveals that problem may have nothing to do with the city, but with the server that is hosting the web site/web application.
Unique_User_session Indicates the number of distinct users who are currently accessing the web site/web application from this city. Number  
Request_Per_Minute Indicates the number of times the pages were viewed per minute by users from this city. Number An unusually high value for this measure may require investigation.
Percentage_Normal Indicates the percentage of page views that delivered a satisfactory experience to users from this city. Percent The value of this measure indicates the percentage of page views in which users from this city have neither experienced any slowness, nor encountered any Javascript errors.

Ideally, the value of this measure should be 100%. A value that is slightly less than 100% indicates that the user experience has not been up to the mark. A value less than 50% is indicative of a serious problem, where most of the page views are either slow or have encountered Javascript errors. Under such circumstances, to know what exactly is affecting the experience of users, compare the value of the Percentage_Slow with that of the Percentage_Error for that browser. This will reveal the reason for the poor user experience % slow pages? or Javascript errors?

If slow pages are the problem, use the detailed diagnosis of the Slow_Requests measure to know which pages are slow and where these pages are losing time - in the front end? network? or backend?.

If JavaScript errors are the problem, use the detailed diagnosis of the Percentage_Error measure to know what errors occurred in which pages.
Percentage_Slow Indicates the percentage of pages that were slow in loading when accessed by users in this city. Percent Ideally, the value of this measure should be 0. A value over 50% implies that you are in a spot of bother, with over half of the page views being slow. Use the detailed diagnosis of the Slow_Requests measure to identify the slow pages and isolate the root-cause of the slowness - is it the front end? the network? or the backend?
Percentage_Error Indicates the percentage of page views that have encountered JavaScript errors. Percent Ideally, the value of this measure should be 0. A value over 50% implies that you are in a spot of bother, with over half of the page views of this type are experiencing JavaScript errors. Use the detailed diagnosis of this measure to identify the error pages and to know what Javascript error has occurred in which page. This will greatly aid troubleshooting!
Satisfied_Requests Indicates the number of times pages were viewed by users in this city without any slowness. Number A page view is considered to be slow when the average time taken to load that page exceeds the SLOW TRANSACTION CUTOFF configured for this test. If this SLOW TRANSACTION CUTOFF is not exceeded, then the page view is deemed to be ‘satisfactory’. To know which page views are satisfactory, use the detailed diagnosis of this measure.

Ideally, the value of this measure should be the same as that of the Page_Requests measure. If not, then it indicates that one/more page views are slow - i.e., have violated the SLOW TRANSACTION CUTOFF.

If the value of this measure is much lesser than the value of the Tolerated_Requests and the Frustrated_Requests, it is a clear indicator that the experience of users in this city has been below-par. In such a case, use the detailed diagnosis of the Tolerated_Requests and the Frustrated_Requests measures to know which pages are slow and why.
Slow_Requests Indicates the number of page views that were slow when accessed from this city. Number A page view is considered to be slow when the average time taken to load that page exceeds the SLOW TRANSACTION CUTOFF configured for this test.

Ideally, a page should load quickly. The value 0 is hence desired for this measure. If the value of this measure is high, it indicates that users frequently experienced slowness when accessing pages in the web site/web application. To know which page views are slow and why, use the detailed diagnosis of this measure.
Error_Requests Indicates the number of times JavaScript errors occurred when accessing pages from this city. Number Ideally, the value of this measure should be 0. A high value indicates that many JavaScript errors are occurring when viewing pages in the web site/web application. Use the detailed diagnosis of this measure to identify the error pages and to know what Javascript error has occurred in which page. This will greatly aid troubleshooting!
Tolerated_Requests Indicates the number of tolerating page views experienced by users in this city. Number If the Avg_Page_Load_Time of a page exceeds the SLOW TRANSACTION CUTTOFF configuration of this test, but is less than 4 times the SLOW TRANSACTION CUTTOFF (i.e., < 4 * SLOW TRANSACTION CUTOFF), then such a page view is considered to be a Tolerating page view.

Ideally, the value of this measure should be 0. A value higher than that of the Satisfied_Requests measure is a cause for concern, as it implies that the overall experience of the users in this city is less than satisfactory. To know which pages are contributing to this sub-par experience, use the detailed diagnosis of this measure. The detailed metrics will also enable you to accurately isolate what is causing the tolerating page views - a problem with the front end? network? or backend?
Frustrated_Requests Indicates the number of frustrated page views experienced by users in this city. Number If the Avg_Page_Load_Time of a page is over 4 times the SLOW TRANSACTION CUTTOFF configuration of this test (i.e., > 4 * SLOW TRANSACTION CUTOFF), then such a page view is considered to be a Frustrated page view.

Ideally, the value of this measure should be 0. A value higher than that of the Satisfied_Requests measure is a cause for concern, as it implies that the experience of users in this city has been less than satisfactory. To know which pages are contributing to this sub-par experience, use the detailed diagnosis of this measure. The detailed metrics will also enable you to accurately isolate what is causing the frustrated page views - a problem with the front end? network? or backend?
Avg_Front_End_Time Indicates the interval between the arrival of the first byte of text response and the completion of the response page rendering by the browser used by users in this city. ms In a typical page loading process, the Avg_Front_End_Time denotes the time from the responseStart event to the loadEventEnd. This process includes document downloading, processing, and page rendering. This time is therefore the sum of the Avg_Dom_Ready_Time and the Avg_Page_Rendering_Time.

If the Avg_Page_Load_Time of the web site/web application exceeds its threshold, then you may want to compare the value of this measure with that of the Avg_Network_Time and Avg_Response_Avail_Time to zoom into the source of the slowness - is it the device? the network? or the backend?
Avg_Page_Rendering_Time Indicates the time taken to complete the download of remaining resources, including images, and to finish rendering the pages in the browser for users in this city. ms A high value of this measure indicates that the pages in this group are taking too long to be rendered. This can adversely impact the Avg_Front_End_Time, which in turn can prolong the Avg_Page_Load_Timee. Ideally therefore, the value of this measure should be low.
Avg_Dom_Ready_Time Indicates the time taken by the browser to make the complete HTML document (DOM) available for JavaScript to apply rendering logic on the pages accessed by users in this city. ms The value of this measure is the sum of the Avg_Dom_Download_Time and the Avg_Dom_proc_Time measures. If the value of this measure is very high, then you may want to compare the Avg_Dom_Download_Time and the Avg_Dom_proc_Time measures to figure out what is delaying DOM building - downloading? Or processing?

A high value for this measure can adversely impact the Avg_Front_End_Time, which in turn can prolong the Avg_Page_Load_Time. Ideally therefore, the value of this measure should be low.
Avg_Dom_Download_Time Indicates the time taken to download the complete HTML document for requests received from users in this city. ms Higher the download time of the document, longer will be the time taken to make the document available for page rendering. As a result, the overall user experience will be affected! This is why, a low value is desired for this measure at all times.
Avg_Dom_proc_Time Indicates the time taken by the browser to build the Document Object Model (DOM) for the pages requested by the users in this city and make it available for JavaScript to apply rendering logic. ms An unusually high value for this measure is a clear indicator that DOM building is taking longer than normal. In consequence, page rendering will be delayed, thus adversely impacting user experience when this page group is accessed. Ideally therefore, the value of this measure should be low.
Avg_First_Byte_Time Indicates the interval between the time that a user in this city initiates a request and the time that the browser receives the first response byte. In the context of an Ajax request, this is the interval between the Ajax request dispatch and the time that the browser receives the first response byte. ms The Avg_First_Byte_Time is the time that elapsed between navigationStart and responseStart. The value of this measure is also the sum of Avg_Response_Avail_Time, Avg_DNS_Time, and Avg_TCP_Time. This means that an abnormal increase in any of the above-mentioned time values will increase the value of this measure.

If the first response byte from the target web site/web application is itself received slowly, it is bound to have a cascading effect on all events that follow - such as, document downloading, processing, and page rendering. Ultimately, this will impact the page load time as seen by end-users. This is why, if the Avg_First_Byte_Time violates its threshold, administrators need to instantly switch to the troubleshooting mode and rapidly isolate what is causing it - is DNS lookup taking a long time? is the network connection to the web site/web application latent? or is the web server/web application server hosting the web site slow in processing requests? By comparing the values of the Avg_Response_Avail_Time, Avg_DNS_Time, and Avg_TCP_Time measures, administrators can swiftly and accurately figure out the exact reason why there was a delay in receiving the first response byte.

If this comparison reveals that the Avg_DNS_Time is the highest, it implies that domain name resolution by the DNS server is taking a long time and impacting responsiveness. If the Avg_TCP_Time is found to be the culprit, then blame the network connection for delaying the transmission of the response byte. If the Avg_Response_Avail_Time is higher than the rest, you can be rest assured that the source of the problem lies with the server hosting the web site/web application.
Avg_Response_Avail_Time Indicates the interval between the start of processing of a request from a user in this city to when response is received. ms The Avg_Response_Avail_Time is the time spent between the requestStart event and responseStart event.

Ideally, a low value is desired for this measure, as high values will certainly hurt the Apdex_Score of the web site/web application.

The key factor that can influence the value of this measure is the request processing ability of the web server/web application server that is hosting the web site/web application being monitored.

Any slowdown in the backend web server/web application server - caused by the lack of adequate processing power in or improper configuration of the backend server - can significantly delay request processing by the server. In its aftermath, the Avg_Response_Avail_Time will increase, leaving users with an unsatisfactory experience with the web site/web application.
Avg_Network_Time Indicates the elapsed time since a user in this city initiates a request to the web site/web application and the start of fetching the response document from it. ms The time spent between navigationStart and requestStart makes up the Avg_Network_Time. This includes the time to perform DNS lookups and the time to establish a TCP connection with the server. In other words, the value of this measure is nothing but the sum of the Avg_DNS_Time and Avg_TCP_Time measures.

Ideally, the value of this measure should be low. A very high value will often end up delaying page loading and damaging the quality of the web site service. In the event that the server connection time is high therefore, simply compare the values of the Avg_DNS_Time and Avg_TCP_Time measures to know to what this delay can be attributed - a delay in domain name resolution? Or a poor network connection to the server?
Avg_DNS_Time Indicates the time taken by the browser used by a user in this city to perform the domain lookup for connecting to the web site/web application. ms A high value for this measure will not only affect DNS lookup, but will also impact the Avg_Network_Time and Avg_Page_Load_Time of the web site/web application. This naturally will have a disastrous effect on user experience.
Avg_TCP_Time Indicates the time taken by the browser used by a user in this city to establish a TCP connection with the server. ms A bad network connection between the browser client and the server can delay TCP connections to the server As a result, the Avg_Network_Time too will increase, thus impacting page load time and overall user experience with the web site/web application.