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A single web page in a web site/web application may contain more than one page type - in other words, it can contain a base page, one/more iFrames, and AJAX pages. Much against popular notion, base pages may not always be responsible for slowing down user accesses to a web site/web application. More often than not, iFrame URLs that that take hours to load and inefficient AJAX code, cause users to experience slowness or errors when accessing a web site/web application. This is why, when users complain that their web site/web application is responding slowly to requests, administrators need to rapidly determine whether the slowness is owing to the base pages themselves, or because of iFrames and/or AJAX pages operating within the base pages. Accurate identification of the problem source enables administrators to figure out exactly what should be done to enhance performance of the web site/web application - should the base pages be re-engineered? should the iFrame URLs be pulled up for scrutiny? or should the AJAX code be cleaned up?

The RUMPageTypeTest test looks ‘under-the-hood’ of a web site/web application, discovers the page types that are in use, and reports the user experience per page type, so that administrators can instantly identify which page type is the least responsive or is error-prone. Detailed diagnostics of the test also lead you to the precise pages of a type that are slow, and what is causing the slowness - is it a slow front end? latent network? or a busy backend? The actual JavaScript errors that occurred in the pages of each type are also available as part of the detailed diagnosis, so as to facilitate easy and effective troubleshooting.

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:

Measurement	Description	Measurement Unit	Interpretation
Page_Requests	Indicates the total number of times pages of this type were viewed by users to the web site/web application.	Number	This is a good measure of the traffic to a specific page type. 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 to this page type.	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 type has been less than satisfactory.
Avg_Page_Load_Time	Indicates the average time taken by the pages of this type 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 page types, you will be able to tell if the page load time is significantly higher for any one type of page – this could be the page type that is causing the slowness. You may want to compare the values of the of the Avg_Front_End_Time, Avg_Network_Time, and Avg_Response_Avail_Time measures for that page type, to know what is exactly causing pages of that type to load slowly - is it the front end? network? or the backend? To know which pages of the type are slow, use the detailed diagnosis of this measure.
Unique_User_session	Indicates the number of distinct users who are currently accessing pages of this type in the web site/web application.	Number
Request_Per_Minute	Indicates the number of times the pages of this type were viewed per minute.	Number	An unusually high value for this measure may require investigation.
Percentage_Normal	Indicates the percentage of page views of this type that delivered a satisfactory experience to users.	Percent	The value of this measure indicates the percentage of page views of this type in which users 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 with pages of this type has not been up to the mark. A value less than 50% is indicative of a serious problem, where most of the page views of this type are either slow or have encountered Javascript errors. Under such circumstances, to know what exactly is affecting the experience of users to this page type, 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 of that type 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 of the type.
Percentage_Slow	Indicates the percentage of page views of this type that are slow in loading.	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 of this type 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 of this type were viewed 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 user experience with this page type has been below-par. In such a case, use the detailed diagnosis of the Tolerated_Requests and the Frustrated_Requests views measures to know which pages are slow and why.
Slow_Requests	Indicates the number of page views of this type that were slow.	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 viewing pages of this type.	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 of this type.	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 CUTOFF (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 user experience with this page type 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 of this type.	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 to this page type 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 for this page type.	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 of type in the browser.	ms	A high value of this measure indicates that the pages of this type 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_Time. 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 of this type.	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 this page type on the browser.	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 of this type 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 with pages of this type. Ideally therefore, the value of this measure should be low.
Avg_First_Byte_Time	Indicates the interval between the time that a user initiates a request and the time that the browser receives the first response byte for this page type. 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 on the browser for this page type to when the 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 initiates a request to this page type 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 this page type 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 this page type 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.