About Web page performance measurement metrics and recommendations

First look at a diagram:

Note: The right image is often used in our work

What are the Web performance metrics we focus on?

1. Page load time

The time to load from the page to the page onload event firing. In general, the OnLoad trigger represents the CSS,JS directly from the HTML reference, and the picture resource is fully loaded.

2. Full page load time

Full page load time refers to the time that the network activity is not available after 2 seconds, starting with the initial start of the browse, until all elements have been loaded.

0-2 seconds: Best user experience, score 100
2-8 seconds: User can tolerate, starting from the 2nd second, each more than 1 seconds minus 5 points
8-15 seconds: User can not endure, starting from the 2nd second, every more than 1 seconds minus 5 points

3. First byte time

The time from the start of loading to the first byte of the received server return data

Compliance Time =DNS Resolution time + Create connection time +SSL authentication time +100ms. 10ms minus 1 points per slower than the standard time.
0-1 seconds: Best User Experience
1-2 seconds: User can tolerate
2-3 seconds: User cannot tolerate

4. Use long connection

The connection view shows the (keepalive) connection created during page loading and the resources loaded through each connection.

5. DNS Time

The time required for domain name resolution

0-50 milliseconds, 100 minutes.
50-500 milliseconds, which may affect the user experience, starting at 50 milliseconds, minus 2 for every 10 milliseconds increase
More than 500 milliseconds, severely affected? User's web experience, starting at 50 milliseconds, minus 2 for every 10 milliseconds added

6. TCP Time

Time the client established the connection

0-100 milliseconds, 100 minutes.
100-500 milliseconds, in general, may affect the user experience, starting at 100 milliseconds, without adding 10 milliseconds, minus 1 points
More than 500 milliseconds, severely affected? User's web experience, starting at 100 milliseconds, each 10 milliseconds, minus 1 points

7. HTTP Page Score

Page rendering, download speed, page smoothness

8. Comprehensive Score

Weighted calculated value of above rating = Full page loading time score *0.2+ first byte time score *0.2+ use long connection *0.1+dns time score *0.2+tcp time score *0.2+http page score *0.1

9, some other measurement indicators

Request time Definition: The so-called request time refers to the user from three handshake to the last request issued by this time, this time can be used to locate network problems. Network packet loss rate definition: Current network packet loss statistics. Network delay definition: The current network delay. including RTTC and Rtts. RTTC user-to-probe transmission delay Rtts probe to the server the transmission delay can be correlated with other metrics affected by the number of users so-called affected, that is, when a metric of the business is poor, how many users are affected. Through this indicator, you can get to the specific users who are affected. The number of sites affected is how many sites are affected when there is a problem with the network, or if there is a problem with the server. Through this indicator, you can then get to the specific affected sites are.

What other indicators do you have?

Simply speaking, the processing of a Web request consists of the following steps:

(1) The customer sends the request
(2) The Web server accepts requests for processing;
(3) Web server obtains data to DB;
(4) The Web server generates the user's object (page), which is returned to the user. The time to send a request to the client to start to the last byte is called the response time (the third step is not included in each request processing).

1. Transaction transaction

2. Request Response Time

3. Transaction response Time

A transaction may consist of a series of requests, and the response time of a transaction is primarily for the user, and is a macro concept that is presented to inform the user of the business response time. For example, the response time for a cross-line withdrawal transaction is made up of a series of requests. Transaction response time is a parameter that directly measures system performance.

4. Number of concurrent users

Concurrency is generally divided into 2 scenarios. One is the strict concurrency, that is, all users do the same thing or operation at the same time, this kind of operation generally refers to doing the same type of business. For example, in the credit card approval business, a certain number of advocates at the same time to the completed approval of the business to submit; There is also a special case where all users do exactly the same thing, for example, in the credit card approval business, all users can apply for business together, or modify the same record. Another concurrency is generalized range of concurrency. The difference between this concurrency and the previous concurrency is that although multiple users have made requests or performed actions on the system, these requests or actions can be the same or different. For the whole system, there are still many users working on the system at the same time, and therefore also belong to the concurrency category. As   you can see, the latter concurrency is the one that contains the previous concurrency. and the latter concurrency is closer to the actual usage of the user, so for most systems, only a very small number of users are "in strict concurrency". For Web performance testing, these 2 concurrency scenarios typically require testing, usually by first performing a rigorous concurrency test. In the strict sense of user concurrency generally occurs in the use of more frequent modules, although the probability of occurrence is not very large, but once a performance problem, the consequences are likely to be fatal. Rigorous concurrency testing is often associated with functional testing because concurrency is often a program problem and is part of robustness and stability testing. Number of concurrent users: There are 2 common misconceptions about the number of concurrent users. One of the misconceptions is that the number of concurrent users is understood as the number of users who use the system, on the grounds that they may use the system at the same time, and that a more near-correct view is that the number of online users is understood as the number of concurrent users. The fact that online users are not necessarily associated with other users, such as users who are browsing the web, has no effect on the server, but the number of online users is one of the main bases for calculating the number of concurrent users.

5. Throughput

6.tps

7. Click Number PV

The number of HTTP requests that the user submits to the Web server per second. This indicator is a unique indicator of Web application: The Web application is a "request-response" mode, the user makes one request, the server will process it, So click is the smallest unit of transactions that the Web app can handle. If you define each click as a trade, CTR and TPS are a concept. It is easy to see that the larger the CTR, the greater the pressure on the server. CTR is just a performance reference, and it's important to analyze the impact of clicks. Note that the Click here does not refer to a single click of the mouse, because in a single click, the client may make multiple HTTP requests to the server.

8. Resource utilization

Performance Item    command    metric CPU Limit    Vmstat when    %user+%sys exceeds 80% disk I/O limit     vmstat     when%iowait exceeds 40% (AIX4.3 .3 or later) apply disk limit     Iostat when%tm_act exceeds 70%, the virtual storage space is less       lsps,-a when  the paging space activity rate exceeds 70%, the page break limit         Iostat, stat  virtual memory Logical Volume %tm_act exceeds I/O (iostat) of 30%, activation of virtual storage rate exceeds the number of CPUs (VMSTAT) 10 times times the system fails         Vmstat, SAR   paging is increased, the CPU waits and runs the queue　　

Performance Item     Resource        Evaluation  CPU Utilization  70%         good           85%         bad           90%+        very poor disk i/0    <30%        Good           <40%        Bad           <50%+       very poor network       <30% bandwidth     good run queue   <2*cpu number   good memory       no page Exchange    good            
　　        10 page swapping   bad             More page swapping  is poor

About Web page performance measurement metrics and recommendations