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The content of this article mainly focuses on what is the stability testing method of the server in software testing. the content of the article is clear and clear, which is very suitable for beginners to learn and is worth reading. Interested friends can follow the editor to read together. I hope you can get something through this article!

Server stability is the most important, if the stability can not guarantee the needs of business operation, no matter how high performance is useless. Regular server manufacturers will test the stability of their products at different temperatures and humidity. The key consideration is redundancy, such as data redundancy, network card redundancy, power supply redundancy, fan redundancy and so on.

Some server stability testing methods are mainly as follows:

Stress test:

Given the number of users in the peak period of the system, verify whether the transaction response time can meet the customer requirements under the number of concurrency (converted by the number of people in the peak period). Whether the performance indicators of the system are still within the normal value under this kind of pressure. Whether the system will cause adverse reactions (such as downtime, abnormal termination of application, etc.) due to such pressure.

Ramp Up incremental design:

If the number of concurrent users is 75, the number of registered users of the system is 1500, and the reference value of 5% Murray 7% is used as the reference value of concurrent users. Generally, the pressurization design is carried out by loading 5 people every 15s. This value mainly refers to testing the performance of the pressurizer, and it is recommended to Run several times. The actual loading mode is measured by transaction pass rate and error rate.

Ramp Up incremental design goals:

Looking for the performance bottleneck location of the incremental pressurized system, and seizing the opportunity of the performance inflection point, we usually refer to the comprehensive judgment of Hits click rate and throughput, CPU and memory usage. Simulate the number of peak users, such as login in the morning, exit after work, messaging system when payroll is sent, etc.

Another limit simulation method can be regarded as the system limit operation index of clicking transaction operation at the same time under peak pressure. The compression method remains the same, and the same collection point name is set in each script transaction point (such as: lr_rendzvous ("same");). In the scenario design, the transaction point collection strategy is used. Release all Vuser that are in Run at the same time based on the percentage of rendezvous point reached simultaneously.

Stability test:

It is known that the number of users during the peak period of the system, the operation frequency of each transaction, and so on. A comprehensive test scenario is designed, in which each scenario is run in proportion to a certain number of people to simulate the use of users for several years. And monitor whether the performance indicators of the system can maintain the normal value under this pressure in the test. Whether the transaction response time fluctuates or increases with the test time. Whether the system will occur during the test period, such as downtime, application abort and other abnormal conditions.

According to the above tests, the location of the performance inflection point under each transaction condition is used to determine the number of concurrent users in the stability test. According to the actual test server (pressure machine, application server, data server tripartite performance), estimate the number of final concurrent users.

You can also test the server in the following ways to verify that the server has an automatic processing mechanism in various special cases:

1 fault tolerance test

By simulating some abnormal situations (such as sudden power outage of the server, intermittent network, insufficient hard disk space of the server, etc.), verify whether the system can have an automatic processing mechanism to ensure the normal operation of the system or resume operation measures. If there is HA (automatic disaster recovery system), additional tests can be carried out specifically for these automatic protection systems to verify whether they can effectively trigger protection measures.

2 problem troubleshooting test

Through the judgment of the original case or experience, verify and test the modules that have problems or suspected hidden dangers in the system to verify whether the same performance problems will occur in these modules. For example, the memory leak of the upload attachment module, the optimization of this module, the impact of enabling Tivoli performance monitoring on the performance of the OA system, and so on.

The evaluation test is a related test used to obtain the key performance index points of the system. Mainly for no clear expected test results in advance, but to obtain performance indicators under specific stress scenarios (such as transaction response time, maximum number of concurrent users, etc.).

Evaluation of transaction response time: a test activity to obtain the response time of a transaction under specific pressure. The response time of the transaction under this pressure is obtained by simulating the pressure values known or expected to be withstood by the customer during the peak period.

Evaluation of the maximum number of concurrent users for a transaction: a test activity to obtain the maximum number of concurrent users that a transaction can withstand in a particular system environment. By simulating the real environment or directly using the real environment, evaluate the maximum number of concurrent users that the transaction can bear in this environment. The standard threshold should be defined in advance (such as response time, CPU utilization, memory utilization, peak click rate, peak throughput, etc.).

Evaluation of the maximum number of concurrent users of the system: the testing activity carried out to obtain the maximum number of concurrent users that the whole system can bear. Through the pre-analysis of the usage ratio and frequency of the main modules of the project, the proportion of each transaction in the integrated scenario is defined, and the number of concurrent users of each transaction is allocated in a proportional manner. Simulate the real environment or directly use the real environment to evaluate the maximum number of concurrent users that the system can bear in this environment. The decision standard threshold is pre-defined (such as response time, CPU usage, memory utilization, peak click rate, peak throughput, etc.). The value standard is based on the barrel rule (the transaction with the lowest number of concurrency is the concurrency of the whole system).

Evaluate the impact of different database data volume on performance: according to the test of different database data volume, compare the test results, and find that the data volume of each table in the database has a negative effect on transaction performance. It is possible to pre-judge the hidden dangers that may exist after the system has been running for a long time, or when customers of some modules require a large amount of data.

Through the above tests or the actual operation of the user, the performance problem in the system has been found or suspected to exist. It is necessary to reproduce the problem or define the problem through the response test scenario. If possible, you can directly identify the code or module that caused the performance problem. This kind of testing is mainly through testing script scenarios with problems, and can add tools for discovery and detection, such as enabling Tivoli performance monitoring, enabling HeapDump output, Linux resource monitoring commands, etc., and supplemented by manual testing during the running of the scene.

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