![]() Because request naming rules produce distinct service requests, each request is independently baselined and monitored for performance anomalies. For example, you can define a naming rule on the test step name (such as TSN in our example below).Īs a result, this rule creates a separate trackable request for each test step. You can also define a web-request naming rule based on request attributes to easily access the monitoring data of the load tests. Once you've tagged requests with relevant HTTP headers, you can use the defined request attributes to filter your monitoring data based on the request attributes you've defined. Of course, any Dynatrace analysis and diagnostic function can be used as well. Following is an overview of some useful approaches you can use to analyze your load tests. Your approach should be based on the type of performance analysis you want to do (for example, crashes, resource and performance hotspots, or scalability issues). There are different ways to analyze the data. ![]() You can also push specific metrics from your load testing tool (throughput, user load, etc.) to Dynatrace via the custom metrics API.įor JMeter, there is a new open-source plugin you can use to push the metrics directly to Dynatrace via the Metrics API. Load test events are also displayed on associated services pages (see example below). ![]() A custom annotation then appears in the Events section on all overview pages of the entities that are defined in the API call (see example below). ![]() When running a load test, you can push additional context information to Dynatrace using the custom event API. Page Context provides information about the document that is loaded in the currently processed page. The Load Test Name uniquely identifies a test execution (for example, 6h Load Test – June 25). This groups a set of test steps that make up a multistep transaction (for example, an online purchase). Load Script Name - name of the load testing script. Test Step Name is a logical test step within your load testing script (for example, Login or Add to cart). Source ID identifies the product that triggered the request (JMeter, LoadRunner, Neotys, or other). Virtual User ID of the unique user who sent the request. The header x-dynatrace-test is used in the following examples with the following set of key/value pairs for the header: The extraction rules can be configured via Settings > Server-side service monitoring > Request attributes. You can use any (or multiple) HTTP headers or HTTP parameters to pass context information. Request attributes enable you to filter your monitoring data based on defined tags. Dynatrace can analyze incoming HTTP headers and extract such contextual information from the header values and tag the captured requests with request attributes. While executing a load test from your load testing tool of choice ( JMeter, Neotys, LoadRunner, etc) each simulated HTTP request can be tagged with additional HTTP headers that contain test-transaction information (for example, script name, test step name, and virtual user ID). Tag test requests and push custom events Tag tests with HTTP headers Test automation is important for continuous delivery and continuous testing. Test automation can automate some repetitive tasks in a formalized testing process already in place or perform additional testing that would otherwise be difficult to do manually. Test automation involves the use of special software (separate from the software being tested) to control the execution of tests and the comparison of actual outcomes with predicted outcomes. By integrating Dynatrace into your existing load testing process, you can stop broken builds in your delivery pipeline earlier.ĭynatrace offers several out-of-the-box integrations with test automation frameworks.
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