Web Load and Stress Testing Tool Proxy Sniffer™    Deutsch    English Engineering Office David Fischer GmbH - Switzerland
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	Screenshots Recording of Load Tests Universal HTTP/S Proxy-Recorder Supported Authentication Methods Automatic Protection from "false positive" Measurement Results Integrated Web Crawler Self-Written Definition Files   Post-Processing of the Recording CGI and HTML Form Parameter Dynamically Exchanged Session Parameters Input Files User Input Fields XML and SOAP Data   Creation and Starting of Load Test Programs Generating a Load Test Program Starting of Load Tests Proxy Sniffer Cluster Technology Generating Load from the Amazon Cloud   Real-Time Monitoring and Real-Time Error Analyses Real-Time Overview Window Response Times per Web Page Detail per URL Statistical Overview Error Overview Error Detail Email and SMS Alert Notifications   Measurement Results per Test Run Results per URL Call (Overview) Results per URL Call (Details) Response Time per Page Users Waiting for Response TCP Socket Connect Time SSL Cache Efficiency   Comparison of Test Runs Response Time Comparison Performance Comparison Error Rate Comparison   Load Curves Overall Load Curves Response Time per Page Load Curves Response Time per URL Load Curves   Miscellaneous Features PDF Reports Load Test Plug-In Wizard Integration with dynaTrace Command Line Support   Note: The screenshots shown here contain only a selection of the Proxy Sniffer product functionalities.   A complete description of all product features is provided in the User's Guide		Creation and Starting of Load Test Programs  Previous Screenshot  Next Screenshot Proxy Sniffer Cluster Technology Combining several Exec Agents to a Load-Releasing Cluster can be done with some few mouse clicks. After that a load test program can be started on a cluster in the same way as it would run only on one Exec Agent: The load is automatically distributed to the cluster members. In cases where the load test program uses Input Files, you are asked - for each Input File - if you wish to split the content of the Input File. This can be useful, for example, if the Input File contains user accounts (usernames/passwords) but the web application does not allow duplicate logins: The statistics result of a cluster job contains the consolidated (merged) measurements of all cluster members:
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