Analysis involves different types of metrics to be captured and analysed before sharing with project stakeholders. The analysis result helps to determine the next action to be taken such as if more testing is required to find out the issues/ more resources required for the business requirements/ any defects to be closed before next set of testing/technical & non technical presentations to both IT & Business teams etc.
Below are the different category of metrics used for analysis post each load test.
• Network-specific metrics. This set of metrics provides information about the overall health and efficiency of your network, including routers, switches, and gateways.
Below are the different category of metrics used for analysis post each load test.
• Network-specific metrics. This set of metrics provides information about the overall health and efficiency of your network, including routers, switches, and gateways.
• System-related
metrics. This set of metrics helps you identify the resource utilisation on
your server. The resources being utilised are processor, memory, disk I/O, and
network I/O.
• Platform-specific
metrics. Platform-specific metrics are related to software that is used to
host your application, such as the Microsoft .NET Framework common language
run-time (CLR), ASP.NET-related metrics and J2EE applications
• Application-specific
metrics. These include custom performance counters inserted in your
application code to monitor application health and identify performance issues. We can use custom counters to determine the number of concurrent threads
waiting to acquire a particular lock, or the number of requests queued to make
an outbound call to a Web service. There are several metrics can be monitored using default tool provided in Windows and Linux OS.
• Service-level
metrics. These metrics can help to measure overall application throughput
and latency, or they might be tied to specific business scenarios.
• Business metrics.
These metrics are indicators of business-related information, such as the
number of orders placed in a given time-frame, number of users accessing the application in real world etc.
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