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Monitoring
Monitoring requires a new section to be added to the application config file:
<configSections>
<section name="monitoring" type ="paramore.brighter.commandprocessor.monitoring.Configuration.MonitoringConfigurationSection, Brighter.commandprocessor" allowLocation ="true" allowDefinition="Everywhere"/>
</configSections>
The monitoring config can then be speicified later in the file:
<monitoring>
<monitor isMonitoringEnabled="true" instanceName="ManagementAndMonitoring"/>
</monitoring>
This enables runtime changes to enable/disable emitting of monitoring messages.
Each handler that requires monitoring must be configured in two stages, a Handler attribute and container registration of a MonitorHandler for the given request:
For example, given:
- TRequest - a Brighter Request, inheriting from IRequest
- TRequestHandler - handles the TRequest, inheriting IHandleRequest <TRequest>
The following attribute must be added to the Handle method in the handler, TRequestHandler:
[Monitor(step:1, timing:HandlerTiming.Before, handlerType:typeof(TRequestHandler))]
Please note the step and timing can vary if monitoring should be after another attribute step, or timing should be emitted after.
The following additional handler must be registered in the application container (where
MonitorHandler<T> is a built-in Brighter handler):container.Register<TRequest, MonitorHandler<TRequest>>
A message is emitted from the Control Bus on Handler Entry and Handler Exit. The following is the form of the message:
{
"Exception": null, // or Exception message
"EventType": "EnterHandler or ExitHandler",
"EventTime": "2016-06-21T15:48:26.1390192Z",
"TimeElapsedMs": 0 or Duration,
"HandlerName": "...",
"HandlerFullAssemblyName": "...",
"InstanceName": "ManagementAndMonitoring",
"RequestBody": "{\"Id\":\"dc32b35f-bc75-4197-9178-c8310a63e4fb\", ... }",
"Id": "048cc207-e820-40fa-b931-55b60203fbc2"
}
Messages can be processed from the queue and interated with your monitoring tool of choice, for example Live python consumers emitting to console or logstash consumption to the ELK stack using relevant plugins to provide performance raditators or dashboards.