Update resilient-high-availability-microservices.md

docs/architecture/microservices/architect-microservice-container-applications/resilient-high-availability-microservices.md

@@ -36,7 +36,7 @@ Logs provide information about how an application or service is running, includi
 
 In monolithic server-based applications, you can write logs to a file on disk (a logfile) and then analyze it with any tool. Since application execution is limited to a fixed server or VM, it generally isn't too complex to analyze the flow of events. However, in a distributed application where multiple services are executed across many nodes in an orchestrator cluster, being able to correlate distributed events is a challenge.
 
-A microservice-based application should not try to store the output stream of events or logfiles by itself, and not even try to manage the routing of the events to a central place. It should be transparent, meaning that each process should just write its event stream to a standard output that underneath will be collected by the execution environment infrastructure where it's running. An example of these event stream routers is [Microsoft.Diagnostic.EventFlow](https://github.com/Azure/diagnostics-eventflow), which collects event streams from multiple sources and publishes it to output systems. These can include simple standard output for a development environment or cloud systems like [Azure Monitor](https://azure.microsoft.com/services/monitor//) and [Azure Diagnostics](/azure/azure-monitor/platform/diagnostics-extension-overview). There are also good third-party log analysis platforms and tools that can search, alert, report, and monitor logs, even in real time, like [Splunk](https://www.splunk.com/goto/Splunk_Log_Management?ac=ga_usa_log_analysis_phrase_Mar17&_kk=logs%20analysis&gclid=CNzkzIrex9MCFYGHfgodW5YOtA).
+A microservice-based application should not try to store the output stream of events or logfiles by itself, and not even try to manage the routing of the events to a central place. It should be transparent, meaning that each process should just write its event stream to a standard output that underneath will be collected by the execution environment infrastructure where it's running. An example of these event stream routers is [Microsoft.Diagnostic.EventFlow](https://github.com/Azure/diagnostics-eventflow), which collects event streams from multiple sources and publishes it to output systems. These can include simple standard output for a development environment or cloud systems like [Azure Monitor](https://azure.microsoft.com/services/monitor//) and [Azure Diagnostics](/azure/azure-monitor/platform/diagnostics-extension-overview). There are also good third-party log analysis platforms and tools that can search, alert, report, and monitor logs, even in real time, like [Splunk](https://www.splunk.com/goto/Splunk_Log_Management?ac=ga_usa_log_analysis_phrase_Mar17&_kk=logs%20analysis&gclid=CNzkzIrex9MCFYGHfgodW5YOtA) or [Middleware](https://middleware.io).
 
 ### Orchestrators managing health and diagnostics information