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Connect Windows computers to the Azure Monitor service



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Connect Windows computers to the Azure Monitor service
https://learn.microsoft.com/azure/azure-monitor/platform/agent-windows
 

Logging What You Mean: Using the Semantic Logging Application Block
https://learn.microsoft.com/previous-versions/msp-n-p/dn440729(v=pandp.60)
 

Splunk
Official site. 
https://www.splunk.com/
 

EventSource Class
API for events tracing for Windows (ETW) 
https://learn.microsoft.com/dotnet/api/system.diagnostics.tracing.eventsource
 
Orchestrate microservices and multi-container 
applications for high scalability and availability 
Using orchestrators for production-ready applications is essential if your application is based on 
microservices or simply split across multiple containers. As introduced previously, in a microservice-
based approach, each microservice owns its model and data so that it will be autonomous from a 
development and dep
loyment point of view. But even if you have a more traditional application that’s 
composed of multiple services (like SOA), you’ll also have multiple containers or services comprising a 
single business application that need to be deployed as a distributed system. These kinds of systems 
are complex to scale out and manage; therefore, you absolutely need an orchestrator if you want to 
have a production-ready and scalable multi-container application. 
Figure 4-23 illustrates deployment into a cluster of an application composed of multiple microservices 
(containers). 


67 
CHAPTER 3 | Architecting container and microservice-based applications 
Figure 4-23. A cluster of containers 
You use one container for each service instance. Docker containers are “units of deployment” and a 
container is an instance of a Docker. A host handles many containers. It looks like a logical approach. 
But how are you handling load-balancing, routing, and orchestrating these composed applications? 
The plain Docker Engine in single Docker hosts meets the needs of managing single image instances 
on one host, but it falls short when it comes to managing multiple containers deployed on multiple 
hosts for more complex distributed applications. In most cases, you need a management platform 
that will automatically start containers, scale out containers with multiple instances per image, 
suspend them or shut them down when needed, and ideally also control how they access resources 
like the network and data storage. 
To go beyond the management of individual containers or simple composed apps and move toward 
larger enterprise applications with microservices, you must turn to orchestration and clustering 
platforms. 
From an architecture and development point of view, if you’re building large enterprise composed of 
microservices-
based applications, it’s important to understand 
the following platforms and products 
that support advanced scenarios: 

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