Monitoring the outbound may seem exaggerated, but it is very useful. Yes, for example. B, several instances of services A and B call several instances of service C, the combination of extensive monitoring of instance service C and supervision of instances A and B gives us a beautiful image. We can better locate important sources and targets of traffic and identify noisy neighbors, routing problems or slow instances. For now, we are sticking to this rather light set of requirements for microservices and we see how it goes. The most important thing is that if ALS is known for any service in a product, then ALS can be defined more precisely for the product in general. Our goal was to define a standard base that all Good Eggs microservices will follow to ensure that our system as a whole is efficient and reliable. Our guiding principles were: with a stable API, ALS and some performance tests to prove that our service can meet ALS, the service is ready for prime time. For the API, an API contract or API description has been defined, including functional interface specifications (i.e. query and response messages with settings) of operations. The dynamic behavior of API operations during the call has not yet been accurately articulated in terms of QoS (Quality-of-Service) quality and quality.
In addition, service support during its life cycle has not been accurately articulated (e.g.B. guaranteed lifespan and average repair time). The model allows us to perform a statistical analysis of a system. To get visibility at the individual message level, distributed tracking must be added. In-depth monitoring shows us how others use our service and how our service responds. It also has the inevitable effect of directing you to suppliers who are willing to respond to ALS discussions rather than talking to suppliers with more important characteristics: a large capacity, a vast ecosystem and a wide range of services that allow you to create innovative applications. Of course, each instance of a service has a state control and creates metrics on its internal state to facilitate troubleshooting. In other words, each instance of each service is a white box for the owners of the service, but it is a black box for all the others.