For this pattern, we have the following problem, solution, and solution requirements.

Problem

If observed response times and/or the usage of hardware resources become unacceptably high, it can be very hard to discover the root cause of the problem. For example, we need to be able to analyze hardware resource consumption per microservice.

Solution

To curb this, we add a new component, a monitor service, to the system landscape, which is capable of collecting metrics about hardware resource usage for each microservice instance level.

Solution requirements

The solution requirements are as follows:

It must be able to collect metrics from all the servers that are used by the system landscape, which includes autoscaling servers

It must be able to detect new microservice instances as they are launched on the available servers and start to collect metrics from them

It must be able to provide APIs and graphical tools for querying and analyzing the collected metrics

It must be possible to define alerts that are triggered when a specified metric exceeds a specified threshold value

The following screenshot shows Grafana, which visualizes metrics from Prometheus, a monitoring tool that we will look at in Chapter 20, Monitoring Microservices:

Figure 1.16: Monitoring with Grafana

That was an extensive list! I am sure these design patterns helped you to understand the challenges with microservices better. Next, we will move on to learning about software enablers.