As a forthcoming, ubiquitous layer of cloud native infrastructure, service meshes offer deep and uniform control and visibility into the topology and state of ephemeral microservices. Managing the myriad configurations of cloud native infrastructure is greatly facilitated by a service mesh, but succinctly summarizing and characterizing the performance of your service mesh in context of your unique workloads and your infrastructure of choice is a challenge unto its own.
We explore how to model your service mesh topology and optimize for your ideal configuration in context of how much you value properties of resiliency, performance, throughput, latency, and so on before you deploy to production. Readers will understand how distributed performance analysis offers unique insights on the behavior of microservices and their efficiency of operation, see examples of how common types of workloads perform under specific service mesh functions, and be empowered with analytical tooling that can be used to make optimized configurations.
