Service Discovery in Kubernetes - Combining the Best of Two Worlds

Before jumping to any Kubernetes specifics, let's talk about the service discovery problem in general.

What is Service Discovery

In the world of web service development, it's a common practice to run multiple copies of a service at the same time. Every such copy is a separate instance of the service represented by a network endpoint (i.e. some IP and port) exposing the service API. Traditionally, virtual or physical machines have been used to host such endpoints, with the shift towards containers in more recent times. Having multiple instances of the service running simultaneously increases its availability and helps to adjust the service capacity to meet the traffic demand. On the other hand, it also complicates the overall setup - before accessing the service, a client (the term client is intentionally used loosely here; oftentimes a client of some service is another service) needs to figure out the actual IP address and the port it should use. The situation becomes even more tricky if we add the ephemeral nature of instances to the equation. New instances come and existing instances go because of the non-zero failure rate, up- and downscaling, or maintenance. That's how a so-called service discovery problem arises.

Service discovery problem

Service discovery problem.

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Traefik: canary deployments with weighted load balancing

Traefik is The Cloud Native Edge Router yet another reverse proxy and load balancer. Omitting all the cloud-native buzzwords, what really makes Traefik different from Nginx, HAProxy, and alike is the automatic and dynamic configurability it provides out of the box. And the most prominent part of it is probably its ability to do automatic service discovery. If you put Traefik in front of Docker, Kubernetes, or even an old-fashioned VM/bare-metal deployment and show it how to fetch the information about the running services, it'll automagically expose them to the outside world. If you follow some conventions of course...

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Service Proxy, Pod, Sidecar, oh my!

How services talk to each other?

Imagine you're developing a service... For certainty, let's call it A. It's going to provide some public HTTP API to its clients. However, to serve requests it needs to call another service. Let's call this upstream service - B.

Service A talks to Service B directly.

Obviously, neither network nor service B is ideal. If service A wants to decrease the impact of the failing upstream requests on its public API success rate, it has to do something about errors. For instance, it could start retrying failed requests.

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