Increasingly complex applications are relying on microservices to remain scalable and efficient. Kubernetes provides the perfect environment for microservices and makes them compatible with Kubernetes tool components and functions. When each part of the application is placed in a container, the overall system is more scalable.

Microservices and containers also work in a way that fits into the current CI/CD workflow, where there is no need to shut down the entire system for updates because each microservice (container) can be updated separately. However, this would shorten the lifetime of the container or POD, and its IP address would change.

During the life cycle of the application and its microservices, some of these parts can go wrong and not run, leading to unexpected conditions and, quite possibly, IP address changes. At this point, the service grid can help reroute applications and improve security.

Dynamic IP Address Allocation

Before we understand how to manage services and how to efficiently establish service discovery, we must understand the primary challenge of service discovery: IP assignment. Specifically, the way Kubernetes dynamically assigns IP addresses to pods and services.

We could certainly define IP addresses for individual pods and services, but doing so would limit the scalability of the Kubernetes environment. By default, any resource gets a new IP address every time the environment restarts the cluster, POD, or service, so we can only use a unique name for the service.

To overcome this, you can use two methods. First, look at the service’s environment variables. Similar to the way Docker allows containers to communicate with each other, Kubernetes allows you to scan environment variables injected into containers.

If you have a service running on multiple ports, you can run kubectl exec memcached-rm58b en and do a quick grep on the service name, which will show you the available IP addresses and ports assigned to the service. However, this is not the most efficient way to manage service discovery. Because the services that depend on in this approach must exist before the POD is started, otherwise they would not appear in the environment variable.

Kube – DNS rescue

In the long run, the second approach described below is generally considered more efficient, thanks to Kubernetes’ plug-in Kube-DNS. Let’s first understand what kube-DNS is. As the name suggests, Kube-DNS is an add-on that acts as an internal DNS parser. It is a database containing key-value pairs for lookups. The key is the name of the Kubernetes service and the value is the IP address on which the service runs.

Kube-dns relies only on namespaces and does not need to configure PODS and services in other ways, or even modify the configuration files of clusters, pods, and services for DNs-based service discovery.

Kube-dns also supports advanced DNS queries and DNS policies. For example, you can configure each Pod to follow a different DNS property from the node it runs on. This means that you can customize how pods communicate with each other using a private DNS space.

This approach goes a step further by configuring DNS policies on a per-POD basis. All you need to do is set the node DNS policy to “None” and manually configure each Pod to meet your specific requirements.

Label and Selectors

As mentioned earlier, you can use parameters to further influence how pods communicate with each other and with services. Kubernetes service discovery supports the use of labels and selectors for advanced controls, especially when managing complex clusters. You can assign labels to components and containers for easy identification.

The way Kubernetes handles labels and selectors makes these arguments easier to use. In essence, they are simple key-value parameters added to the metadata. That is, they don’t actually affect the rest of the system or the environment, and you can freely use labels and selectors across pods and services (and even across nodes) in complex environments.

Next, we’ll use the replica controller. Again, as the name implies, it is a tool to make Kubernetes’ systems highly available and scalable. You can use the replica controller to create and manage pod replicas and maintain high availability. At the same time, you can easily delete the POD and its copy at once.

Service Mesh and highly elastic scaling system

To complete the setup, we need to use advanced service discovery methods that are relevant to our existing infrastructure and platform. AWS Cloud Map is a very interesting example. Application resources in the AWS environment can have unique names, and those resources are automatically mapped by the Cloud Map. Once they are registered, the service automatically becomes discoverable and the registration process takes place immediately after the Pod or service is started.

Now there is a new approach that makes it easy to manage complex arrays of microservices by using a service grid. The service grid standardizes the way services and PODS communicate. Using a service grid to maintain Pod visibility in your environment is a perfect solution if you are creating a highly available system.

However, if your environment is on AWS, you can leverage its service grid capabilities in the form of AWS App Mesh. It automatically handles everything, including traffic routing, traffic balancing, calls, and circuit breaking using API calls. All microservices are able to enable API Mesh to simplify administration. Because this tool is part of the Amazon ecosystem, it is automatically used with other tools like Amazon EKS, IAM, and so on.

Kubernetes service discovery makes the container platform powerful and flexible, and methods such as service grid undoubtedly make Kubernetes service discovery more powerful through standardization. As long as the service is running, the correct API call can pass data back and forth before each Pod without interruption.