The Art of Service Discovery in Microservices: Advanced Techniques for Managing Distributed Systems




May 23, 2023

The Art of Service Discovery in Microservices: Advanced Techniques for Managing Distributed Systems

Today’s complex applications are built on the foundations of serverless computing and microservices architectures. But since the number of instances of a service and their location change dynamically, it is important to know what and where these instances are to allow requests to arrive at the target microservice. This is where service discovery comes in. Read on as we talk about how service discovery acts as an advanced technique for managing distributed systems.

The Importance of Service Discovery

As software products become increasingly complex, making frequent changes or updating features in the traditional way is no longer possible. Microservices architectures overcome this challenge by dividing the application architecture into loosely coupled services that communicate with each other using different protocols.

But one of the primary challenges with microservices architectures is their ability to discover and interact with different services. The distributed characteristics of microservices architecture make it extremely hard for services to communicate — while also causing roadblocks in checking the health of systems and announcing when new applications become available.

Every microservice needs to know the IP location of the service it communicates with. But with current microservices architectures expanding across different environments, this becomes extremely difficult. Employing a service discovery mechanism allows different microservices to determine the location of a service, even as it changes dynamically.

Let’s take an example. Imagine you are building a product that needs to invoke an AI service. To make the request, the code needs to know the exact location of the service instance. In a traditional monolithic application, finding this location is straightforward as they are relatively static. But in a modern, cloud-based microservices application, this is much more difficult. Since service instances have dynamically assigned network locations, they keep changing with new features and updates. Service discovery via platforms like Kubernetes or Amazon ECS makes it easy for containerized services to discover and connect.

By creating and managing a registry of service names, service discovery allows requests to easily find services in the code, specify health check conditions, and ensure only healthy service endpoints are returned. Event-based, infrastructure-less computing makes service registration extremely affordable, quick, reliable, and maintenance-free. You can also ensure a zero-downtime application version update by making use of the load balancer for frequent health checks.

Mastering the Art of Service Discovery

The key advantage microservices bring to large distributed systems is the ability to create new instances of each service to meet shifting loads, respond to failures, and roll out upgrades. Unlike the traditional monolith approach, with a microservices architecture, you can scale different services at different rates without the risk of services becoming coupled.

For microservices to discover each other intelligently, writing code that links different locations together isn’t practical. Since the location of microservices can change abruptly, tying code directly to those locations can cause services to fail as the architecture changes. Given how rapidly microservices evolve, streamlining service discovery is a must.

Here’s how you can master the art of service discovery for large distributed systems:

Understand the Difference Between Client-Side and Server-Side Discovery Patterns

When it comes to service discovery, you have two options at hand. You can either use the client-side discovery pattern where the client checks for the network locations of available service instances in the service registry and determines the load balancing requests across them. Or you can use the server-side discovery method where the client requests a service via a load balancer. The load balancer checks the service registry and directs each request to an available service instance.

Continuously Update the Service Registry

If you want to keep track of the locations of all your instances in a distributed environment, you need to continuously update the service registry. Such updating ensures every new service that comes online (or goes offline) is recorded, making it easy for the request to be routed to the right service at the right location.

Choose the Right Registration Technique

For large distributed systems, enabling self-registration can make each microservice responsible for adding itself to the service registry when it comes online and removing itself when it goes offline. You could also opt for Kubernetes-enabled third-party registration techniques to standardize and automate communication between services.

Embrace Automation

Since the locations of your service instances constantly change – by the hour or even by the minute – recording these locations in a config file is not feasible. To accurately route requests to a particular service, an automated solution can easily and quickly find the address of the service instance it should use – even as instances are added and removed on the fly.

Summing Up

In large distributed systems, ensuring timely requests of services doesn’t come easy. With new features, updates, and changes happening frequently in a microservices-based architecture, these dynamically assigned network locations demand an effective approach to service discovery.

The right approach to service discovery can ease the process of detecting devices and services on distributed networks. By connecting services through a common language, service discovery streamlines connection without any manual intervention. Master the art of service discovery today and ensure your distributed systems can respond to changing needs with speed, accuracy, and agility. Connect with our experts to learn more.

This article first appeared here.