A client typically identifies connected servers through service discovery mechanisms, configuration files, or network protocols designed to share server information. The exact method depends on the system architecture, but common approaches include querying a registry, using DNS-based lookups, or relying on preconfigured server lists. For example, in a microservices setup, a client might consult a service discovery tool like Consul or etcd to find available servers. These tools maintain a real-time list of registered servers and their network locations (IP addresses and ports), allowing clients to dynamically discover services without hardcoding details. This ensures flexibility as servers scale up, down, or fail.
One practical example is DNS-based discovery. Clients can resolve a domain name (e.g., api.example.com) to a list of server IPs using DNS SRV or A records. For instance, Kubernetes services use DNS to expose endpoints: a client querying backend-service.namespace.svc.cluster.local receives the IPs of all pods running that service. Similarly, cloud platforms like AWS provide Elastic Load Balancers (ELBs) that assign a DNS name to distribute traffic across servers. Clients connect to the ELB’s DNS name, which internally routes requests to healthy instances. This abstracts the complexity of tracking individual servers, especially in auto-scaling environments where server counts change frequently.
Alternatively, clients might use static configuration files or environment variables containing server addresses. For example, a client application could read a servers.json file listing IPs like ["10.0.0.1:8080", "10.0.0.2:8080"]. While simple, this approach lacks dynamism and requires manual updates when servers change. Hybrid solutions, such as combining configuration files with periodic API checks (e.g., querying a central server every 30 seconds), offer a middle ground. Tools like Netflix Eureka exemplify this: servers register themselves with Eureka, and clients fetch the server list from Eureka’s API, caching it temporarily. This balances reliability with adaptability, ensuring clients stay aware of current server states without constant network overhead.