Service Discovery & Configuration Management Questions

Service discovery and configuration management within distributed systems. Covers runtime service lookup patterns (service registries, DNS-based discovery, and Kubernetes service discovery), health checks, load balancing, and centralizing configuration across services. Includes dynamic configuration, feature flags, secret management, versioned configuration, rollout strategies, and related operational concerns such as security, consistency, and observability. Topics span implementations with tools like Consul, Etcd, Zookeeper, as well as cloud-native and IaC approaches for microservices architectures.

HardTechnical

0 practiced

Implement the core algorithm (pseudo-code or Python) for a rolling-config-apply orchestrator that ensures at most N instances are unhealthy at any time during config application. Inputs: list of instances, health_check(instance) -> bool, apply_config(instance) -> restart. Show scheduling strategy, concurrency control to limit in-flight operations, backoff and retry logic for failures, and how you would surface progress and abort criteria.

EasyTechnical

0 practiced

Implement in Python a thread-safe ServiceResolver class that resolves a service name to IP addresses using socket.getaddrinfo and caches results per-service with a configurable TTL. Provide methods: resolve(service_name) -> list of IPs, and invalidate(service_name). The cache should refresh after TTL expiry and avoid duplicate simultaneous DNS queries when multiple threads request the same service concurrently.

HardTechnical

0 practiced

Design a zero-downtime secret rotation process for thousands of running containers that avoids secret leakage and guarantees minimal exposure to old secrets. Explain how you would distribute new secrets, revoke old secrets, coordinate dependent services (databases, third-party APIs), and audit the rotation. Discuss use of short-lived tokens, TLS, key-version headers, and potential race conditions.

MediumTechnical

0 practiced

Implement in Python a thread-safe ClientLB class that accepts a dynamic list of endpoints and supports both round-robin and least-connections strategies. The class should provide choose() returning an endpoint, report_result(endpoint, success) to influence health state, and avoid selecting endpoints marked unhealthy for a configurable cooldown period.

EasyTechnical

0 practiced

Define service discovery in the context of microservices and SRE. Explain the differences between client-side discovery and server-side (proxy) discovery, including who is responsible for load balancing, how health checks are handled, and examples of real-world tools (DNS, Consul, Kubernetes Service). When would you choose each approach and why?

Unlock Full Question Bank

Get access to hundreds of Service Discovery & Configuration Management interview questions and detailed answers.

Join thousands of developers preparing for their dream job.