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.

EasyTechnical

0 practiced

Explain the difference between general configuration values and feature flags. When should a capability be implemented as a feature flag versus a normal configuration parameter? Discuss lifecycle considerations: rollout, rollback, targeting, observability for flags, and operational responsibilities for stale flags.

EasyTechnical

0 practiced

Why should secrets not be stored in plain configuration files or version control? Describe a secure secrets management approach for containerized microservices, covering short-lived vs long-lived secrets, authentication to a secrets store, audit logging, and how to revoke or rotate secrets safely.

HardTechnical

0 practiced

Explain leader election algorithms such as the Bully algorithm and Raft. Discuss their safety and liveness properties, message complexity, and why Raft's leader-based replication model is often used for configuration stores. In what scenarios would you prefer application-level leader election versus relying on a consensus-backed store?

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.

MediumSystem Design

0 practiced

Design a secrets distribution architecture for containerized workloads that supports key rotation without requiring container restarts. Constraints: thousands of containers, least-privilege access, audit logs, node-level caching, and low-latency retrieval. Consider using Vault, sidecars, node agents, and Kubernetes secrets; explain trade-offs for each.

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