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8. Microservices, Containers, and Deployment Tools

Compare monolith, SOA, and microservices while reviewing Docker, Kubernetes, and Spring Boot.

Java Backend Interview Prep
2. Backend Architecture & Data
May 29, 2026
18
A

Architecture Styles

StyleMain Idea
MonolithOne deployable application containing most features
SOAServices communicate, often with enterprise-level shared infrastructure
MicroservicesSmall autonomous services modeled around business capabilities

Microservice Challenges

Microservices improve independent deployment and scaling, but they add distributed-system complexity. Common challenges include service discovery, observability, configuration management, debugging, network failures, data consistency, and deployment automation.

Common Tools

Docker packages a service and its dependencies into a portable container image. Kubernetes orchestrates containers with scheduling, scaling, service discovery, and self-healing. Spring Boot helps Java teams build production-ready services quickly.

Interview Framing

Do not present microservices as automatically better. Explain that they help when organizational and scaling needs justify the operational cost.

Interview Scenario Practice

Scenario 1: Split a Monolith

Scenario: A monolith has user, order, payment, and notification features. The team wants microservices.

Strong answer: Split by business capability, not by technical layer. Start with clear boundaries such as Orders, Payments, and Notifications, then define APIs, data ownership, and deployment ownership.

Why it works: Microservices need autonomy. A service that owns no data or business capability becomes distributed coupling.

Common mistake: Creating separate controller, service, and repository services. That turns local method calls into network calls without business value.

Scenario 2: Debugging Across Services

Scenario: A checkout request fails after calling four services.

Strong answer: Use centralized logs, correlation IDs, metrics, traces, and clear service-level dashboards.

Why it works: Distributed systems need observability because the failure path crosses process boundaries.

Common mistake: SSHing into individual containers and manually reading logs as the primary debugging strategy.

Scenario 3: Service Deployment

Scenario: One service needs a new version while others should continue running.

Strong answer: Containerize each service, deploy independently, and use backward-compatible APIs or versioning during rollout.

Why it works: Independent deployment is one of the main reasons microservices can help larger teams.

Common mistake: Requiring every service to deploy together, which recreates monolith-style release coupling.

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