A practical roadmap for coding, problem solving, and communication under pressure.

Patterns, trade-offs, and a repeatable framework to tackle open-ended design prompts.

Craft a concise narrative that connects your experience to the role and sets the tone.

End-to-end preparation: study plan, tooling, mock interviews, and on-site tactics.

Deep-dive into performance, concurrency, GC tuning, and modern language features.

What’s new in Java 21: virtual threads, pattern matching, records, and more.

Key LTS features: sealed classes, records, switch expressions, and performance notes.

From List vs Set to HashMap internals—complexity, contracts, and best practices.

Stream pipelines, stateless vs stateful ops, collectors, and performance pitfalls.

Threads, executors, locks vs atomics, and designing safe concurrent components.

Class loading, heap vs stack, garbage collectors, and diagnosing memory issues.

Encapsulation, inheritance, composition, and when to prefer one over the other.

Core Spring Boot concepts: auto-configuration, starters, profiles, and testing.

Production patterns: configuration, observability, performance, and resilience.

Authentication, authorization, filters, method security, and common pitfalls.

Entity mapping, repositories, transactions, and performance tuning techniques.

Designing clean controllers, error handling, validation, and API versioning.

Service boundaries, configuration, discovery, resilience, and observability.

Latest features, migration tips, and real-world upgrade considerations.

Constructor vs field injection, scopes, bean lifecycles, and configuration.

Cross-cutting concerns with proxies, pointcuts, and advice types.

Core AWS services, architecture patterns, and cost/performance trade-offs.

Azure building blocks, networking, security, and deployment strategies.

GCP primitives, data services, and design choices across common architectures.

Practice scenarios covering scale, reliability, and trade-off analysis.

Complex challenges: multi-region, cost modeling, and failure domain isolation.

Service decomposition, contracts, versioning, and synchronous vs async patterns.

CAP, consensus, leader election, idempotency, and data partitioning.

Events, topics, ordering, retries, and designing for at-least-once semantics.

Resource modeling, status codes, pagination, and robust error handling.

Normalization vs denormalization, indexing, and transactional integrity.

Horizontal vs vertical scaling, caches, queues, and backpressure strategies.

Redundancy, failover, quorum, and minimizing blast radius.

Producers, consumers, partitions, consumer groups, and delivery guarantees.

Cache-aside vs write-through, eviction policies, and consistency trade-offs.

Algorithms, health checks, sticky sessions, and L4 vs L7 concerns.