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Core technical concepts that come up in every interview, across all languages and tracks. Each topic aggregates questions from every relevant domain — so whether you're a Java backend engineer or a Python ML developer, you get concept-level mastery that transfers everywhere.
How systems are structured, decomposed, and designed for scale
Scalability, availability, consistency, load balancing, databases at scale
Service decomposition, communication patterns, sagas, service mesh
CAP theorem, consensus, replication, fault tolerance, CRDTs
Events, commands, CQRS, event sourcing, outbox pattern
Hexagonal, onion, dependency rule, ports and adapters
Entities, value objects, aggregates, bounded contexts, ubiquitous language
Databases, caching, and data management patterns
ACID, indexes, query optimization, sharding, replication
Cache strategies, eviction policies, invalidation, distributed caching
Consistency, availability, partition tolerance — trade-offs explained with real systems
How services communicate and expose functionality
Protecting systems and ensuring they stay up
Development workflows, testing, and operational excellence
CI/CD, infrastructure as code, monitoring, SRE, on-call practices
Unit, integration, contract, e2e, TDD, test pyramids
Profiling, bottlenecks, JVM tuning, async patterns, batching
Every topic appears in your domain prep dashboard. Select your tech stack and get these concepts mapped to your interview path — with progress tracking and related Q&A.