🚀 Apache Kafka & Spring Boot

Mastery & Interview Mind Map

1. 🏗️ Core Architecture

  • Brokers & Clusters: Distributed servers & storage
  • Topics & Partitions: Append-only log partitions
  • Offsets: Sequential record indices
  • KRaft vs Zookeeper: Modern self-managed metadata (KIP-500)

🛡️ Replication & ISR

  • Leader Partition: Handles all reads/writes
  • Follower Partitions: Async data replication
  • ISR Pool: In-Sync Replicas ready for failover

2. ⚙️ Consumer Groups & Rebalancing

  • Cardinality Rule: 1 Partition = Max 1 Active Consumer
  • Idle Consumers: Extra pods wait on standby
  • Eager vs Cooperative Rebalancing: Stop-the-world vs incremental partition reassignment

3. 🍃 Spring Boot 3 Integration

  • KafkaTemplate: Async non-blocking sending with callbacks
  • @KafkaListener: Event consumption & payload extraction
  • Manual Offsets: AckMode.MANUAL_IMMEDIATE for at-least-once safety

4. 🛡️ Resiliency, Retries & DLT

  • @RetryableTopic: Non-blocking asynchronous retries
  • Exponential Backoff: Configurable delay & multipliers
  • @DltHandler: Dead Letter Topic for unprocessable messages
  • ErrorHandlingDeserializer: Poison pill protection

5. 🧬 Advanced Patterns & EOS

  • Ordering: Partition Key hashing for FIFO sequence
  • Transactions (EOS): Atomic read-process-write loops
  • Avro & Schema Registry: Centralized schema validation & compatibility

6. 🎯 Key Interview Scenarios

  • Pod Crashes: Uncommitted offset duplication & idempotency
  • Consumer Lag: Partition scaling & thread concurrency
  • Schema Evolution: Adding defaults for backward compatibility