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Kafka Basics

Master Apache Kafka for high-throughput event streaming.

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Kafka

Kafka Architecture

Producer → Topic → Partition → Consumer Group

Key Concepts

Concept Description
Topic Message category
Partition Ordered log within topic
Consumer Group Set of consumers sharing load
Offset Position in partition

Key Points

  • Understanding Apache Kafka is essential for production systems
  • Always consider scalability and maintainability
  • Test thoroughly before deploying to production
  • Monitor performance and set up alerting

Common Patterns

  1. Validation: Always validate input at the boundary
  2. Error Handling: Use structured error responses
  3. Logging: Log key events for debugging
  4. Testing: Unit, integration, and load tests
  5. Documentation: Keep docs updated with code changes

Kafka Patterns

Architecture

Producer -> Broker (Topic/Partition) -> Consumer Group

Key Concepts

  • Topic: Message category
  • Partition: Parallel unit
  • Consumer Group: Load balancing
  • Offset: Message position

Best Practices

  • Partition by key
  • Monitor consumer lag
  • Handle rebalancing
  • Use compacted topics

Key Points

  • Understanding Apache Kafka is essential for production systems
  • Always consider scalability and maintainability
  • Test thoroughly before deploying to production
  • Monitor performance and set up alerting

Common Patterns

  1. Validation: Always validate input at the boundary
  2. Error Handling: Use structured error responses
  3. Logging: Log key events for debugging
  4. Testing: Unit, integration, and load tests
  5. Documentation: Keep docs updated with code changes

Practice Problems

0/3solved
Implement Apache Kafka

Design and implement a solution for Apache Kafka in a backend system. Consider scalability, error handling, and production readiness.

Solution
// Apache Kafka implementation
// Key aspects: validation, error handling, logging, testing

public class ApacheKafka {
    // Production-ready implementation
}
Apache Kafka Edge Cases

Identify and handle edge cases for Apache Kafka. What happens under high load, with invalid input, or during failures?

Solution
// Edge case handling:
// 1. Null/empty input -> validation
// 2. High load -> rate limiting, queuing
// 3. Failures -> retries, circuit breaker
// 4. Concurrent access -> locks, idempotency
Apache Kafka Testing Strategy

Write a testing strategy for Apache Kafka. Include unit tests, integration tests, and performance tests.

Solution
// Test plan:
// - Unit: 80% coverage target
// - Integration: API contracts
// - Performance: latency, throughput
// - Chaos: failure injection

Quiz

1. Kafka messages stored in?

Question 1 options

2. Consumer group ensures?

Question 2 options

3. What is the primary purpose of Apache Kafka?

Question 3 options

4. What is a common mistake when implementing Apache Kafka?

Question 4 options

Flashcards

Question

Kafka messages stored in?

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Answer

Topics (split into partitions)

Question

Consumer group?

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Answer

Each message processed once per group

Question

What is Apache Kafka?

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Answer

Apache Kafka is a key concept in backend development.

Question

When to use Apache Kafka?

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Answer

Use Apache Kafka when building production systems that require reliability, scalability, and maintainability.

Question

Apache Kafka best practices

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Answer

Follow SOLID principles, write clean code, test thoroughly, document decisions, and monitor in production.

Revision Notes

Key Takeaways

  • 1.Kafka: topics → partitions → consumer groups
  • 2.Each partition is ordered log
  • 3.Consumer groups for load balancing
  • 4.Offset tracks position

Interview Tips

  • •Understand Kafka architecture
  • •Configure producers and consumers

Cheat Sheet

Kafka

  • Topics → Partitions → Consumer Groups
  • Each partition: ordered log
  • Consumer group: one consumer per message
  • Offset: position tracking