3 pages from the guide: the cover, the contents (100 questions in 8 sections) and one complete question with its answer, code and interview tips.
Kafka shows up in most backend interviews that mention microservices, and the questions go well past "what is a topic": how acks and min.insync.replicas decide durability, why a consumer group rebalances, how to avoid duplicates after a restart, and how Spring Kafka retries and dead-letters a failing message. This guide answers 100 questions in eight sections, from Kafka fundamentals and producers to consumer groups, delivery semantics, Spring for Apache Kafka, schemas, operations and five production scenarios.
100 questions in 8 sections, 89 code examples in a 113-page PDF (2026 edition).
150+ frequently asked microservices interview questions with explanations, hands-on examples and mock interviews.
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Read one section at a time and answer each question aloud before opening the answer. Then work through the five scenarios and sketch your own producer and consumer configuration for a topic you use at work, explaining each setting.
Write the business change and an outbox row (the event to publish) in one local database transaction. A separate relay reads new outbox rows and publishes them to Kafka, then marks them sent. Either mechanism, a polling publisher or change data capture (for example Debezium), gives at-least-once publishing without a distributed transaction.
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It covers this topic in depth. It is one topic from the TechTribers Java Interview Series, which has all 23 parts (1,200+ questions) in one bundle.
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60 microservices scenario questions: boundaries, sync vs async, sagas and the outbox, retries and circuit breakers, tracing, safe deploys, mTLS, poison messages and duplicate payments.
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A self-paced data engineering program from foundations to job-ready skills: SQL, Python, ETL, Airflow and projects.
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