Apache Kafka Tutorial 0/111 lessons ~6 min read Lesson 51

    Leader Election

    What is Leader Election?

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    Focus
    9 guided sections
    Practice signal
    Examples included
    Career prep
    Foundation builder

    Introduction

    What is Leader Election? Leader election chooses a replica to serve reads/writes for a partition when the current leader fails or leadership is moved.

    Understanding the topic

    What happens — Leader Election:

    • Plan partitions and replication factor.
    • Configure retention and compaction.
    • Monitor ISR, lag, disk.
    • Scale brokers and partitions with load.
    TermDescription
    Replication factorCopies per partition.
    ISRIn-sync replica set.
    Retention.msTime to keep records.
    Log compactionKeep latest per key.

    Visual explanation

    Pipeline view:

    text
    Topic partitions
    replicas across brokers
    ISR health
    disk + network + controller
    SLO dashboards

    Step-by-step explanation

    1. Create/configure — kafka-topics or API.
    2. Replicate — Followers stay in ISR.
    3. Observe — Metrics and alerts.
    4. Scale — Brokers/partitions/consumers.

    Informative example

    Example:

    bash
    kafka-topics --bootstrap-server localhost:9092 --create --topic leader-election --partitions 6 --replication-factor 3
    kafka-console-producer --bootstrap-server localhost:9092 --topic leader-election
    kafka-console-consumer --bootstrap-server localhost:9092 --topic leader-election --from-beginning
    kafka-consumer-groups --bootstrap-server localhost:9092 --describe --group leader-election-service

    Execution workflow

    1Leader Election workflow
    1 / 4

    Create/configure

    kafka-topics or API.

    Best practices

    • Use replication factor 3 for critical topics.
    • Set min.insync.replicas with acks=all.
    • Alert on under-replicated partitions, offline partitions, disk usage, and lag.
    • Document topic ownership and cleanup policy.

    Common mistakes

    • Changing partitions without understanding ordering impact.
    • Ignoring hot partitions caused by skewed keys.
    • Letting retention grow until disks become the outage.

    Summary

    Leader Election — Operate Kafka through SLOs: durability, availability, latency, lag, disk headroom, and recovery time.

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