In-sync replicas (ISR) in Kafka - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is an In-sync Replica (ISR) in Kafka?

An In-sync Replica (ISR) is a Kafka broker that has fully caught up with the leader's data for a partition. It means the replica has all the latest messages and is ready to take over if the leader fails.

beginner

Why is ISR important in Kafka?

ISR ensures data durability and availability. Only replicas in the ISR can be elected as leaders, which guarantees that no data is lost during failover because these replicas have the latest data.

intermediate

How does a replica join or leave the ISR?

A replica joins the ISR when it catches up with the leader's data within a configured time. It leaves the ISR if it falls behind or becomes unresponsive for too long.

intermediate

What happens if all replicas leave the ISR except the leader?

If all replicas leave the ISR except the leader, Kafka cannot guarantee data durability. The leader continues serving data but the risk of data loss increases if it fails before replicas catch up.

advanced

How does Kafka use ISR to maintain consistency?

Kafka only commits messages when all replicas in the ISR have acknowledged them. This ensures that committed data is safely stored on all in-sync replicas, maintaining consistency.

What does ISR stand for in Kafka?

A Internal Sync Resource

B Instant Sync Replication

C In-sync Replicas

D Independent Sync Replica

ISR stands for In-sync Replicas, which are replicas fully caught up with the leader.

When does a replica leave the ISR?

A When it falls behind or is unresponsive

B When it receives new data

C When it becomes the leader

D When it catches up with the leader

A replica leaves the ISR if it falls behind the leader or becomes unresponsive for too long.

Why does Kafka commit messages only after ISR replicas acknowledge them?

A To ensure data durability and consistency

B To reduce network traffic

C To improve performance

D To allow replicas to lag

Committing messages after ISR replicas acknowledge ensures data is safely stored and consistent.

What risk increases if only the leader remains in the ISR?

A Faster data replication

B Data loss if leader fails

C More replicas joining ISR

D Automatic leader election

If only the leader is in ISR, data loss risk increases if the leader fails before replicas catch up.

Which Kafka component decides the ISR membership?

A Kafka Producer

B Kafka Controller

C Kafka Consumer

D Kafka Broker Leader

The Kafka Broker Leader (partition leader) manages ISR membership by tracking replica states.

Explain what In-sync Replicas (ISR) are and why they matter in Kafka.

Think about how Kafka keeps data safe and available.

Describe the process of how a replica joins or leaves the ISR in Kafka.

Consider what makes a replica 'in-sync' or not.

Practice

1. What does In-sync replicas (ISR) mean in Kafka?

easy

A. Replicas that are offline

B. Replicas that never receive data

C. Replicas that have the latest data from the leader

D. Replicas that only store old data

Solution

1. Step 1: Understand the role of ISR

   ISR are replicas that keep up-to-date with the leader's data.

2. Step 2: Compare options

   Only Replicas that have the latest data from the leader correctly describes ISR as replicas with the latest data.

3. Final Answer:

   Replicas that have the latest data from the leader -> Option C

4. Quick Check:

   ISR = Latest data replicas [OK]

Hint: ISR means replicas fully caught up with leader data [OK]

Common Mistakes:

• Thinking ISR includes offline replicas
• Confusing ISR with replicas that lag behind
• Assuming ISR means replicas with old data

2. Which Kafka configuration controls the minimum number of ISR replicas required to acknowledge a write?

easy

A. replica.fetch.max.bytes

B. min.insync.replicas

C. max.insync.replicas

D. offsets.retention.minutes

Solution

1. Step 1: Identify configuration related to ISR acknowledgments

   The setting min.insync.replicas defines the minimum ISR count for write success.

2. Step 2: Eliminate unrelated options

   Other options control fetch size or retention, not ISR acknowledgments.

3. Final Answer:

   min.insync.replicas -> Option B

4. Quick Check:

   Minimum ISR replicas = min.insync.replicas [OK]

Hint: min.insync.replicas sets minimum ISR for writes [OK]

Common Mistakes:

• Confusing min.insync.replicas with max.insync.replicas
• Choosing unrelated configs like offsets.retention.minutes
• Assuming replica.fetch.max.bytes controls ISR count

3. Given a Kafka topic with 3 replicas and ISR = [replica1, replica2], what happens if replica2 falls behind and leaves ISR?

medium

A. Only replica1 remains in ISR; leader continues with one ISR

B. Leader stops producing until replica2 catches up

C. All replicas are removed from ISR

D. Replica2 becomes the new leader immediately

Solution

1. Step 1: Understand ISR behavior when a replica falls behind

   If a replica lags, it is removed from ISR, leaving others in ISR.

2. Step 2: Analyze leader and ISR state

   The leader continues with remaining ISR replicas; it does not stop or change leader immediately.

3. Final Answer:

   Only replica1 remains in ISR; leader continues with one ISR -> Option A

4. Quick Check:

   Lagging replica leaves ISR, leader continues [OK]

Hint: Lagging replica leaves ISR; leader stays with remaining ISR [OK]

Common Mistakes:

• Thinking leader stops producing when ISR shrinks
• Assuming all replicas leave ISR together
• Believing lagging replica becomes leader immediately

4. You see this error in Kafka logs: "Not enough replicas are in ISR to satisfy min.insync.replicas". What is the likely cause?

medium

A. The consumer group is not committed

B. The leader replica is offline

C. The topic has zero partitions

D. Too few replicas are currently in ISR compared to min.insync.replicas

Solution

1. Step 1: Interpret the error message

   The error means the number of replicas in ISR is less than the configured minimum.

2. Step 2: Match cause with options

   Too few replicas are currently in ISR compared to min.insync.replicas directly matches the error cause; other options are unrelated to ISR count.

3. Final Answer:

   Too few replicas are currently in ISR compared to min.insync.replicas -> Option D

4. Quick Check:

   ISR count below min.insync.replicas causes error [OK]

Hint: Error means ISR count < min.insync.replicas [OK]

Common Mistakes:

• Blaming leader offline instead of ISR count
• Confusing consumer group commit with ISR errors
• Thinking zero partitions cause this error

5. You want to ensure high availability in Kafka by allowing leader failover only if at least 2 replicas are in ISR. Which configuration and setup achieve this?

hard

A. Set min.insync.replicas=2 and have at least 3 replicas per partition

B. Set min.insync.replicas=1 and have 2 replicas per partition

C. Set min.insync.replicas=3 with 2 replicas per partition

D. Set min.insync.replicas=0 and 1 replica per partition

Solution

1. Step 1: Understand min.insync.replicas meaning

   This setting defines the minimum ISR count required for leader failover and write success.

2. Step 2: Match configuration to requirement

   To require at least 2 ISR replicas, set min.insync.replicas=2 and have at least 3 replicas to allow failover.

3. Final Answer:

   Set min.insync.replicas=2 and have at least 3 replicas per partition -> Option A

4. Quick Check:

   High availability needs min.insync.replicas=2 with 3 replicas [OK]

Hint: min.insync.replicas ≤ replica count for failover [OK]

Common Mistakes:

• Setting min.insync.replicas higher than replica count
• Using too few replicas for desired availability
• Setting min.insync.replicas to zero disables safety