Browse Exams — Mock Exams & Practice Tests

CCAAK Cheatsheet — Kafka Admin Tables, Configs, and Troubleshooting Pickers

Comprehensive CCAAK quick reference: Kafka cluster architecture, broker/topic configs, replication/ISR durability rules, security (TLS/SASL/ACLs), monitoring signals, and safe operational playbooks.

On this page

Use this for last‑mile review. Pair it with the Syllabus for coverage and Practice to validate instincts.

1) The admin mental models (what the exam is testing)

Partition + replication = your durability envelope

  • Replication factor: how many copies exist.
  • ISR (in-sync replicas): replicas caught up enough to be considered safe for acknowledgements.
    flowchart LR
	  P["Partition leader"] --> F1["Follower replica"]
	  P --> F2["Follower replica"]
	  F1 --> ISR["ISR set"]
	  F2 --> ISR

High-yield rule: durability choices are mostly about acks (producer) + min.insync.replicas (topic/broker).

2) Topic and partition quick pickers

You want… Do this Why
More consumer parallelism Increase partitions One consumer per partition per group
Higher durability Use higher replication factor More copies; better fault tolerance
“Changelog” style topic Enable compaction Keeps latest value per key
Audit/event log Use retention Keep full history for N days/size

Ordering reminder: ordering is per partition, not across partitions.

3) High-yield topic configs (recognize these)

Config What it controls Notes
cleanup.policy delete vs compact Compaction for latest-by-key streams
retention.ms / retention.bytes Delete policy bounds Applies when cleanup.policy=delete
min.insync.replicas Required ISR for acks=all Too high can reduce availability
unclean.leader.election.enable Allow data-loss failover Usually false for durability
segment.ms / segment.bytes Log segment roll Affects compaction/retention behavior
max.message.bytes Max record size Protects brokers from huge messages
compression.type Broker-side compression Usually set by producer; broker may enforce

4) Broker configs: the usual suspects

Listener and networking (most common misconfigs)

Setting Why it matters Typical pitfall
listeners Where broker binds Wrong interface/port
advertised.listeners What clients use Wrong hostname → clients can’t connect
listener.security.protocol.map TLS/SASL mapping Mismatch between listeners and protocols
inter.broker.listener.name Broker-to-broker traffic listener Incorrect security settings break replication

Storage and log placement

Setting Why it matters Typical pitfall
log.dirs Where partition logs live Disk fills → ISR shrink/URP
num.network.threads / num.io.threads Throughput Too low for high traffic
socket.*.bytes Network buffers Can throttle throughput if too small

5) Security cheat sheet (TLS vs SASL vs ACLs)

Control What it provides Examples
TLS Encryption in transit SSL listeners, certs, truststores
SASL Authentication SASL_PLAINTEXT, SASL_SSL with mechanisms
ACLs Authorization topic read/write, group access

Remember: Consumers typically need topic READ + group access permissions to operate.

6) Core admin CLI commands (Apache Kafka)

 1# List topics
 2kafka-topics --bootstrap-server <broker:9092> --list
 3
 4# Describe a topic (partitions, ISR, leaders)
 5kafka-topics --bootstrap-server <broker:9092> --describe --topic <topic>
 6
 7# Describe consumer group lag
 8kafka-consumer-groups --bootstrap-server <broker:9092> --describe --group <group>
 9
10# View or alter topic configs
11kafka-configs --bootstrap-server <broker:9092> --entity-type topics --entity-name <topic> --describe

Mental model: almost every operational question reduces to: what is the cluster state → what is unsafe → what is the least risky next step.

7) Troubleshooting pickers (high-yield)

Under-replicated partitions (URP)

Most common causes:

  • broker down / unstable
  • disk pressure / slow I/O
  • network issues between brokers
  • follower fetch falling behind due to load

Offline partitions

This is more severe:

  • no leader available
  • controller instability, multiple broker failures, or misconfiguration

Consumer lag climbing

Common causes:

  • insufficient partitions for the required throughput
  • slow processing / downstream bottleneck
  • frequent rebalances (timeouts / long processing)

8) Safe operations playbooks (exam-friendly)

  • Change management: prefer small, reversible changes; validate with metrics/logs before and after.
  • Rolling restarts: maintain quorum/ISR safety; restart one broker at a time; verify health between steps.
  • Disk incidents: protect brokers first (free space), then restore replication health, then tune retention/traffic.
  • Security changes: stage configs, validate with a test client, then roll through brokers.

Mini-glossary

Controller (cluster metadata leader) • ISR (in-sync replicas) • URP (under replicated partitions) • Leader election (choosing partition leader) • Compaction (latest per key) • ACL (authorization rules).

Syllabus
Practice