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| Section | Weight | Objectives |
|---|---|---|
| Kafka Fundamentals | 10-15% | - Replication Factor and ISR - Topics, Partitions, and Offsets - Log Segments and Retention - Producer and Consumer Basics - Brokers and Clusters |
| Kafka Connect | 10-15% | - Single Message Transformations (SMT) - Source and Sink Connectors - Offset Management in Connect - Connect Architecture (Workers, Connectors, Tasks) - Connector Configuration - Converters and Transforms |
| Monitoring and Operations | 5-10% | - Kafka Metrics and Monitoring - Consumer Lag and Health Checks - Log Compaction - Cross-region Replication - Disaster Recovery |
| Developing with Kafka Consumers | 15-20% | - Consumer Configuration and Tuning - Deserialization - Consumer Interceptors - Commit Strategies (Auto, Manual, Cooperative) - Multi-threaded Consumers - Consumer Groups and Rebalancing - Offset Management |
| Developing with Kafka Producers | 15-20% | - Idempotent Producers - Producer Interceptors - Error Handling and Retry Logic - Partitioning Strategies - Exactly-Once Semantics - Serialization (JSON, Avro, Protobuf) - Producer Configuration and Tuning |
| Schema Management | 5-10% | - Schema Registry Architecture - Schema Evolution and Compatibility - Schema Registration and Retrieval - Avro Schemas - Protobuf and JSON Schemas |
| Kafka Streams | 20-25% | - Testing Kafka Streams Applications - Transformation Operations (map, filter, join, aggregate) - Interactive Queries - Streams Architecture and Topology - State Stores and Processors - Windowed Operations (Tumbling, Hopping, Session) - Exactly-Once Processing |
| Installing and Configuring Kafka | 5-10% | - Topic Creation and Configuration - Broker Configuration Parameters - Partition Assignment Strategies - ZooKeeper vs KRaft Mode |
| Security | 5-10% | - Securing Schema Registry - Authorization (ACLs) - Authentication (SASL, SSL/TLS) - Encryption in Transit |
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NEW QUESTION # 45
(You need to set alerts on key broker metrics to trigger notifications when a Kafka cluster is unhealthy.
What are three minimum broker metrics to monitor for cluster health?
Select three.)
Answer: B,D,E
Explanation:
The Apache Kafka monitoring and operations documentation highlights several controller-level metrics that are critical indicators of cluster health.
ActiveControllerCount must always be 1 in a healthy cluster. A value of 0 indicates no active controller, while values greater than 1 indicate a serious split-brain condition. This metric is fundamental for cluster stability.
OfflinePartitionsCount is one of the most important health metrics. Any value greater than 0 means that some partitions have no available leader, making them unavailable for producers and consumers. This directly indicates a degraded or unhealthy cluster.
UncleanLeaderElectionsPerSec tracks the rate of unclean leader elections. Unclean elections can cause data loss, and any non-zero value is a strong signal of broker failures or misconfiguration and should immediately trigger alerts.
The remaining options are not minimum health indicators. LastCommittedRecordOffset is not a standard health metric, and TopicsToDeleteCount only indicates pending administrative operations, not cluster instability.
Therefore, the three minimum and officially recommended broker metrics for monitoring Kafka cluster health are UncleanLeaderElectionsPerSec, ActiveControllerCount, and OfflinePartitionsCount.
NEW QUESTION # 46
What are the requirements for a Kafka broker to connect to a Zookeeper ensemble? (select two)
Answer: A,B
Explanation:
Each broker must have a unique broker id and connect to the same zk ensemble and root zNode
NEW QUESTION # 47
Which configuration determines how many bytes of data are collected before sending messages to the Kafka broker?
Answer: C
NEW QUESTION # 48
Match each configuration parameter with the correct deployment step in installing a Kafka connector.
Answer:
Explanation:
Explanation:
* 1st:Place the connector's JAR file in the directory specified by plugin.path
* 2nd:Restart the Kafka Connect cluster
* 3rd:Verify using REST API (/connector-plugins)
* 4th:Configure the connector
* 5th:(Repeat of 4th, duplicate step)
1st # Place the connector's JAR file in the directory specified by the plugin.path configuration.
2nd # Restart the Kafka Connect cluster.
3rd # Verify that the connector is installed by listing all available connectors using the Kafka Connect REST API (/connector-plugins).
4th # Configure the connector using a JSON or properties file with the necessary settings.
5th # Configure the connector using a JSON or properties file with the necessary settings.
Kafka Connect requires that custom connectors be placed in the directory defined by plugin.path. After restarting the cluster, you can use the REST API to confirm availability and then deploy the connector configuration.
FromKafka Connect Documentation:
"After placing the JAR in the plugin.path, you must restart the Connect cluster to pick it up. Use the
/connector-plugins REST endpoint to verify."
The duplication of configuration is an error in the question options and should occur only once.
Reference:Kafka Connect Plugin Installation Guide
NEW QUESTION # 49
You are working on a Kafka cluster with three nodes. You create a topic named orders with:
replication.factor = 3
min.insync.replicas = 2
acks = allWhat exception will be generated if two brokers are down due to network delay?
Answer: A
Explanation:
With acks=all and min.insync.replicas=2, Kafka requires at least two in-sync replicas to acknowledge a write.
If only one broker is alive, the condition fails, and NotEnoughReplicasException is thrown by the producer.
From Kafka Producer Exception Docs:
"NotEnoughReplicasException is thrown when the number of in-sync replicas is insufficient to satisfy acks=all with min.insync.replicas." NetworkException is generic and not raised here.
NotCoordinatorException is related to consumer group coordination.
NotLeaderForPartitionException is unrelated unless accessing an unassigned leader.
Reference: Kafka Producer Error Handling
NEW QUESTION # 50
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