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| Section | Weight | Objectives |
|---|---|---|
| Kafka Fundamentals | 10-15% | - Brokers and Clusters - Replication Factor and ISR - Topics, Partitions, and Offsets - Log Segments and Retention - Producer and Consumer Basics |
| Kafka Connect | 10-15% | - Single Message Transformations (SMT) - Source and Sink Connectors - Converters and Transforms - Offset Management in Connect - Connector Configuration - Connect Architecture (Workers, Connectors, Tasks) |
| Monitoring and Operations | 5-10% | - Consumer Lag and Health Checks - Cross-region Replication - Disaster Recovery - Log Compaction - Kafka Metrics and Monitoring |
| Developing with Kafka Consumers | 15-20% | - Consumer Groups and Rebalancing - Offset Management - Consumer Configuration and Tuning - Consumer Interceptors - Commit Strategies (Auto, Manual, Cooperative) - Multi-threaded Consumers - Deserialization |
| Security | 5-10% | - Authorization (ACLs) - Securing Schema Registry - Encryption in Transit - Authentication (SASL, SSL/TLS) |
| Developing with Kafka Producers | 15-20% | - Serialization (JSON, Avro, Protobuf) - Producer Interceptors - Partitioning Strategies - Producer Configuration and Tuning - Error Handling and Retry Logic - Idempotent Producers - Exactly-Once Semantics |
| Installing and Configuring Kafka | 5-10% | - ZooKeeper vs KRaft Mode - Topic Creation and Configuration - Partition Assignment Strategies - Broker Configuration Parameters |
| Schema Management | 5-10% | - Avro Schemas - Schema Registration and Retrieval - Schema Evolution and Compatibility - Protobuf and JSON Schemas - Schema Registry Architecture |
| Kafka Streams | 20-25% | - Testing Kafka Streams Applications - Transformation Operations (map, filter, join, aggregate) - Streams Architecture and Topology - State Stores and Processors - Windowed Operations (Tumbling, Hopping, Session) - Interactive Queries - Exactly-Once Processing |
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NEW QUESTION # 46
Which producer exceptions are examples of the class RetriableException? (Choose 2.)
Answer: C,D
NEW QUESTION # 47
An application is consuming messages from Kafka. You observe partitions being frequently reassigned to the consumer group from the application logs.
Which factors may be contributing to this? (Choose 2.)
Answer: D
NEW QUESTION # 48
In stream processing applications, handling out-of-order data can be a challenge which could affect the implemented business logic.
Which type of Join handles out-of-order records?
Answer: C
NEW QUESTION # 49
Your company has three Kafka clusters: Development, Testing, and Production.
The Production cluster is running out of storage, so you add a new node.
Which two statements about the new node are true?
(Select two.)
Answer: A,B
Explanation:
* C is true: When a new broker is added,no partitions are assigned to itunless you create new topics or reassign existing onesusing kafka-reassign-partitions.sh.
* D is true: Kafka brokers arehot-pluggable; no need to stop the cluster when scaling.
FromKafka Operations Guide:
"A newly added broker won't be assigned partitions until reassignments or new topic creation."
"Kafka allows dynamic scaling by adding brokers without downtime."
* A is false: Broker IDs must bemanually setunless using dynamic broker registration in KRaft mode.
* B is false unless the cluster usesKRaft modeand the broker isspecifically assigneda controller role.
Reference:Kafka Operations > Adding Brokers
NEW QUESTION # 50
In Kafka, what are Topics split into?
Answer: C
NEW QUESTION # 51
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