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| Section | Weight | Objectives |
|---|---|---|
| Monitoring and Operations | 5-10% | - Log Compaction - Disaster Recovery - Kafka Metrics and Monitoring - Consumer Lag and Health Checks - Cross-region Replication |
| Developing with Kafka Consumers | 15-20% | - Commit Strategies (Auto, Manual, Cooperative) - Consumer Groups and Rebalancing - Consumer Configuration and Tuning - Offset Management - Multi-threaded Consumers - Consumer Interceptors - Deserialization |
| Developing with Kafka Producers | 15-20% | - Idempotent Producers - Error Handling and Retry Logic - Partitioning Strategies - Serialization (JSON, Avro, Protobuf) - Exactly-Once Semantics - Producer Interceptors - Producer Configuration and Tuning |
| Kafka Fundamentals | 10-15% | - Producer and Consumer Basics - Log Segments and Retention - Brokers and Clusters - Topics, Partitions, and Offsets - Replication Factor and ISR |
| Kafka Connect | 10-15% | - Connect Architecture (Workers, Connectors, Tasks) - Offset Management in Connect - Single Message Transformations (SMT) - Converters and Transforms - Connector Configuration - Source and Sink Connectors |
| Installing and Configuring Kafka | 5-10% | - Broker Configuration Parameters - ZooKeeper vs KRaft Mode - Partition Assignment Strategies - Topic Creation and Configuration |
| Security | 5-10% | - Authorization (ACLs) - Authentication (SASL, SSL/TLS) - Securing Schema Registry - Encryption in Transit |
| Kafka Streams | 20-25% | - Windowed Operations (Tumbling, Hopping, Session) - Testing Kafka Streams Applications - Transformation Operations (map, filter, join, aggregate) - Exactly-Once Processing - State Stores and Processors - Streams Architecture and Topology - Interactive Queries |
| Schema Management | 5-10% | - Protobuf and JSON Schemas - Schema Registry Architecture - Avro Schemas - Schema Registration and Retrieval - Schema Evolution and Compatibility |
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NEW QUESTION # 42
You use Kafka Connect with the JDBC source connector to extract data from a large database and push it into Kafka.
The database contains tens of tables, and the current connector is unable to process the data fast enough.
You add more Kafka Connect workers, but throughput doesn't improve.
What should you do next?
Answer: A
Explanation:
Increasing tasks.max allows the connector to create multiple tasks, each responsible for processing different tables or table partitions. If only one task is used, adding more workers has no effect.
From Kafka Connect JDBC Connector Docs:
"Use tasks.max to configure how many tasks are created for the connector. Each task can process a subset of the data." A and C help only if the bottleneck is in Kafka, not Connect.
D is a large architectural change, not the first step.
Reference: Kafka Connect JDBC Connector Configuration
NEW QUESTION # 43
You need to collect logs from a host and write them to a Kafka topic named 'logs-topic'. You decide to use Kafka Connect File Source connector for this task.
What is the preferred deployment mode for this connector?
Answer: C
Explanation:
Kafka Connect can run in standalone mode or distributed mode. For simple tasks like reading logs from a file on a single host, standalone mode is recommended.
From Kafka Connect User Guide:
"Standalone mode is useful when running connectors on a single machine (e.g., for development or simple deployments like log collection from a local file)." Distributed mode is preferred for scalability and fault tolerance but overkill for this use case.
Reference: Kafka Connect User Guide > Deployment Modes
NEW QUESTION # 44
ksqIDB Lambda functions must be used inside what type of designated functions?
Answer: B
NEW QUESTION # 45
A Zookeeper ensemble contains 3 servers. Over which ports the members of the ensemble should be able to communicate in default configuration? (select three)
Answer: B,C,D
Explanation:
2181 - client port, 2888 - peer port, 3888 - leader port
NEW QUESTION # 46
In Kafka, every broker... (select three)
Answer: A,E,F
Explanation:
Kafka topics are divided into partitions and spread across brokers. Each brokers knows about all the metadata and each broker is a bootstrap broker, but only one of them is elected controller
NEW QUESTION # 47
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