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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Security | 5-10% | - Authorization (ACLs) - Encryption in Transit - Authentication (SASL, SSL/TLS) - Securing Schema Registry |
| Topic 2: Developing with Kafka Producers | 15-20% | - Producer Interceptors - Partitioning Strategies - Error Handling and Retry Logic - Idempotent Producers - Producer Configuration and Tuning - Exactly-Once Semantics - Serialization (JSON, Avro, Protobuf) |
| Topic 3: Developing with Kafka Consumers | 15-20% | - Consumer Configuration and Tuning - Consumer Groups and Rebalancing - Multi-threaded Consumers - Offset Management - Deserialization - Consumer Interceptors - Commit Strategies (Auto, Manual, Cooperative) |
| Topic 4: Schema Management | 5-10% | - Schema Registry Architecture - Schema Evolution and Compatibility - Protobuf and JSON Schemas - Avro Schemas - Schema Registration and Retrieval |
| Topic 5: Installing and Configuring Kafka | 5-10% | - ZooKeeper vs KRaft Mode - Broker Configuration Parameters - Topic Creation and Configuration - Partition Assignment Strategies |
| Topic 6: Kafka Streams | 20-25% | - Interactive Queries - Testing Kafka Streams Applications - State Stores and Processors - Transformation Operations (map, filter, join, aggregate) - Windowed Operations (Tumbling, Hopping, Session) - Exactly-Once Processing - Streams Architecture and Topology |
| Topic 7: Monitoring and Operations | 5-10% | - Disaster Recovery - Kafka Metrics and Monitoring - Consumer Lag and Health Checks - Log Compaction - Cross-region Replication |
| Topic 8: Kafka Connect | 10-15% | - Connector Configuration - Source and Sink Connectors - Converters and Transforms - Offset Management in Connect - Single Message Transformations (SMT) - Connect Architecture (Workers, Connectors, Tasks) |
| Topic 9: Kafka Fundamentals | 10-15% | - Replication Factor and ISR - Brokers and Clusters - Topics, Partitions, and Offsets - Log Segments and Retention - Producer and Consumer Basics |
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NEW QUESTION # 39
Which configurations define which connector is deployed?
Answer: B
NEW QUESTION # 40
Your streams application is reading from an input topic that has 5 partitions. You run 5 instances of your application, each with num.streams.threads set to 5. How many stream tasks will be created and how many will be active?
Answer: A
Explanation:
One partition is assigned a thread, so only 5 will be active, and 25 threads (i.e. tasks) will be created
NEW QUESTION # 41
Which of the following event processing application is stateless? (select two)
Answer: A,B
Explanation:
Stateless means processing of each message depends only on the message, so converting from JSON to Avro or filtering a stream are both stateless operations
NEW QUESTION # 42
To allow consumers in a group to resume at the previously committed offset, I need to set the proper value for...
Answer: B
Explanation:
Setting a group.id that's consistent across restarts will allow your consumers part of the same group to resume reading from where offsets were last committed for that group
NEW QUESTION # 43
Producing with a key allows to...
Answer: A
Explanation:
Keys are necessary if you require strong ordering or grouping for messages that share the same key. If you require that messages with the same key are always seen in the correct order, attaching a key to messages will ensure messages with the same key always go to the same partition in a topic. Kafka guarantees order within a partition, but not across partitions in a topic, so alternatively not providing a key - which will result in round-robin distribution across partitions - will not maintain such order.
NEW QUESTION # 44
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