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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Security | 5-10% | - Encryption in Transit - Authorization (ACLs) - Securing Schema Registry - Authentication (SASL, SSL/TLS) |
| Topic 2: Schema Management | 5-10% | - Protobuf and JSON Schemas - Avro Schemas - Schema Registry Architecture - Schema Evolution and Compatibility - Schema Registration and Retrieval |
| Topic 3: Developing with Kafka Consumers | 15-20% | - Consumer Interceptors - Deserialization - Offset Management - Multi-threaded Consumers - Commit Strategies (Auto, Manual, Cooperative) - Consumer Configuration and Tuning - Consumer Groups and Rebalancing |
| Topic 4: Developing with Kafka Producers | 15-20% | - Partitioning Strategies - Producer Interceptors - Producer Configuration and Tuning - Idempotent Producers - Serialization (JSON, Avro, Protobuf) - Error Handling and Retry Logic - Exactly-Once Semantics |
| Topic 5: Kafka Streams | 20-25% | - Windowed Operations (Tumbling, Hopping, Session) - Exactly-Once Processing - Testing Kafka Streams Applications - State Stores and Processors - Transformation Operations (map, filter, join, aggregate) - Interactive Queries - Streams Architecture and Topology |
| Topic 6: Monitoring and Operations | 5-10% | - Kafka Metrics and Monitoring - Disaster Recovery - Log Compaction - Cross-region Replication - Consumer Lag and Health Checks |
| Topic 7: Kafka Fundamentals | 10-15% | - Producer and Consumer Basics - Brokers and Clusters - Topics, Partitions, and Offsets - Log Segments and Retention - Replication Factor and ISR |
| Topic 8: Installing and Configuring Kafka | 5-10% | - Topic Creation and Configuration - ZooKeeper vs KRaft Mode - Partition Assignment Strategies - Broker Configuration Parameters |
| Topic 9: Kafka Connect | 10-15% | - Offset Management in Connect - Source and Sink Connectors - Connect Architecture (Workers, Connectors, Tasks) - Single Message Transformations (SMT) - Converters and Transforms - Connector Configuration |
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NEW QUESTION # 50
(You are writing a producer application and need to ensure proper delivery.
You configure the producer with acks=all.
Which two actions should you take to ensure proper error handling?
Select two.)
Answer: A,D
Explanation:
The Apache Kafka producer API is asynchronous by default, and proper error handling requires explicit mechanisms. The official documentation recommends using a callback function with producer.send() to determine whether a record was successfully acknowledged or failed due to an exception. The callback provides access to both RecordMetadata and any exception encountered during sending.
Additionally, certain errors-such as serialization errors or configuration issues-are thrown synchronously when calling producer.send(). These must be handled using a try/catch block that catches KafkaException or its subclasses.
Option A is invalid because ProducerRecord has no status() method. Option C is incorrect because producer.
send() returns a Future<RecordMetadata>, not a RecordMetadata object directly.
Thus, combining a callback for asynchronous errors and a try/catch block for synchronous errors is the correct and officially documented approach to ensure reliable producer error handling when using acks=all.
NEW QUESTION # 51
What is the default maximum size of a message the Apache Kafka broker can accept?
Answer: A
Explanation:
The default maximum message size that a Kafka broker accepts is1MB (1,048,576 bytes), controlled by the config propertymessage.max.bytes.
FromKafka Broker Configuration Docs:
"The default maximum message size is 1MB. To accept larger messages, configure message.max.bytes and the producer's max.request.size." Producers also have a matching limit via max.request.size, and consumers via fetch.message.max.bytes.
Reference:Kafka Broker Configuration > message.max.bytes
NEW QUESTION # 52
Using the Confluent Schema Registry, where are Avro schema stored?
Answer: C
Explanation:
The Schema Registry stores all the schemas in the _schemas Kafka topic
NEW QUESTION # 53
What is the function of Kafka Connect Converters?
Answer: C
NEW QUESTION # 54
A consumer application needs to use an "at most once" delivery semantic.
What is the best consumer configuration lo avoid duplicate messages being read?
Answer: A
NEW QUESTION # 55
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