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| Section | Weight | Objectives |
|---|---|---|
| Schema Management | 5-10% | - Protobuf and JSON Schemas - Schema Evolution and Compatibility - Schema Registry Architecture - Schema Registration and Retrieval - Avro Schemas |
| Kafka Fundamentals | 10-15% | - Log Segments and Retention - Replication Factor and ISR - Brokers and Clusters - Topics, Partitions, and Offsets - Producer and Consumer Basics |
| Monitoring and Operations | 5-10% | - Consumer Lag and Health Checks - Log Compaction - Cross-region Replication - Disaster Recovery - Kafka Metrics and Monitoring |
| Installing and Configuring Kafka | 5-10% | - Partition Assignment Strategies - Broker Configuration Parameters - Topic Creation and Configuration - ZooKeeper vs KRaft Mode |
| Developing with Kafka Producers | 15-20% | - Partitioning Strategies - Producer Interceptors - Producer Configuration and Tuning - Idempotent Producers - Error Handling and Retry Logic - Exactly-Once Semantics - Serialization (JSON, Avro, Protobuf) |
| Developing with Kafka Consumers | 15-20% | - Consumer Interceptors - Deserialization - Offset Management - Consumer Configuration and Tuning - Consumer Groups and Rebalancing - Multi-threaded Consumers - Commit Strategies (Auto, Manual, Cooperative) |
| Kafka Connect | 10-15% | - Single Message Transformations (SMT) - Source and Sink Connectors - Converters and Transforms - Connector Configuration - Connect Architecture (Workers, Connectors, Tasks) - Offset Management in Connect |
| Security | 5-10% | - Authorization (ACLs) - Authentication (SASL, SSL/TLS) - Encryption in Transit - Securing Schema Registry |
| Kafka Streams | 20-25% | - Streams Architecture and Topology - Exactly-Once Processing - State Stores and Processors - Testing Kafka Streams Applications - Windowed Operations (Tumbling, Hopping, Session) - Transformation Operations (map, filter, join, aggregate) - Interactive Queries |
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NEW QUESTION # 79
Producing with a key allows to...
Answer: B
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 # 80
An ecommerce website maintains two topics - a high volume "purchase" topic with 5 partitions and low volume "customer" topic with 3 partitions. You would like to do a stream-table join of these topics. How should you proceed?
Answer: C
Explanation:
In case of KStream-KStream join, both need to be co-partitioned. This restriction is not applicable in case of join with GlobalKTable, which is the most efficient here.
NEW QUESTION # 81
You are running a Kafka Streams application in a Docker container managed by Kubernetes, and upon application restart, it takes a long time for the docker container to replicate the state and get back to processing the dat a. How can you improve dramatically the application restart?
Answer: C
Explanation:
Although any Kafka Streams application is stateless as the state is stored in Kafka, it can take a while and lots of resources to recover the state from Kafka. In order to speed up recovery, it is advised to store the Kafka Streams state on a persistent volume, so that only the missing part of the state needs to be recovered.
NEW QUESTION # 82
(You have a Kafka Connect cluster with multiple connectors deployed.
One connector is not working as expected.
You need to find logs related to that specific connector to investigate the issue.
How can you find the connector's logs?)
Answer: D
Explanation:
The official Apache Kafka Connect documentation explains that connectors run within the same worker JVM, and all logs are written through the worker's logging framework (Log4j or Log4j2). To isolate logs for a specific connector, Kafka Connect supports connector-specific logging contexts, which can be routed to separate log files using logging configuration.
By modifying the log4j.properties (or log4j2.xml) file to define a dedicated logger and appender for the connector's package or class name, you can direct logs from that connector to a separate file. This is the recommended and documented approach for debugging individual connectors in a shared Connect cluster.
Option A is incorrect because there is no generic "enable connector context" switch. Option B may increase verbosity but does not isolate logs per connector. Option D is false; Kafka Connect explicitly supports connector-level log separation through logging configuration.
Therefore, the correct approach is to configure a dedicated log appender for the specific connector.
NEW QUESTION # 83
If you enable an SSL endpoint in Kafka, what feature of Kafka will be lost?
Answer: A
Explanation:
With SSL, messages will need to be encrypted and decrypted, by being first loaded into the JVM, so you lose the zero copy optimization. See more information herehttps://twitter.com/ijuma/status/1161303431501324293?s=09
NEW QUESTION # 84
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