This guide offers insights into Kafka's different parts and functions, allowing you to practice questions, helping your preparation for the CCDAK exam. 90 minutes - 60 questions - Around 75% pass rate required.
You can prepare on the [theory of CCDAK here] (https://www.danielsobrado.com/blog/guide-ccdak-concluent-kafka-developer-certification/)
Brokers form Kafka's core, managing data flow - storing and routing messages. Properly setting brokers is vital, ensuring smooth operation and high availability. Brokers handle performance optimization and fault tolerance.
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Producers bring data into the Kafka ecosystem. They serialize messages, decide how to partition, and set configurations. Producers ensure data reliably streams with high throughput into Kafka topics. Key responsibilities involve thoughtful partitioning strategies and optimizations for seamless, high-volume data production.
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You get information from Kafka topics with consumers. You have to know consumer settings to build good apps. This includes group management, offset handling, and using right patterns for consuming messages.
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In a Kafka system, topics organize messages. They're key - dividing messages into categories. This part talks about making new topics. Plus: setup details for topics, ways to manage them. It covers partitioning and replication too.
Kafka clusters are like engines - they need care. Proper cluster admin is key. That's where brokers, topics, and configs come in. Set Kafka up right. Scale it as needs arise. Balancing ensures smooth running. Stay on top of these tasks - it keeps Kafka strong.
Watching closely is key. Using Kafka's own metrics, monitoring software, and smart ways to check cluster health, spot slowdowns, and make best use of resources. Monitoring lets you act early to keep things running well.
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Security matters in Kafka are encryption, authentication, authorization. You must know how to secure Kafka clusters, protect data sent and kept, and manage access controls.
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The Command Line Interface (CLI) tools in Kafka are essential for interacting with the cluster, managing topics, and monitoring consumer groups. Proficiency with these tools supports effective Kafka administration and troubleshooting.
Kafka Streams simplifies building complex data processing apps. It operates directly on Kafka. Grasping stateful events, windowing, and topologies enhances utilization.
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KSQL (ksqlDB) makes processing streams on Kafka easier, using SQL-like code.
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Kafka Connect links Kafka to other systems. It allows data to move in and out. We will explore setting up connectors. These connect data sources and destinations.
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Kafka REST Proxy allows external applications to interact with Kafka clusters. It enables the production and consumption of messages through HTTP. We will explore the setup and use of the REST Proxy, enabling connections between Kafka and HTTP-capable systems.
Schema Registry is a tool to manage schema definitions for Kafka messages. It helps with schema evolution and makes sure data is compatible. Understanding how schema registration works is important. Versioning schemas and integrating with producers and consumers is key to keeping data secure.
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Zookeeper manages activities within Kafka clusters. Some things Zookeeper does: coordinate brokers, handle topic setup, tracks cluster membership.
Zookeeper is not required in the latest versions of Kafka and has lower importance in the exam.
Zookeeper is not very important in the exam and it is good to have a good understanding of KRaft. This is why the questions are only about KRaft.
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And finally check the Last minute review
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