To ace your interview, you must prepare the most anticipated Kafka interview questions and answers. The demand for software engineers with certified Apache Kafka expertise is increasing at an exponential rate. Over 60% of the Fortune 100 companies use Kafka, including Goldman Sachs, Cisco, Intuit, Target, and others. The increased popularity of Kafka has resulted in a plethora of job opportunities as well as stiff competition in technical interviews.
Kafka has emerged as a highly attractive option for data integration. It ranks among the top open-source tools for building real-time streaming data pipelines and applications that adapt to the data streams. This article covers the crucial topics that will help you ace your Kafka technical interview rounds.
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You must be thoroughly familiar with the most common topics for Kafka interview questions. Here are some sample Kafka interview questions and answers to help you quickly revise the most vital concepts.
Apache Kafka is an open-source, partitioned, and replicated log service and publish-subscribe messaging application. It is also a full-fledged event streaming platform developed by Apache and written in Scala. It is used for building real-time data pipelines and streaming applications.
You should be well-prepared for Kafka features interview questions. The interviewer can also ask about any one of the features in particular. The top features of Apache Kafka are as follows:
This is one of the most important Kafka interview questions as the interviewer can ask you to elaborate on the various components too. The important components available in Kafka are as follows:
The ZooKeeper stores offset-related information used to consume a specific topic and by a specific consumer group in the Kafka environment. It builds coordination between different nodes in a cluster. You can also use ZooKeeper to recover from previously committed offset if any node fails because it works as a periodically-commit offset.
It is impossible to avoid Zookeeper and directly connect to the Kafka server. You cannot serve any client request in Kafka if ZooKeeper is down.
Kafka uses the following four core APIs:
You should be well-versed with the drawbacks while answering Kafka interview questions. You can consider the following list of disadvantages of Kafka:
Kafka producers handle the load balancing process by default, wherein they spread out the message load between partitions, preserving message ordering. You can specify the exact partition for a message in Kafka.
Leaders in Kafka perform all read and write requests for the partition, and followers passively replicate the leader. If the leader fails, one of the followers takes over the role, and this entire process ensures load balancing of the servers.
Replicas are a list of nodes. They replicate the log for a particular partition irrespective of whether they play the role of the leader.
ISR stands for In-Sync Replicas, and it is a set of message replicas synced to the leaders.
You should also prepare some Kafka tough interview questions to nail the most challenging software engineer tech interview rounds at FAANG.
Interviewers often put up Kafka interview questions that require comparisons between Kafka and its alternatives. The following table states the main points of difference between Kafka and RabbitMQ:
| Kafka | RabbitMQ |
| Kafka supports message ordering because of its partitions. | Kafka supports message ordering because of its partitions. |
| Kafka is durable, distributed, and highly available. It can share as well as replicate data. | RabbitMQ doesn’t have such features. |
| Kafka is a log. The messages are logged, and they are always there. | RabbitMQ is a queue. The messages are destroyed once consumed. |
| The performance rate is up to 100,000 messages/second. | The performance rate is up to 20,000 messages/second. |
The major differences between Kafka and Flume are:
| Kafka | Flume |
| Kafka is a general-purpose tool for both multiple producers and consumers. | It is a special-purpose tool for specific applications. |
| Kafka can replicate the events. | Flume does not replicate the events. |
| It works on the pull model. | It works on the push model. |
| It is easy to scale. | It is not that scalable. |
QueueFullException occurs when the producer tries to send messages at a pace that the broker cannot handle. You will have to add enough brokers to collaboratively handle the increased load as the producer doesn’t block.
Znodes are nodes in a ZooKeeper tree. They keep version numbers for data modifications, ACL changes, and timestamps in a structure. ZooKeeper utilizes the version number and timestamp to verify the cache while guaranteeing that updates are well-coordinated. The version number connected grows each time the data on Znode changes.
There are three types of znodes in ZooKeeper:
This is one of the frequently asked Kafka interview questions. A Kafka has one or more brokers that act as the Controller. The producers push records into Kafka topics within the broker while consumers pull records off a Kafka topic.
If one or more brokers of the Kafka cluster are down, the producer will retry for a certain time (based on the settings). One or more of the consumers will not be able to read anything during this time until the respective brokers are up.
The three types of system tools are:
The Kafka Replication Tool also assists in creating a high-level design for the replica maintenance process. Some replication tools available include:
Kafka has the following benefits:
A BufferExhaustedException is thrown when the producer is unable to assign memory to a record as the buffer is full. When the production rate exceeds the rate of data transfer from the buffer for long enough, and the producer is in non-blocking mode, the allocated buffer will be depleted, and the exception will be thrown.
An OutOfMemoryException arises when the consumers are sending huge messages, or there is a spike in messages sent at a quicker rate than the rate of downstream processing, and the message queue fills up, consuming memory space.
Kafka does not permit you to reduce the number of partitions for a topic. However, you can expand the partitions. The alter command enables you to change the behavior and its associated configurations of a topic. You can use the following alter command and increase the partitions to five:
This completes the list of Kafka interview questions that you must practice for your next tech interview. The interviewer can ask you to develop a Kafka client application that produces messages to and consumes messages from an Apache Kafka cluster in Java, Kotlin, Python, Ruby, .NET, Scala, or other languages of your choice.
If you are applying for senior Kafka developer positions, you must practice Kafka coding interview questions to ace the coding rounds.
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You must compile a list of relevant Kafka projects and accomplishments to discuss while answering Kafka interview questions. To ace your Kafka interview, you must show your enthusiasm for the position. Practice the most common Kafka interview questions, including coding challenges. You can also take a few mock interviews to improve your tech interview preparation.
You must focus on stream processing, replications, clusters, Kafka features, partitioning, amongst others, to tackle the challenging Kafka interview questions.
Once the hiring manager is done asking you Kafka interview questions, they will give you some time to ask them questions. You should make the most of this time and ask well-structured questions about your role, the team, and the company. You should not question the basic values or any information you are expected to know beforehand.
Leading companies worldwide use Kafka to modernize their data strategies with event streaming architecture, including Goldman Sachs, Cisco, Intuit, Netflix, and Airbnb.
Kafka-python is designed to function much like the official java client, with some pythonic interfaces. You can use Python to write Kafka code as a developer.
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3. Top Advanced Java Interview Questions for Your Coding Interview
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