Hire Kafka Developers

Kafka is an open-source distributed message streaming platform that provides an efficient way to store and subscribe to event data for applications. It consists of cluster nodes that import and replicate data that different applications can later access. It can process hundreds of thousands of online and offline messages. It guarantees zero downtime and zero data loss for the system.

Kafka is highly reliable due to its partitioning. The execution time in Kafka is constant i.e. O(log N). This means that the execution of the algorithm is independent of the message input size. It can also balance and support multiple subscribers. Kafka is also fault tolerant – it can handle failures by restarting the server by itself. All of these qualities are why Kafka Consulting is so sought after.

If you want to stay on top of the game, the first step is to hire Kafka developers.

Hiring Guide

Kafka has several components such as producers, consumers, topics, clusters, replicas and partitions. Producers send messages to Kafka clusters and consumers read messages from them. Messages are stored in topics. Kafka divides these topics into partitions. In partitions, all messages are ordered linearly and you can check specific messages by their offset.

Producers perform load balancing to ensure that messages are split evenly across partitions. If a consumer drops out, the consumer group rebalances the partition among the remaining consumers. Kafka works with exactly once semantics, i.e. all data passing through it can only be processed once.

Data in Kafka is distributed and streamlined across a cluster of nodes to handle large amounts of data. Its distributed commit log transports messages to disk as quickly as possible, making it efficient for data transfer. It is fast and can serve different types of customers. You can also use it to transform, aggregate, and filter data.

Kafka in today's industry

Many companies such as LinkedIn, Yahoo and Pinterest use Kafka. Kafka has many use cases in the industry, such as processing payments, collecting customer interactions, tracking metrics, and processing data streams.

Kafka can handle messages with large volumes of data streams. If necessary, Kafka can also scale along many different dimensions, i.e. you can increase the number of processors, consumers or producers, whatever suits your business needs. Kafka is stable and has high throughput for publishing and subscribing to messages.

Kafka can also process data in real time through Kafka Streams. It is a client library that allows you to work with continuously updating datasets. Stream processors receive information from streams and apply their own processes to them. It has a low barrier to entry and can create small-scale applications for proof of concepts. These applications can later be scaled as per requirements.

Problems finding the best Kafka developer

Even if you hire the best Kafka engineers, they may not have adequate experience regarding the hardware requirements for implementing Kafka. Inexperienced Apache Kafka developers can sometimes overestimate Kafka's hardware requirements. This causes customers to invest in expensive and unnecessary hardware for their projects. A good engineer should assess the scale of data the customer wants to run through Kafka and develop a systematic hardware plan for optimal data processing.

Due to the large amount of data passing through Kafka per second, sometimes the system can back up and problems can arise. There can be several problems – the leader can fail or the brokers can fail. Issues like these need to be resolved as quickly as possible.

Unfortunately, it's not easy to find a Kafka expert who can understand these issues and fix them as quickly as possible. Although the system is fault tolerant, Kafka engineers must understand common Kafka faults and ensure that such events do not harm message consumption.

How to choose the best Kafka developer

The perfect Kafka expert must have proficiency in programming languages ​​like Java, Golang, Dot Net, and Python. They must be able to integrate Kafka with Hadoop, Spark, and Storm, and they must be able to implement Kafka for customer applications.

A Kafka expert must also understand the hardware requirements for a specific project, such as CPU/RAM, type and number of drives, network type and file systems, among others. All this hardware is immensely significant if you want to develop an optimally functioning Kafka architecture.

Kafka experts should also be able to advise their customers on which cloud providers they should choose based on their network requirements. Network bandwidth can be a significant obstacle to Kafka running smoothly, so knowing everything about cloud providers is critical for an experienced Kafka engineer.

Kafka Interview Questions

Here are some questions you can ask Kafka developers before hiring them:

What are some of Kafka's main APIs and what are their functions?

Here is a list of Core Kafka APIs and their list of functions:

• Admin API : Used to monitor topics, brokers, and configurations.
• Producer API : Publishes application data streams to Kafka topics on Kafka clusters.
• Consumer API : Reads data streams from one or more topics.
• Streams API : Implements microservices and stream processing applications for continuous data.
• Connect API : Creates and runs connectors that read or write streams from external systems.

Why does Kafka use ZooKeeper?

Kafka uses ZooKeeper to manage topics, store message offsets, and control cluster nodes. A Kafka professional must know the number of ZooKeepers required for the smooth functioning of Kafka nodes, depending on the workload. A maximum of 5 Zookeepers must be used in one environment.

Could Kafka's redundancy feature create a problem for customers? And what solution can you offer for this?

Too many redundant copies of data in Kafka will affect its performance and increase storage costs. The ideal solution for customers would be to use Kafka to temporarily store data and later migrate the data to a different database. This should reduce overhead costs and improve performance.

What are some of Kafka's system tools and their functions?

• Mirror Creator : These tools help you mirror clusters i.e. replicate Kafka clusters. Data is copied from one topic and written to the subsequent topic on the target cluster.
• Kafka Migration Tool : This tool allows you to seamlessly move brokers from one version to another. It is a reliable tool that allows easy and efficient synchronization of data between different environments.
• Consumer Compensation Checker : This is an essential tool used to debug customers. It also helps to check the efficiency of the mirroring cluster.

Explain the role of displacement.

Messages in partitions have a unique ID number called an offset. It uniquely identifies different messages across partitions.

Job description

We are looking for a highly qualified Kafka developer to join our large-scale software design and development team. We're looking for smart team players who can code and maintain medium to large applications. The Kafka Developer must also be good at documentation and be able to meet deadlines. If you are a goal-oriented Kafka expert this is an excellent opportunity for you to showcase your skills.

Responsibilities

• Write reusable and reliable web applications.
• Create internal and customer projects based on Spring boot microservices for Kafka configuration.
• Configure Kafka production and test environments
• API implementation for Spark and Spring calls.
• Improve systems performance and functionality and decrease latency.
• Implement data movement to and from HDFS from different sources.
• Coordinate with internal and external teams to understand business requirements
• Follow industry best practices and standards
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Skills and qualifications

• Knowledge of Java and Golang. You must also have previous experience with Kafka.
• Experience designing reusable code and modules using Zookeeper, Streams and brokers
• Understanding of JDBC, JMS and MQ.
• Proven experience with Kafka Rest Proxy
• Experience with Kafka converters.
• Experience with redundancy tools, cluster tools and monitoring tools.
• Knowledge of RDBMS, Hadoop ecosystem, alert configuration.
• Problem solving skills and team spirit
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Conclusion

Kafka has become one of the most popular platforms for streaming messages. It is fast, scalable, reliable and has high performance. As a result of its growing popularity, it has enabled many consumers around the world to implement an efficient system for large-scale data processing.