Overview
Kafka is a durable, scalable, and reliable messaging system which has integration with Hadoop and Spark. Big Data analytics has proven to provide significant business benefits and more organizations are seeking to hire professionals who can extract crucial information from structured and unstructured data. Hadoop for many years was the undisputed leader in data analytics but a technology that has now proven itself to be faster and more efficient is Apache Kafka. Developed in the labs of LinkedIn, it is written in Java and Scala and is fast, scalable and distributed by design. As more and more organizations are reaping the benefits of data analysis through Kafka, there is a huge demand for Kafka experts. And hence this is the right time to enrol for this course.
What you will learn
- Multi Broker Kafka Implementation
- Multi Node Cluster Setup
- Kafka Streaming
- Flume with Kafka Integration
- Kafka API
- PyKafka
- Kafka Throughput
- Scalability
- Durability & Fault-tolerance
- Kafka Depployment in Real-time
Benefits
Kafka course can enable organizations and professionals to process huge volumes of data and leverage the benefits of Big Data Analytics efficiently. Over 30% of today’s Fortune 500 companies, like LinkedIn, Yahoo, Netflix, Twitter, PayPal, Airbnb, etc. use Apache Kafka.
Individual Benefits
- Apache Kafka helps you to develop your own applications with ease
- Get equipped to process large-scale data and kick-start a career in real-time analytics
- Kafka helps you to get into multiple industries which include business services, retail, finance, manufacturing, etc.
- Enables you to work in profiles like Kafka Developer, Kafka Testing Professional, Kafka Project Managers, and Big Data Architect in Kafka
According to PayScale, a Kafka professional can earn an average of $140,642 p.a. The salary range varies based on the experience, skills, and designation of an individual.
Organizational Benefits
- It helps organizations to handle large volumes of data
- Enables transparent and seamless message handling while avoiding downtime
- Allows organizations to integrate with a variety of consumers
- Implementation of Kafka helps to handle real-time data pipeline
Course Content
| Introduction to Big Data | Play | |
| Big Data Analytics | Play | |
| Need for Kafka | Play | |
| What is Kafka? | Play | |
| Kafka Features | Play | |
| Kafka Concepts | Play | |
| Kafka Architecture | Play | |
| Kafka Components | Play | |
| ZooKeeper | Play | |
| Where is Kafka Used? | Play | |
| Kafka Installation | Play | |
| Kafka Cluster | Play | |
| Types of Kafka Clusters | Play | |
| Configuring Single Node Single Broker Cluster | Play |
| Configuring Single Node Multi Broker Cluster | Play | |
| Constructing a Kafka Producer | Play | |
| Sending a Message to Kafka | Play | |
| Producing Keyed and Non-Keyed Messages | Play | |
| Sending a Message Synchronously & Asynchronously | Play | |
| Configuring Producers | Play | |
| Serializers | Play | |
| Serializing Using Apache Avro | Play | |
| Partitions | Play |
| Consumers and Consumer Groups | Play | |
| Standalone Consumer | Play | |
| Consumer Groups and Partition Rebalance | Play | |
| Creating a Kafka Consumer | Play | |
| Subscribing to Topics | Play | |
| The Poll Loop | Play | |
| Configuring Consumers | Play | |
| Commits and Offsets | Play | |
| Rebalance Listeners | Play | |
| Consuming Records with Specific Offsets | Play | |
| Deserializers | Play |
| Cluster Membership | Play | |
| The Controller | Play | |
| Replication | Play | |
| Request Processing | Play | |
| Physical Storage | Play | |
| Reliability | Play | |
| Broker Configuration | Play | |
| Using Producers in a Reliable System | Play | |
| Using Consumers in a Reliable System | Play | |
| Validating System Reliability | Play | |
| Performance Tuning in Kafka | Play |
| Use Cases - Cross-Cluster Mirroring | Play | |
| Multi-Cluster Architectures | Play | |
| Apache Kafka’s MirrorMaker | Play | |
| Other Cross-Cluster Mirroring Solutions | Play | |
| Topic Operations | Play | |
| Consumer Groups | Play | |
| Dynamic Configuration Changes | Play | |
| Partition Management | Play | |
| Consuming and Producing | Play | |
| Unsafe Operations | Play |
| Considerations When Building Data Pipelines | Play | |
| Metric Basics | Play | |
| Kafka Broker Metrics | Play | |
| Client Monitoring | Play | |
| Lag Monitoring | Play | |
| End-to-End Monitoring | Play | |
| Kafka Connect | Play | |
| When to Use Kafka Connect? | Play | |
| Kafka Connect Properties | Play |
| Stream Processing | Play | |
| Stream-Processing Concepts | Play | |
| Kafka Streams by Example | Play | |
| Stream-Processing Design Patterns | Play | |
| Kafka Streams: Architecture Overview | Play |
| Apache Hadoop Basics | Play | |
| Hadoop Configuration | Play | |
| Kafka Integration with Hadoop | Play | |
| Apache Storm Basics | Play | |
| Configuration of Storm | Play | |
| Integration of Kafka with Storm | Play | |
| Apache Spark Basics | Play | |
| Spark Configuration | Play | |
| Kafka Integration with Spark | Play |
| Flume Basics | Play | |
| Integration of Kafka with Flume | Play | |
| Cassandra Basics such as and KeySpace and Table Creation | Play | |
| Integration of Kafka with Cassandra | Play | |
| Talend Basics | Play | |
| Integration of Kafka with Talend | Play |
Course Details
Apache Kafka training will take you through the architectural design of Kafka that enables it to process large strings of data in real-time. Kafka stores, processes, and publishes streams of data records seamlessly as they occur and in a durable manner. The speed and performance of Kafka can be attributed to the fact that it runs as a cluster on multiple servers, enabling it to span across several data centers.
IT professionals can use Kafka certification to dive into the intrinsic architecture of Apache Kafka. Moreover, it helps to understand Kafka API streams, learn how it is developed on Java, and eventually develop cutting-edge big data solutions using Kafka.
Who should go for this course?
- Data scientists
- ETL developers
- Data analysts
- BI Analysts & Developers
- SAS Developers
- Big Data Professionals
- Big Data Architects
- Project Managers
- Research professionals
- Analytics professionals
- Professionals aspiring for a career in Big Data
- Messaging and Queuing System professionals
Prerequisites
It is not mandatory for you to have a prior knowledge of Kafka to take up Apache Kafka training. However, as a participant you are expected to know the core concepts of Java or Python to attend this course.
Course Info.
Training Options
Selfpaced Training
349
- Lifetime access to high-quality self-paced eLearning content curated by industry experts
- 3 simulation test papers for self-assessment
- Lab access to practice live during sessions
- 24x7 learner assistance and support
Live Virtual Classes
499
- Online Classroom Flexi-Pass
- Lifetime access
- Practice lab and projects with integrated Azure labs
- Access to Microsoft official content aligned to examination
One on One Training
999
- Customized learning delivery model (self-paced and/or instructor-led)
- Flexible pricing options
- Enterprise grade learning management system (LMS)
- Enterprise dashboards for individuals and teams
- 24x7 learner assistance and support
Exam & Certification
- Exam Cost $150
- 60 multiple choice questions in 90 minutes
- No negative scoring
- Remotely proctored on your computer
- Available globally in English
- There is no mention of number of questions need to be correct in order to pass the exam. Result will be shown immediately (PASS or FAIL) at the end of exam. No scoring or percentage is provided.
FAQs
Apache Kafka is one of the most popular publish subscribe messaging systems which is used to build real-time streaming data pipelines that are robust, reliable, fault tolerant & distributed across a cluster of nodes. Kafka supports a variety of use-cases which commonly include Website activity tracking, messaging, log aggregation, Commit log & stream processing. These are reasons why many giants such as Airbnb, PayPal, Oracle, Netflix, Mozilla, Uber, Cisco, Coursera, Spotify, Twitter, Tumblr are looking for professionals with Kafka skills. Getting Kafka certified will help you land your dream job.
To master Apache Kafka, you need to learn all the concepts related to Apache Kafka – Kafka Architecture, Kafka Producer & Consumer, Configuring Kafka Cluster, Kafka Monitoring, Kafka Connect & Kafka Streams. Knowledge of Kafka integration with other Big Data tools such as Hadoop, Flume, Talend, Cassandra, Storm and Spark will be a plus point.
There are a lot of job opportunities for Apache Kafka professionals as it is adopted by both SME & big giants. The average salary of a Software Engineer with Kafka skills is $110,209 whereas a Senior Software Engineer and a Lead Software Engineer can expect average salaries of $131,151 and $134,369 respectively.
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