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Real-Time Log Processing in Kafka for Streaming Architecture

The goal of this apache kafka project is to process log entries from applications in real-time using Kafka for the streaming architecture in a microservice sense.
What are the prerequisites for this project?
  • Cloudera QuickStart VM

What will you learn

  • Re-state the case for real-time processing of log files
  • Run through our application and real-time log collection using Flume Log4J appenders
  • Flume Kafka Integration (Channels or Sink)
  • Kafka Stream
  • Kafka Connect
  • Extending our architecture in a microservice world

Project Description

In our previous Spark Project-Real-Time Log Processing using Spark Streaming Architecture, we built on a previous topic of log processing by using the speed layer of the lambda architecture. We performed a real time processing of log entries from application using Spark Streaming, storing the final data in a hbase table.

In this kafka project, we will repeat the same objectives using another set of real time technologies. The idea is to compare both approaches of doing real time data processing which will soon become mainstream in various industries.

We will be using Kafka for the streaming architecture in a microservice sense.

The major highlight of this big data project will be students having to compare the spark streaming approach vs the Kafka-only approach. This is a great session for developers, analyst as much as architects.

Note: It is worthy of note that the Cloudera QuickStart VM does not have Kafka. We intend to work around that. So come prepare to do Kafka Installation in Cloudera quickstart vm.

Instructors

 
Michael

Big Data & Enterprise Software Engineer

I am passionate about software development, databases, data analysis and the android platform. My native language is java but no one has stopped me so far from learning and using angular and node.js. Data and data analysis is thrilling and so are my experiences with SQL on Oracle, Microsoft SQL Server, Postgres and MyS see more...

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