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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.

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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

What will you get

  • Access to recording of the complete project
  • Access to all material related to project like data files, solution files etc.

Prerequisites

  • Cloudera QuickStart VM

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...

Curriculum For This Mini Project

 
  Agenda for the Project
07m
  What is Kafka?
04m
  Microservices and Its Architecture
06m
  Why businesses need logs?
03m
  Making a case for real-time log processing
10m
  Run through the application using Flume Log4j appenders
10m
  Using Flume for Events
12m
  Getting data into Kafka
08m
  Download and Install Kafka
20m
  Kafka and Flume Integration
12m
  Lambda Architecture
26m
  Recap of the Previous Session
05m
  Kafka Streams and Kafka Connect
01m
  Starting Kafka Agents -Zookeeper
13m
  Kafka Streams
01m
  Kafka as a Processing Platform
06m
  Steps to use Kafka for Streaming Architecture in Microservices
05m
  Kafka Streaming Application
01m
  LogParserProcessor
09m
  KStream
03m
  Applying Business Logic on KStream
11m
  Parsing the Stream and Transforming into Object
09m
  Processed Logs
12m
  Resource Counter
05m
  Storing the Data into the Destination -HBase, Cassandra, MongoDB
00m
  Using Kafka Connect
05m
  Example on how to use Kafka Connect
43m
  Discussion on using Kafka for Microservices
01m
  Resource Counter Process
07m