Apache Kafka & Streaming Distributed Messaging training covers Basic, Intermediate and Advanced level Kafka , its implementation and Application Development.
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Topic |
Apache Kafka & Streaming Distributed
Messaging Training |
Scope |
Confluence Kafka Enterprise 5.x Kafka 2.x Version |
Level |
Intermediate and Advanced |
Languages |
Java 1.8 |
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Days |
3 days or 24 hours |
Virtual Machine |
Linux OS [Mint/Ubuntu OS Based] |
Host Machine |
Windows/Linux/Mac |
Host Machine RAM |
16 GB if developer wants to use Virtual
Machine |
RAM |
8 GB if developer can use Linux/Mac
machine directly without Host Machine |
Setup Requirements |
for Docker setup 16 GB RAM 40-50 GB GB Free harddrive OS: Windows 10/Ubuntu Desktop/Mac |
Virtualization |
Virtualization to be enabled for
VirtualBox |
Training Setup |
Trainer shall provide pre-installed
VirtualBox Linux (GUI) image which has Java JDK 1.8, Scala, SBT, Maven, IntelliJ, Confluent Kafka, PostgreSQL,
Apache Spark, Dockers pre-installed.
The Lab should have facility to copy 20GB
of images to every test machines through network or USB |
Cloud Machine |
Trainer provides cloud machine for each participant
with 160 GB SSD Harddrive, 4 vCPU and 16 GB RAM for participants, cost about
5 Euros per student. The VM shall be available for 4 Days total during
training period. |
Participants
Pre-requites |
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Languages |
Good Working knowledge on Java or Scala
Languages Basic/Exposure to Reactive Programming
for Streaming |
JDK |
Good Knowledge on Using JDK, Compiler
Setup, either Java/Scala languages |
Maven & POM XML |
Good Knowledge on Maven & POM XML
files handling |
Scala SBT if Scala is preferred |
Good knowledge on Scala SBT |
Highspeed Internet |
Access to Highspeed Internet |
Editor |
Good expertise in using IntelliJ/Eclipse
Editor |
Preferred, but not mandatory |
High level understanding of AMQP Understanding Producer and Consumer
Design Patterns Message Queuing Distributed Systems Stream vs Batch Processing |
SSH |
Gitbash for windows SSH client for Linux/Mac/Windows |
Kafka Basic to
Intermediate |
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Introduction |
Introduction to Big Data Big Data and Streaming Kafka Introduction Kafka Features Kafka vs AMQP Kafka Features Kafka
Use Case 1 |
Understanding Big Data and Data Streaming
Problem Use Cases |
Introduction to Data Ingestion Messaging System Data Streaming Batch Processing Live Data Processing Data Forwarding, Queuing problems Publish/Subscribe patterns Workflow Application Hadoop and Map Reduce Integration Connected, Disconnected Architecture Persistence issues with large data
processing AMQP/MQTT to Kafka Bridge |
Kafka Architecture |
Elements of Kafka [Consumer, Producer,
Broker, ZooKeeper, Cluster] Kafka Architectures Kafka Overall Messaging Architecture Kafka Streaming Architecture Kafka Consumer and Producer Architecture Kafka Persistence Architecture Kafka Clusters Kafka Consumer Workers Group |
Kafka Distribution |
Apache Kafka Confluence Kafka Open Source Confluence Kafka Enterprise |
Kafka Setup
[Hands-on] |
Java JDK Kafka Setup Zoo Keeper Configuration Single Broker Configuration Understanding build-in tools, Kafka
server, test publisher, test consumer Configuration Kafka Single Node Broker Start ZooKeeper Start Kafka Server Using Example console consumer and publisher Broker, Consumer, Producer Configuration Zoo Keeper connection Broker ID Logs Port Consumer Configuration Producer Configuration |
Kafka Administrator Commands
[Hands-on] |
List all topics List all brokers Create Topics Change Topics Delete Topics Topic
Description |
Topics & Partitions |
Understanding Topics Understanding Partitions Understanding Replications |
Producer
[Hands-on] |
Kafka Producer Introduction Kafka Producer API Writing First Producer Kafka Producer Class Build a Kafka Producer Configure Producers Kafka Topics, Partitions Configuration Send messages to Kafka Send messages Synchronously Send Message Asynchronously and process
the async acknowledgement Producing Keyed and Non-Keyed Messages Serializers, Key/Value Serializer,
ProducerRecord Serialize Using Apache Avro, JSON Working with Multiple Brokers |
Consumer [Hands-on] |
Kafka Consumer Introduction Consumers and Consumer Groups Subscribe for Topics Consumer Records Achieving higher performance with
Consumer group De-serialize key and values Consumer Groups and Partition Rebalance Creating a Kafka Consumer The Poll Loop Configuring Consumers Commits and Offsets Rebalance Listeners Consuming Records with Specific Offsets |
Kafka Internal Architecture, Storages,
Cluster, Partitions in Depth |
Cluster Membership The Controller Replication workflow, Replication Internals Request Processing Physical Storage Reliability Partition allocation and number of partitions Broker Configuration Using Producers in a Reliable System Using Consumers in a Reliable System Validating System Reliability Performance Tuning in Kafka |
Intermediate to
Advanced |
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Cluster Architecture and Workflow
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Kafka Use Case Revising Cluster, Producer, Consumer, Broker, ZooKeeper Data Flow Between all actors in Kafka Systems Creating Clusters with Multiple Brokers Broker IDs and Master/Slave Brokers Fail over handling in clusters Understanding Leader Broker Balancing leadership |
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Cluster Administration and Configuration [Hands-on] |
Configure Cluster Replication High Availability Multi-Cluster Architectures Apache Kafka’s MirrorMaker Topic Operations |
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Partition in Depth [Hands-on] |
Topics and Partitions Understanding partition numbers Default partitions Explicit Partitions Under the hood partitions |
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Replications |
Understanding Replications Replication Factors and High Availability |
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Messages in Details
[Hands-on] |
Message Models Message Serialize JSON handling Message IDs |
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Persistence [Hands-on] |
Persisting Messages on File System Offline Consumer and Subscription
handling Durability of Messages Failover and Persistence |
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Kafka Streaming
4 Hours |
Stream Processing Stream-Processing Concepts Stream-Processing Design Patterns Kafka Streams by Example Kafka Streams: Architecture Overview KStream KTable GlobalKTable KStream to KTable KTable to KSTream |
Advanced |
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Kafka Monitoring |
Considerations When Building Data
Pipelines Metric Basics Kafka Broker Metrics Client Monitoring Lag Monitoring End-to-End Monitoring |
Kafka Connect APIs
[Hands-on] |
Kafka Connect API overview Kafka Connect When to Use Kafka Connect? Kafka Connect Properties Perform File source and sink using Kafka
Connect Kafka Connect vs Consumer/Producer model Kafka Connect with JDBC [Requires MySQL] Cassandra Connectivity [Optional] Working with HDFS Connectors Working with Elastic Search Connectors |
REST Proxy
[Hands-on] |
Managing REST Proxy Configuration |
Kafka Connect Configuration &
Administration
[Hands-on] |
Managing Kafka Connect Managing Sink/Sources Configuration and settings |
Zoo Keeper Administration
[Hands-on] |
Managing Zoo Keeper Cluster Zoo keeper lead, configurations |
Confluence Control Centre
[Hands-on] |
Introduction to Confluent Control Center Managing Control Center and Dashboard |
Schema Registry Configuration &
Administration
[Hands-on] |
Managing Schema Registry services |
Kafka Integrate with Apache Spark [Demo
only] [Optional] |
Integrate Apache Spark with Kafka Spark Streaming Jobs and Kafka Stream |
Mirror Maker and Confluent Replicator for
Data Centre Backup and Replication |
Mirror Maker Replication Confluent Replicator Setup and demo |
Production |
Deployment Configuration, cleaner installation |
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