Course Catalog  > Data Science and Big Data  > Streaming Analytics with Kafka
WA3204

Introduction to Kafka for C# Developers Training

Kafka is an open-source distributed event-streaming platform used for high-performance data pipelines, streaming analytics, data integration, and mission-critical applications. This four-day class will introduce students to Kafka’s capabilities using .NET Core, through lecture, labs, and a hands-on project the final day.

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Course Details

Duration

4 days

Prerequisites

  • Basic understanding of messaging, cloud, development, architecture and virtualization is beneficial.
  • Experience in .NET with C# is highly recommended as the majority of the labs, and the course project uses .NET Core

Target Audience

  • .NET/C# Developers
  • Architects
  • System Integrators
  • Security Administrators
  • Network Administrators
  • Software Engineers
  • Technical Support Individuals
  • Technology Leaders and Managers
  • Consultants who are responsible for elements of messaging for data collection, transformation, and integration for your organization.

Skills Gained

  • Understand the use of Kafka for high performance messaging
  • Identify the usages for Kafka in Microservices
  • Explain the benefits of Kafka patterns
  • Differentiate between messaging and message brokers
  • Describe Kafka messaging environments
  • Develop producers and consumers for Kafka
  • Recognize how Kafka enables Cloud-native applications
  • Summarize characteristics and architecture for Kafka
  • Demonstrate how to process and consume messages from Kafka using .NET Core Web API, MVC, and Worker (BackgroundService)
  • Demonstrate Kafka's role in the end-to-end project involving .NET MVC frontend, .NET Web API backend, .NET Worker, Azure SQL database, and Redis cache.
  • Design distributed high throughput systems based on Kafka
  • Describe the built-in partitioning, replication and inherent fault-tolerance of Kafka
Course Outline
  • Introduction to Kafka
    • Messaging Architectures – What is Messaging?
    • Messaging Architectures – Steps to Messaging
    • Messaging Architectures – Messaging Models
    • What is Kafka?
    • Kafka Overview
    • Need for Kafka
    • When to Use Kafka?
    • Kafka Architecture
    • Core concepts in Kafka
    • Kafka Topic
    • Kafka Partitions
    • Kafka Producer
    • Kafka Consumer
    • Kafka Broker
    • Kafka Cluster
    • Why Kafka Cluster?
    • Sample Multi-Broker Cluster
    • Overview of ZooKeeper
    • Kafka Cluster & ZooKeeper
    • Schema Registry
    • Who Uses Kafka?
  • The Inner Workings of Apache Kafka
    • A Kafka Cluster High-Level Interaction Diagram
    • Topics & Partitions
    • The Terms Event/Message/Record
    • Message Offset
    • Message Retention Settings
    • Deleting Messages
    • The Flush Policies
    • Writing to Partitions
    • Batches
    • Batch Compression
    • Partitions as a Unit of Parallelism
    • Message Ordering
    • Kafka Default Partitioner
    • The Load Balancing Aspect
    • Kafka Message Production Schematics
    • ZooKeeper
    • Reading from a Topic
    • Consumer Lag
    • Consumer Group
    • Consumer Group Diagram
    • The Broker
    • Broker Hardware Consideration
    • OS and File System
    • The Leader and Followers Pattern
    • Partition Replication Diagram
    • Controlled Shutdown
    • Controlling Message Durability with Minimum In-Sync Replicas
    • Log Compaction
    • Frequent Operational Problems
    • Some Kafka Design FAQs
  • Using Apache Kafka
    • What is Confluent?
    • Confluent Cloud
    • Confluent Cloud Resource Hierarchy
    • Setting up Confluent Cloud on Azure
    • Setting up Confluent Cloud using Confluent.io
    • Select the Confluent Cloud Cluster Type
    • Choose the Cloud Provider
    • Setting up Confluent Cloud using Azure Marketplace
    • Select Confluent Cloud in Azure Marketplace
    • Purchase Confluent Cloud
    • The Cluster View
    • Exploring the Confluent Cloud Console
    • Topics
    • Topics Advanced Settings
    • Searching for Messages in a Topic
    • The Confluent CLI
    • Kafka Cluster Planning
    • Kafka Cluster Planning – Producer/Consumer Throughput
    • Kafka Cluster Planning – Sizing for Topics and Partitions
    • Managing Topics in Confluent Cloud Console
    • Editing an Existing Topic
    • Delete a Topic
    • Kafka and .NET
    • .NET Kafka Architectures
    • Packages
    • Installing the Packages
    • Navigating .NET Client Documentation
    • Important Classes and Interfaces
    • appsettings.json Kafka Configuration
    • Loading the Configuration from appsettings.json
    • Produce and ProduceAsync Methods
    • Produce vs ProduceAsync
    • Error Handling
    • Consuming Messages
    • Creating and Deleting Topics
    • Copying Data from Between Environments
    • Mocking Datasets using Datagen Connector
    • Monitoring Confluent Cloud
    • Monitoring Confluent Cloud using cURL
    • Motoring Confluent Cloud using third-party Tools
  • Building Data Pipelines
    • Building Data Pipelines
    • What to Consider When Building Data Pipelines
    • Timeliness
    • Reliability
    • High and Varying Throughput
    • Evolving Schema
    • Data Formats
    • Protobuf (Protocol Buffers) Overview
    • Avro Overview
    • Managing Data Evolution Using Schemas
    • Confluent Schema Registry
    • Confluent Schema Registry in a Nutshell
    • Schema Management on Confluent Cloud
    • Create a Schema
    • Create a Schema using Confluent CLI
    • Create a Schema from the Web UI
    • Schema Change and Backward Compatibility
    • Collaborating over Schema Change
    • Handling Unreadable Messages
    • Deleting Data
    • Segregating Public and Private Topics
    • Transformations
    • Transformations - ELT
    • Security
    • Failure Handling
    • Agility and Coupling
    • Ad-hoc Pipelines
    • Metadata Loss
    • Extreme Processing
    • Kafka Connect vs. Producer and Consumer
  • Integrating Kafka with Other Systems
    • Introduction to Kafka Integration
    • Kafka Connect
    • Running Kafka Connect Operating Modes
    • Key Configurations for Connect workers:
    • Kafka Connect API
  • Kafka Security
    • Kafka Security
    • Encryption and Authentication using SSL
    • Configuring Kafka Brokers
    • Configuring Kafka Brokers – Optional Settings
    • Authenticating Using SASL
    • Authenticating Using SASL – Configuring Kafka Brokers
    • Authorization and ACLs
    • Securing a Running Cluster
    • ZooKeeper Authentication
  • Monitoring Kafka
    • Introduction
    • Metrics Basics
    • JVM Monitoring
    • Garbage collection
    • Java OS monitoring
    • OS Monitoring
    • Kafka Broker Metrics
    • Under-Replicated Partitions
    • Active controller count
    • Request handler idle ratio
    • Intelligent Thread Usage
    • All topics bytes in
    • All topics bytes out
    • All topics messages in
    • Partition count
    • Leader count
    • Offline partitions
    • Request metrics
    • Logging
    • Client Monitoring
    • Producer Metrics
    • Overall producer metrics
    • Per-broker and per-topic metrics
    • Consumer Metrics
    • Fetch Manager Metrics
    • Per-broker and per-topic metrics
    • Consumer coordinator metrics
    • Quotas
    • Lag Monitoring
    • End-to-End Monitoring
  • Apache Kafka Best Practices
    • Best Practices for Working with Partitions
    • Best Practices for Working with Consumers
    • Best Practices for Working with Producers
    • Best Practices for Working with Brokers
  • Lab Exercises
    • Lab 1 - Signing Up for the Free Trial of Confluent Cloud
    • Lab 2 - Understanding Confluent Cloud Clusters
    • Lab 3 - Understanding Confluent Cloud CLI
    • Lab 4 - Understanding Kafka Topics
    • Lab 5 - Using the Confluent CLI to Consume Messages
    • Lab 6 - Creating an ASP.NET Core MVC Kafka Client
    • Lab 7 - Creating an ASP.NET Core Web API Kafka Client
    • Lab 8 - Creating a .NET Core 3.1 Worker Kafka Client
    • Lab 9 - Integrating Azure SQL and Kafka
    • Lab 10 - Integrating Redis cache with .NET Core 3.1 ASP.NET MVC Lab
    • The Final Project