Intro to Kafka Training Overview
This Introduction to Kafka for C# Developers training course teaches attendees how to use the Apache Kafka event streaming platform for high-performance data pipelines, streaming analytics, data integration, and mission-critical applications. .NET Core is used as the underlying framework.
Location and Pricing
Accelebrate offers instructor-led enterprise training for groups of 3 or more online or at your site. Most Accelebrate classes can be flexibly scheduled for your group, including delivery in half-day segments across a week or set of weeks. To receive a customized proposal and price quote for private corporate training on-site or online, please contact us.
In addition, some courses are available as live, instructor-led training from one of our partners.
Objectives
- 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 the characteristics and architecture of 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 fault-tolerance of Kafka
Prerequisites
- Having a basic understanding of messaging, cloud, development, architecture, and virtualization is beneficial.
- Experience developing .NET applications with C# is required. Prior .NET Core experience is recommended.
Outline
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Introduction to Kafka
- Messaging Architectures
- What is Kafka?
- When to Use Kafka?
- Kafka Architecture
- Core concepts in Kafka
- 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
- The confluent CLI Command Examples
- Kafka Cluster Planning – Producer/Consumer Throughput
- 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
- Avro Schema Example
- JSON Schema Example
- Managing Data Evolution Using Schemas
- Confluent Schema Registry
- Confluent Schema Registry in a Nutshell
- Schema Management on Confluent Cloud
- 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
- 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 Connect Example – File Source
- Kafka Connect Example – File Sink
Kafka Security
- Kafka Security
- Encryption and Authentication using SSL
- Configuring Kafka Brokers
- Authenticating Using SASL
- Authorization and ACLs
- Securing a Running Cluster
- ZooKeeper Authentication
Monitoring Kafka
- 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
- Partitions
- Consumers
- Producers
- Brokers
Conclusion
Training Materials
All Kafka training students receive comprehensive courseware.
Software Requirements
Attendees will not need to install any software on their computers for this class. The class will be conducted in a remote environment that Accelebrate will provide; students will only need a local computer with a web browser and a stable Internet connection. Any recent version of Microsoft Edge, Mozilla Firefox, or Google Chrome will work well.
