Azure Kafka Services - MSDN Documentation

Overview

Azure provides several options for running Apache Kafka, catering to different needs and management preferences. These options allow you to leverage the power of Kafka within the robust Azure ecosystem.

Azure Managed Kafka (e.g., Azure Event Hubs with Kafka Endpoint)

Azure Event Hubs is a highly scalable data streaming platform and event ingestion service. It supports Kafka protocol, allowing you to use Kafka applications with Event Hubs without significant code changes. This is a fully managed service, meaning Azure handles the infrastructure, scaling, and maintenance.

Key Features: High throughput, low latency, durable storage, SDKs for various languages, integration with other Azure services.
Use Cases: Real-time analytics, event-driven architectures, log aggregation, IoT data streaming.
Getting Started: Create an Event Hubs Namespace.

Self-Managed Kafka on Azure Virtual Machines

For complete control over your Kafka cluster, you can deploy and manage your own Kafka instances on Azure Virtual Machines. This approach provides maximum flexibility but requires more operational overhead.

Considerations: Requires careful planning for zookeeper, broker configuration, scaling, monitoring, and disaster recovery.
Recommended Tools: Apache Kafka, Apache ZooKeeper, Azure VM Scale Sets for scaling.
Deployment Guides: Refer to the official Apache Kafka documentation for deployment best practices.

Azure Kubernetes Service (AKS) with Kafka Operators

Running Kafka on AKS using operators (like Strimzi) offers a balance between managed services and self-management. Operators automate the deployment, scaling, and management of Kafka clusters on Kubernetes.

Benefits: Simplified cluster management, automated operations, integration with Kubernetes ecosystem.
Key Components: Strimzi Kafka Operator, Kafka brokers, ZooKeeper.
Tutorials: Deploy Kafka on AKS with Strimzi.

Choosing the Right Option

The best Kafka solution for you depends on your requirements:

Recommendation: For most users looking for a managed, scalable, and cost-effective solution, Azure Event Hubs with its Kafka endpoint is the recommended choice.

Managed Service (Event Hubs): Ideal for ease of use, scalability, and reduced operational burden.
Full Control (VMs): Necessary when you need specific Kafka configurations, custom plugins, or absolute control over the environment.
Kubernetes-Native (AKS): Suitable for organizations already heavily invested in Kubernetes and seeking automated cluster management.

Key Concepts

Topics

Kafka messages are organized into categories called topics. Producers publish messages to topics, and consumers subscribe to topics to read messages.

Producers

Applications that publish (write) messages to Kafka topics.

Consumers

Applications that subscribe to (read) messages from Kafka topics.

Brokers

Kafka servers that store messages and serve read/write requests from producers and consumers. Multiple brokers form a Kafka cluster.

ZooKeeper

Traditionally used for managing cluster state, leader election, and configuration. In modern Kafka deployments, it's often managed by operators or cloud services.

Partitions

Topics are divided into partitions. This allows for parallel processing and increased throughput. Messages within a partition are ordered.

Common Scenarios

Security Note: Always use TLS/SSL encryption and SASL authentication for securing your Kafka communication, especially in production environments.

Real-time Data Processing: Ingesting streaming data from sources like IoT devices or web applications for immediate analysis.
Event Sourcing: Using Kafka as a central event log to store all state changes in an application.
Message Queuing: Decoupling microservices by using Kafka as a reliable message bus.
Log Aggregation: Centralizing logs from distributed systems for monitoring and analysis.

Next Steps

Explore the following resources to learn more: