This document provides an overview of Apache ZooKeeper and Apache Kafka, two fundamental technologies in the world of distributed systems. We'll explore what each is, their basic setup concepts, and highlight their core features, concluding with why they are often used together.
What is Apache ZooKeeper?
Apache ZooKeeper is an open-source, centralized service for maintaining configuration information, naming, providing distributed synchronization, and group services. It's designed for highly reliable distributed coordination, acting as a single source of truth for distributed applications.
Basic Setup Concepts
- Ensemble: A ZooKeeper deployment consists of a cluster of ZooKeeper servers, known as an ensemble. For fault tolerance, it's recommended to have an odd number of servers (e.g., 3, 5, 7).
- Leader and Followers: Within an ensemble, one server is elected as the leader, and the others are followers. All write requests go through the leader, which then propagates changes to followers. Read requests can be served by any server.
- Znodes: ZooKeeper's data is stored in a hierarchical namespace, similar to a file system, with data nodes called "znodes". Each znode can store data and have children.
- Client Port: Clients (like Kafka brokers) connect to ZooKeeper via a specific port (default 2181) to read or write data.
Feature Highlights
- Distributed Synchronization: Provides primitives like distributed locks, queues, and barriers, essential for coordinating processes across multiple machines.
- Configuration Management: Stores and manages configuration data for distributed applications, allowing clients to receive updates when configurations change.
- Naming Service: Acts as a centralized registry for distributed services, allowing them to discover each other.
- Failure Detection: Clients maintain a persistent connection with ZooKeeper, and if a connection is lost, ZooKeeper can detect client failures and remove ephemeral nodes.
- High Availability: Achieved through replication across the ensemble; if a server fails, others can take over.
What is Apache Kafka?
Apache Kafka is a distributed streaming platform capable of handling trillions of events per day. It's primarily used for building real-time data pipelines and streaming applications. Kafka combines messaging, storage, and stream processing to allow storage and analysis of both historical and real-time data.
Basic Setup Concepts
- Brokers: A Kafka cluster consists of one or more servers, called brokers. Brokers store data, serve client requests, and replicate data for fault tolerance.
- Topics: Data streams in Kafka are organized into categories called topics. Topics are logical channels for publishing and subscribing to data.
- Partitions: Topics are divided into partitions. Each partition is an ordered, immutable sequence of records. Partitions enable parallelism and scalability across brokers.
- Producers: Client applications that publish (write) records to Kafka topics.
- Consumers: Client applications that subscribe to (read) records from Kafka topics. Consumers read from specific partitions within a topic.
- Consumer Groups: Multiple consumers can form a consumer group to share the load of reading from a topic's partitions, ensuring that each message is processed by only one consumer within the group.
Feature Highlights
- High Throughput: Capable of handling millions of messages per second with very low latency.
- Scalability: Horizontally scalable by adding more brokers and partitions, allowing it to grow with data volume.
- Durability: Messages are persisted to disk and replicated across multiple brokers, ensuring data is not lost even if a broker fails.
- Fault Tolerance: Designed to withstand broker failures; data remains available and accessible.
- Decoupling: Producers and consumers are decoupled, allowing them to operate independently without direct knowledge of each other.
- Real-time Processing: Enables applications to process data as it arrives, supporting real-time analytics and event-driven architectures.
Why Kafka and ZooKeeper Work Together
Historically, Kafka uses ZooKeeper for critical cluster management functions. While newer Kafka versions are reducing this dependency, in many common deployments, ZooKeeper provides:
- Broker Registration: Kafka brokers register themselves with ZooKeeper, allowing producers and consumers to discover available brokers.
- Controller Election: ZooKeeper helps elect a "controller" broker in the Kafka cluster, which is responsible for managing partitions and replicas.
- Configuration Storage: Stores metadata about Kafka topics, partitions, and access control lists (ACLs).
- Cluster Membership: Tracks the live status of Kafka brokers, enabling failure detection.
In essence, ZooKeeper acts as the "brain" for Kafka's distributed coordination, ensuring that the Kafka cluster operates smoothly and reliably.