Knative vs Kueue

Introduction

This page compares two Kubernetes-native technologies that serve different but complementary purposes in cloud-native applications: Knative and Kueue.

Overview

Feature	Knative	Kueue
Primary Purpose	Serverless platform for event-driven applications	Job queueing and resource management system
Focus	Serving and eventing for serverless workloads	Batch job scheduling and resource management
Components	Serving, Eventing	Job queueing and scheduling
Scale to Zero	Yes	No (designed for batch workloads)
Auto Scaling	Yes, traffic/event-based	No, focuses on resource quota management
Best For	Short-lived, event-driven microservices	Batch processing, ML workloads, HPC

Knative

Knative is a platform for building, deploying, and managing serverless workloads on Kubernetes. It consists of two main components:

Knative Serving

• Deploys and serves containerized applications
• Automatic scaling based on demand (including scale-to-zero)
• Traffic management with revisions and splitting
• Simplified developer experience with service abstractions

Knative Eventing

• Event-driven architecture support
• Connects event producers to consumers
• Supports event sources like Kafka, CloudEvents, etc.
• Event routing, transformation, and filtering

Use Cases

• Serverless APIs and microservices
• Event-driven architectures
• Modernizing legacy applications with serverless components
• Simplifying container deployment and management

Kueue

Kueue is a Kubernetes-native job queueing system focused on batch workloads and resource management.

Key Features

• Manages resource quotas for batch workloads
• Fair-share scheduling of compute resources
• Job preemption and prioritization
• Supports multi-tenancy for batch processing
• Designed for data processing and machine learning workloads

Core Concepts

• ClusterQueue: Defines resources available to a set of cohorts
• LocalQueue: Namespace-scoped queues that use resources from ClusterQueues
• Admission Check: Controls when workloads can start based on available resources
• Quota Management: Manages quota allocation across multiple tenants

Use Cases

• Machine learning training jobs
• Data processing pipelines
• High Performance Computing (HPC) workloads
• Resource-intensive batch jobs

When to Use Which

Choose Knative when:

• Building event-driven microservices
• Deploying serverless applications
• Need automatic scaling including scale-to-zero
• Working with event sources and sinks

Choose Kueue when:

• Running batch processing workloads
• Managing resource-intensive computing jobs
• Need fair resource allocation across teams
• Working with machine learning training pipelines
• Need sophisticated queue management for jobs

Using Together

Knative and Kueue can complement each other in a Kubernetes ecosystem:

• Knative can handle the serving and eventing parts of your application
• Kueue can manage resource-intensive batch jobs triggered by events
• Together they provide a comprehensive platform for both serverless and batch processing workloads