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Ryu SDN Controller Review: Python-Based Flexible Framework

Comparison of Software Defined Networking (SDN) Controllers. Ryu

Ryu (pronounced “ree-yooh,” meaning “flow” in Japanese) represents a fundamentally different approach to SDN controllers—rather than a complete platform, it’s a component-based framework that provides building blocks for creating custom SDN solutions. With a score of 73.2% in our comprehensive evaluation, Ryu’s Python-based architecture and well-defined APIs make it the preferred choice for academic research, rapid prototyping, and developers who need complete flexibility to build exactly the SDN controller they envision.

This is part of our comprehensive SDN Controller Comparison Guide, where we evaluate 6 leading open-source controllers across 13 technical criteria.

Ryu at a Glance

Attribute Details
Overall Score 73.2% (Ranked #3)
Best For Academic research, custom development, OpenStack integration
Architecture Component-based framework (toolbox approach)
Programming Language Python
Primary Protocols OpenFlow, NETCONF, OF-Config, partial P4 support
Clustering External tools required (Zookeeper)
Community Active development community, popular in academia
Key Differentiator Complete development flexibility with minimal constraints
Deployment Complexity Low to High (depends on customization)
License Apache License 2.0

What Ryu Does Best:

  • Component-based framework for building custom controllers
  • Well-defined Python APIs for rapid development
  • Popular in academic research and education
  • OpenStack Neutron integration (historical significance)
  • Low barrier to entry for Python developers

Understanding Ryu: Framework vs. Platform 

The Fundamental Difference:

Ryu is a very different proposition to the other options being put forward. Although boasting a core set of programs that are run as a ‘platform’, Ryu is better thought of as a toolbox, with which SDN controller functionality can be built.

Ryu is a component-based software defined networking framework. It provides software components with well defined API that make it easy for developers to create new network management and control applications. Ryu means “flow” in Japanese and is pronounced “ree-yooh”.

Platform vs. Framework:

Aspect Traditional Platform (ONOS/ODL) Framework (Ryu)
Out-of-Box Full-featured controller ready to use Basic components, build what you need
Applications Pre-built apps included Write your own applications
Clustering Native HA clustering DIY with external tools
GUI Production-ready web interface Basic or build your own
Intent Framework Built-in Implement if needed
Philosophy “Everything included” “Minimal core, maximum flexibility”
Learning Curve Learn the platform Learn the concepts
Use Case Production deployment Research, custom solutions, prototyping

What Ryu Provides:

Core Components:

  • OpenFlow protocol library (1.0 – 1.5)
  • Event-driven application framework
  • Network topology discovery
  • Basic switching applications (as examples)
  • NETCONF/OF-Config libraries
  • REST API framework
  • Packet parsing libraries

What You Build:

  • Custom routing algorithms
  • Specific network applications
  • High availability mechanisms
  • Telemetry and monitoring
  • Integration with other systems
  • Business logic for your network

The Toolbox Metaphor:

Think of Ryu like a woodworking toolbox:

  • Saw (OpenFlow library): Tool to interact with switches
  • Hammer (Event framework): Tool to respond to network events
  • Measuring tape (Topology discovery): Tool to understand network structure
  • Sandpaper (Packet libraries): Tool to process packets

But Ryu doesn’t tell you what to build. You decide whether you’re building a simple birdhouse (learning switch) or a complex cabinet (production router).

Architecture Deep Dive

A Ryu SDN controller composes of these components:

Comparison of Software Defined Networking (SDN) Controllers. Ryu Diagram
  • Southbound interfaces allow communication of SDN switches and controllers
  • Its core supports limited applications (e.g. Topology discovery, Learning switch) and libraries
  • External applications can deploy network policies to data planes via well-defined northbound APIs such as REST

Modularity and Extensibility

Ryu is structured differently from other solutions in that it provides simple supporting infrastructure that users of the platform must write code to utilise as desired. While this requires development expertise, it also allows complete flexibility of the SDN solution.

Scalability

Ryu does not have an inherent clustering ability and requires external tools to share the network state and allow failover between cluster members.

Cluster Scalability

  • External tools such as Zookeeper distribute a desired state. Extra instances of the controller can be started independently as long as the backing configuration remains identical.

Architectural Scalability

  • While Ryu supports high availability via a Zookeeper component, it does not yet support a co-operative cluster of controllers.

Interfaces

  • Southbound: It supports multiple southbound protocols for managing devices, such as OpenFlow, NETCONF, OF-Config, and partial support of P4
  • Northbound: Offer RESTful APIs only, which are limited compared to ONOS and ODL

Telemetry

Ryu doesn’t provide any telemetry functionality. This needs to be provided via external tools.

Resilience and Fault Tolerance

Ryu has no inbuilt clustering mechanism, instead relying on external tools to maintain availability. High availability is achieved by running multiple, identically configured instances, or a single instance controlled by an external framework that detects and restarts failed nodes.

Fault tolerance can be provided by Zookeeper for monitoring the controllers in order to detect controller’s failure and sharding state between cluster members.

Programming Language

Ryu is written in Python.

Community

An active community developing the framework, it is a well supported and targeted controller.

Conclusion

Ryu is like a toolbox with software components, which provides the SDN controller functionality. It has a support of various southbound interfaces for managing network devices. It is very popular in academia and has been used in OpenStack as a Network controller.
Next, we will be evaluating Faucet.

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