This repository contains the documentation for the Nephio project.
We are in the middle fo moving the documentation from a GitHub based documentation to a Hugo / Docsy based documentation site. The content of this repo (especially this) branch will be a bit chaotic during this time.
1 The site is using Hugo as the documentation generating engine, therefore you need to install Hugo. As the Docsy
template that we use requires transforming Sass to CSS, you will need to install the extended version of Hugo.
Link to installation instructions is here. To ensure that you have the
extended version of Hugo, run hugo version
. The version string should have the word extended in it (Or hugo version | grep extended
should not be an empty line).
2 Some functions of the theme generation are using NPM packages, therefore NodeJS and NPM will be needed. For
compatibility reasons a Node version of at least v16.20.2 is needed. To install this version of NodeJS, follow the
instructions from deb.nodesource.com and set the NODE_MAJOR=20
.
3 Install the npm dependencies with npm install
To build and see the documentation locally run hugo serve
. To double-check if the site will build on Netifly run hugo --gc --minify
.
Welcome to the R1 release of Nephio. Please use the documentation links below to learn more about Nephio R1, or checkout our Learning Nephio with R1 series, which includes a demo video and short articles about different aspects of R1.
Our mission is "to deliver carrier-grade, simple, open, Kubernetes-based cloud native intent automation and common automation templates that materially simplify the deployment and management of multi-vendor cloud infrastructure and network functions across large scale edge deployments." But what does that mean? With this release and the accompanying documentation, we hope to make that clear.
The mission outlines the basic goals and the About Nephio page describes the high-level architecture of Nephio. It is important to understand that Nephio is about managing complex, inter-related workloads at scale. If we simply want to deploy a network function, existing methods like Helm charts and scripts are sufficient. Similarly, if we want to deploy some infrastructure, then using existing Infrastructure-as-Code tools can accomplish that. Configuring running network functions can already be done today with element managers.
So, why do we need Nephio? The problems Nephio wants to solve start only once we try to operate at scale. "Scale" here does not simply mean "large number of sites". It can be across many different dimensions: number of sites, number of services, number of workloads, size of the individual workloads, number of machines needed to operate the workloads, complexity of the organization running the workloads, and other factors. The fact that our infrastructure, workloads, and workload configurations are all interconnected dramatically increases the difficulty in managing these architectures at scale.
To address these challenges, Nephio follows a few basic principles that experience has shown to enable higher scaling with less management overhead:
- Intent-driven to enable the user to specify "what they want" and let the system figure out "how to make that happen".
- Distributed actuation to increase reliability across widely distributed fleets.
- Uniformity in systems to reduce redundant tooling and processes, and simplify operations.
Additionally, Nephio leverages the "configuration as data" principle. This methodology means that the "intent" is captured in a machine-manageable format that we can treat as data, rather than code. In Nephio, we use the Kubernetes Resource Model (KRM) to capture intent. As Kubernetes itself is already an intent-driven system, this model is well suited to our needs.
To understand why we need to treat configuration as data, let's consider an example. In a given instance, a network function may have, say, 100 parameters that need to be decided upon. When we have 100 such network functions, across 10,000 clusters, this results in 100,000,000 inputs we need to define and manage. Handling that sheer number of values, with their interdependencies and a need for consistency management between them, requires data management techniques, not code management techniques. This is why existing methodologies begin to break down at scale, particular edge-level scale.
Consider as well that no single human will understand all of those values. Those values relate not only to workloads, but also to the infrastructure we need to support those workloads. They require different areas of expertise and different organizational boundaries of control. For example, you will need input from network planning (IP address, VLAN tags, ASNs, etc.), input from compute infrastructure teams (types of hardware or VMs available, OS available), Kubernetes platform teams, security teams, network function experts, and many, many other individuals and teams. Each of those teams will have their own systems for tracking the values they control, and processes for allocating and distributing those values. This coordination between teams is a fundamental organizational problem with operating at scale. The existing tools and methods do not even attempt to address these parts of the problem; they start once all of the "input" decisions are made.
The Nephio project believes the organizational challenge around figuring out these values is actually one of the primary limiting factors to achieving efficient management of large, complex systems at scale. This gets even harder when we realize that we need to manage changes to these values over time, and understand how changes to some values implies the need to change other values. This challenge is currently left to ad hoc processes that differ across organizations. Nephio is working on how to structure the intent to make it manageable using data management techniques.
This release of Nephio focuses:
- Demonstrating the core Nephio principles such as Configuration-as-Data and leveraging the intent-driven, active-reconciliation nature of Kubernetes.
- Infrastructure orchestration/automation using controllers based on the Cluster API. At this time only KIND cluster creation is supported.
- Orchestration/automation of 5G core network functions deployment and management. This release focuses on network functions from free5gc.
While the current release uses Cluster API, KIND, and free5gc for demonstration purposes, the exact same principles and even code can be used for managing other infrastructure and network functions. The uniformity in systems principle means that as long as something is manageable via the Kubernetes Resource Model, it is manageable via Nephio.