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Visual Graph for Kubernetes (VGK) is a system used to define any Kubernetes API Objects through a Low-Code Visual Graphing System.

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Visual Graph for Kubernetes (VGK)

Visual Graph for Kubernetes (VGK) is a low-code Visual Graphing system to create and script Objects on Kubernetes. VGK is comprised of VisualGraphs and VisualSubGraphs objects.

Figure 1.) Mock Design

vgk reference architecture


Visual Graphs

VisualGraphs are defined by GraphInputs and GraphNodes which are used together to orechestrate a visual user experience around creating and maintaining Objects on Kubernetes. Supporting a wide vareity of use cases, Visual Graphs are typically used to construct entire Application Deployments, CI/CD Pipelines, Secret/ConfigMap Injection but can also be used for nearly limitless possibilities - Any Defined Object in the Kuberetes API can be leveraged in this low-code Visual Scripting Tool.

GraphInputs are user-created variables that can represent any Object Reference on the cluster -or- YAML primitive (like strings, booleans, ints, etc.). GraphInputs ared used in conjunction with GraphNodes to act as Inputs to complete the Object Defintions.


GraphNodes

GraphNodes are the primary building block for VisualGraphs and are generated for every well-defined Object Definition on the target cluster's Kuberentes API (CRDs & k8s-core Object Definitions). GraphNodes are logically equivalent to the YAML Schema they represent.

Figure 2.) GraphNode Concept - GraphNodes grow dynamically based on the Data Inputs Required to make an Object Instance of that given kind

vgk graphnode concept

Required and Optional Fields for the Schema are defined as Inputs, they are visually represented as Connectors on the GraphNodes Left-Side and support Connections from GraphInputs and other GraphNodes Outputs.

Outputs are relatively standard across GraphNodes where there is typically only 1 Output defined as stdout - which in the case of VisualGraphs, the stdout is always the GraphNodes with its Inputs applied resulting in a Complete YAML Object Definition. Occasionally, multiple Outputs are used which implies that the given GraphNode is typically linked together in sequence with other GraphNodes (Tekton Pipeline Tasks, etc.) where a specific order is required and preserved.

Figure 3.) GraphNode Example - Notice the stdin and stdout used as givens, the ability to create objects from YAML Defs and get the final Output as YAML

vgk graphnode concept


Graph Utility Nodes

VGK also provides GraphUtilityNodes which are common Utilities and Helper Functions commonly used to make VisualGraphs more effective and create Shortcuts for doing longer/tedious cluster tasks.

Figure 4.) GraphUtilityNodes Concept - Utilities and Helper Functions to make building on Kubernetes easier and streamlined

vgk utility node concept

GraphUtilityNodes Operations List:

Operation - Description
ToEnvVar => Output N Inputs as 1 Output in common Environment Variable form for Deployments
Substitute => Perform Variable Substitution on 1 Input YAML with N Inputs of substitution Values / Secrets / ConfigMaps and create 1 Output YAML that is fully substituted with the N Inputs
Diff => Perform a Diff between N Inputs of YAML and create 1 Output of the resulting Diff YAML
Merge => Perform a Merge between N Inputs of YAML and create 1 Output of the resulting Merged YAML

What is it?

  • Operator (first and foremost)
  • Visual Graph User Interface
    • Focus 1: OpenShift Console Dynamic Plugin
    • Focus 2: General k8s UI

Original Abstract

My idea comes from a lot of tools I've been using recently (Game Engines like Unity and Unreal, Circuit Builders, etc.), they've all started implementing a very dynamic and useful Visual Graph System that uses dynamic Nodes to take inputs and outputs and drive configurations/process/etc.

My rendition is the OpenShift Visual Graph: Completely architect, manage, and scale entire application systems using a Visual Graph/Node system. The Visual Graph Node Toolbox contains every API Schema/Definition on OpenShift since they are generated from the active API where it's installed.

Graph Nodes are dynamic and operate on Inputs & Outputs - Inputs are defined as any Object Reference on-platform or Primitive supported by YAML, Outputs are any resulting Data or Object Reference that is created as a result of the Graph Node operating on its Inputs.

The Graph Node Toolbox also supports a number of Utility Core Nodes, These are Graph Nodes like Substitute, ToEnvVar, Aggregate, Combine, Diff, and more. Utility Core Nodes provide mechanisms to Manipulate Inputs & Outputs of other Nodes and Variables (typically String / YAML operations).

All of this combines to provide a fully dynamic and visual system to creating anything in OpenShift, providing a whole new experience for usability/visibility of Application Development & Delivery.

OpenShift Visual Graph Instances are a defined instance of a Graph. This definition, as seen in the editor below, leverages Utility Core Nodes to combine Secrets with Yaml Definitions as well as take many Inputs and output them as Environment Variables for another Object - The Pipeline Node will generate an OpenShift Pipeline & The Deployment Node will generate an OpenShift Deployment, all with the provided Inputs and manipulations. Making an V1 of a fully visual experience to building complex applications on OpenShift.

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Visual Graph for Kubernetes (VGK) is a system used to define any Kubernetes API Objects through a Low-Code Visual Graphing System.

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