KDL: A Notation to Describe Kubernetes Application Deployments

This post illustrates a graphical notation for Kubernetes API objects: Kubernetes Deployment Language (KDL). Kubernetes API objects can be used to describe how a solution will be deployed in Kubernetes.

KDL is helpful for describing and documenting how applications will be deployed in Kubernetes and is especially useful when these applications are comprised of several components. I’ve created a simple graphical convention to describe these deployments, so that the diagram could be easily whiteboarded and captured in a document.

To better understand the objective, you can draw a parallel to UML, which had several graphical languages to describe different aspects of application architecture. The difference between UML and KDL is we don’t have to do forward or reverse engineering (that is, we don’t convert the diagrams in yaml files or vice versa). This way we can manage how much information we want to display in the diagrams. As a general rule of thumb we will only display architecturally relevant information.

Here you can find a git repo with the latest version of KDL and you can also download a visio stencil for the proposed notation.

Kubernetes API Objects

In general, Kubernetes API objects cover the following areas:

Area Color convention Example
OpenShift Cluster Red The Kubernetes cluster(s) involved in the solution
Compute Green Deployment
Networking Yellow Service
Storage Blue Persistent Volume Claim. Persistent Volume

Kubernetes cluster

The Kubernetes cluster is simply represented as a rectangle:

Kubernetes rectangle

All the other API objects will live inside the cluster or at its edges. There should never be a need to call out individual nodes of a Kubernetes cluster.

You can represent components outside the cluster and show how they connect to components inside the cluster. This graphical convention does not cover components outside the cluster.

Compute

The compute objects are the most complex. In general, they are represented by a rectangle with badges around it to show additional information. Here is a template:
Networking config template

The central section of the image represents a pod. In it we can find one or more containers. Both pod and containers should have a name.

On the left side of the pod we have additional compute information. The top badge specifies the type of controller for this pod. Here are the types of controllers and their abbreviations:

Type of controller Abbreviation
Replication Controller RC
Replica Set RS
Deployment D
DeploymentConfig (OpenShift only) DC
DaemonSet DS
StatefulSet SS
Job J
Cron Job CJ

On the bottom, we have the cardinality of the instances of that pod. This field assumes different meaning and format depending on the type of controller. Here is a reference table:

Type Of Controller Format
Replication Controller A number or a range (for example, 3 or 2:5)
ReplicaSet A number or a range (for example, 3 or 2:5)
Deployment A number or a range (for example, 3 or 2:5)
DeploymentConfig (OpenShift only) A number or a range (for example, 3 or 2:5)
DaemonSet The node selector: storage-node=true
StatefulSet A number: 3
Job A number representing the degree of parallelism: 3
Cron Job A number representing the degree of parallelism: 3

At the top of the pod we have the exposed ports. You can use the little badges to just show the port number or add the port name. Here is an example:

Port name

These badges are in yellow because they represent networking config. You can connect each port with the container that is actually exposing that port, if relevant. But in most cases this will not be necessary because most pods have just one container.

At the bottom of the pod we have the attached volumes. The name of the volume should be displayed in the rectangle. In most cases these will be persistent volumes. If the volume type is not a persistent volume it may be relevant to show it. Also, sometimes it may be important to show the mount point. Here are examples of acceptable notation:

Volumes emptyDir

The right side of the pod will have volumes that pertain to the configuration of the pod: secrets and configmaps. The name of the data volume should be indicated. It is important to distinguish between configmaps and secrets, so the type of volume should be indicated. If necessary, the mount point can also be shown. See these examples:

 Data volume

Networking

There are two types of networking objects: services and ingresses (routes in OpenShift).

Services

A service can be represented with an oval as in the following picture:

Service

On the left side is a badge representing the type of service. The possible abbreviations are below:

Type Abbreviation
Cluster IP CIP
Cluster IP, ClusterIP: None HS a.k.a. Headless service
Node Port NP
LoadBalancer LB
External Name (OpenShift only) EN
External IP EIP

The exposed ports are at the top of the service. The same convention applies here as for the compute ports.

The service should be connected to a compute object. This will implicitly define the service selector, so there is no need to have it indicated in the picture. If a service allows traffic from the outside of the cluster to internal pods, such as for LoadBalancer or Node Port or External IP, it should be depicted on the edge of the cluster.

Cluster

The same concept applies to services that regulate outbound traffic, such as External Name. However, in this case, they would probably appear at the bottom of the OpenShift cluster rectangle.

Ingresses

Ingresses can be indicated with a parallelogram as in this image:
Ingresses

An ingress shows the ingress name and, optionally, the host exposed. An ingress will be connected to a service (the same rules apply to OpenShift routes). Ingresses are always shown at the edge of the OpenShift cluster.

Ingresses 2

Storage

Storage is used to indicate persistent volumes. The color of storage is blue and its shape is a bucket, as seen in the following image:

Storage bucket

Storage should indicate the persistent volume name and the storage provider, for example, NFS, gluster, etc.

Persistent storage is always depicted at the edge of the cluster because it’s a configuration pointing to an externally available storage.

Persistent storage

Putting it all together

Here’s an example how this notation can be used to describe the deployment of an application. Our application is a bank service application that uses a mariadb database as its datastore. Here is the deployment diagram:

Deployment diagram

Notice that the mariadb pod uses StatefulSet and a persistent volume for its data. This pod is not exposed externally to the cluster, but its service is consumed by the BankService app.

The BankService app is a stateless pod controlled by a deployment config which has a secret with the credentials to access the database. It also has a service and a route so that it can accept inbound connections from outside the cluster.

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  • Fish

    The author explicitly decouples the diagrams from implementation (“we don’t convert the diagrams in yaml files or vice versa”) which basically means that your diagrams are almost definitely to be out of sync with implementation.

    • Raffaele Spazzoli

      please see the answer to @pablogl:disqus , it applies also to your comment.

      • Pablo G

        @raffaelespazzoli:disqus Sorry, what answer you’re referring to? I got confused now.

        For clarify, I wasn’t suggesting adding reverse/forward engineering to KDL. Instead, I was asking for the possibility of having a simplified DSL to generate the diagrams that would cater for non-visio users. Like the PlantUML language to generate UML diagrams.

  • oso2k

    Thank Raffaele. I really like this. It keeps things mostly simple which is how I prefer my flowcharts, workflow, dataflow diagrams and swim lane charts.

  • Pablo Gomes Ludermir

    Quite interesting. If the plan is to have a simple approach to visualise your k8s configuration, why not also create a DSL to generate the diagrams (instead of using Visio)? Using an approach similar to PlantUML for example.