DPs and Data Model

When Kuma (kuma-cp) runs, it will be waiting for the data-planes to connect and register themselves. In order for a data-plane to successfully run, two things have to happen before being executed:

  • There must exist at least one Mesh in Kuma. By default the system auto-generates a default Mesh when the control-plane is run for the first time.
  • There must exist a Dataplane entity in Kuma before the actual data-plane tries to connect to it via kuma-dp.

DPs and Data Model - 图1

On Universal the Dataplane entity must be manually created before starting kuma-dp, on Kubernetes it is automatically created.

Dataplane Entity

A Dataplane entity must be created on the CP kuma-cp before a kuma-dp instance attempts to connect to the control-plane. On Kubernetes, this operation is fully automated. On Universal, it must be executed manually.

To understand why the Dataplane entity is required, we must take a step back. As we have explained already, Kuma follow a sidecar proxy model for the data-planes, where we have an instance of a data-plane for every instance of our services. Each Service and DP will communicate with each other on the same machine, therefore on 127.0.0.1.

For example, if we have 6 replicas of a “Redis” service, then we must have one instances of kuma-dp running alongside each replica of the service, therefore 6 replicas of kuma-dp as well.

DPs and Data Model - 图2

Many DPs! The number of data-planes that we have running can quickly add up, since we have one replica of kuma-dp for every replica of every service. That’s why it’s important for the DP process to be lightweight and consume a few resources, otherwise we would quickly run out of memory, especially on platforms like Kubernetes where multiple services are running on the same underlying host machine. And that’s one of the reasons why Kuma leverages Envoy for this task.

When we start a new data-plane in Kuma, two things have to happen:

  1. The data-plane needs to advertise what service it is responsible for. This is what the Dataplane entity does.
  2. The data-plane process needs to start accepting incoming and outgoing requests.

These steps are being executed in two separate commands:

  1. We register the Dataplane object via the kumactl or HTTP API.
  2. Once we have registered the DP, we can start it by running kuma-dp run.

Remember: this is all automated if you are running Kuma on Kubernetes!

The registration of the Dataplane includes two main sections that are described below in the Dataplane Specification:

  • inbound networking configuration, to configure on what port the DP will listen to accept external requests, specify on what port the service is listening on the same machine (for internal DP <> Service communication), and the Tags that belong to the service.
  • outbound networking configuration, to enable the local service to consume other services.

For example, this is how we register a Dataplane for an hypotetical Redis service and then start the kuma-dp process:

  1. echo "type: Dataplane
  2. mesh: default
  3. name: redis-1
  4. networking:
  5. inbound:
  6. - interface: 127.0.0.1:9000:6379
  7. tags:
  8. service: redis" | kumactl apply -f -
  9. kuma-dp run \
  10. --name=redis-1 \
  11. --mesh=default \
  12. --cp-address=http://127.0.0.1:5681 \
  13. --dataplane-token-file=/tmp/kuma-dp-redis-1-token

In the example above, any external client who wants to consume Redis will have to make a request to the DP on port 9000, which internally will be redirected to the Redis service listening on port 6379.

Now let’s assume that we have another service called “Backend” that internally listens on port 80, and that makes outgoing requests to the redis service:

  1. echo "type: Dataplane
  2. mesh: default
  3. name: backend-1
  4. networking:
  5. inbound:
  6. - interface: 127.0.0.1:8000:80
  7. tags:
  8. service: backend
  9. outbound:
  10. - interface: :10000
  11. service: redis" | kumactl apply -f -
  12. kuma-dp run \
  13. --name=backend-1 \
  14. --mesh=default \
  15. --cp-address=http://127.0.0.1:5681 \
  16. --dataplane-token-file=/tmp/kuma-dp-backend-1-token

In order for the backend service to successfully consume redis, we specify an outbound networking section in the Dataplane configuration instructing the DP to listen on a new port 10000 and to proxy any outgoing request on port 10000 to the redis service. For this to work, we must update our application to consume redis on 127.0.0.1:10000.

As mentioned before, this is only required in Universal. In Kubernetes no change to our applications are required thanks to automated transparent proxying.

Envoy

kuma-dp is built on top of Envoy, which has a powerful Admin APIDPs and Data Model - 图3 that enables monitoring and troubleshooting of a running dataplane.

By default, kuma-dp starts Envoy Admin API on the loopback interface (that is only accessible from the local host) and the first available port from the range 30001-65535.

If you need to override that behaviour, you can use --admin-port command-line option or KUMA_DATAPLANE_ADMIN_PORT environment variable.

E.g.,

  • you can change the default port range by using --admin-port=10000-20000
  • you can narrow it down to a single port by using --admin-port=9901
  • you can turn Envoy Admin API off by using --admin-port=

If you choose to turn Envoy Admin API off, you will not be able to leverage some of Kuma features, such as enabling Prometheus metrics on that dataplane.

Tags

A data-plane can have many labels that define its role within your architecture. It is obviously associated to a service, but can also have some other properties that we might want to define. For example, if it runs in a specific world region, or a specific cloud vendor. In Kuma these labels are called tags and they are being set in the Dataplane entity.

There is one special tag, the service tag, that must always be set.

Tags are important because can be used later on by any Policy that Kuma supports now and in the future. For example, it will be possible to route requests from one region to another assuming there is a region tag associated to the data-planes.

Dataplane Specification

The Dataplane entity includes the networking and naming configuration that a data-plane proxy (kuma-dp) must have attempting to connect to the control-plane (kuma-cp).

In Universal mode we must manually create the Dataplane entity before running kuma-dp. A Dataplane entity can be created with kumactl or by using the HTTP API. When using kumactl, the regular entity definition will look like:

  1. type: Dataplane
  2. mesh: default
  3. name: web-01
  4. networking:
  5. inbound:
  6. - interface: 127.0.0.1:11011:11012
  7. tags:
  8. service: backend
  9. outbound:
  10. - interface: :33033
  11. service: redis

And the Gateway mode‘s entity definition will look like:

  1. type: Dataplane
  2. mesh: default
  3. name: kong-01
  4. networking:
  5. gateway:
  6. tags:
  7. service: kong
  8. outbound:
  9. - interface: :33033
  10. service: backend

The Dataplane entity includes a few sections:

  • type: must be Dataplane.
  • mesh: the Mesh name we want to associate the data-plane with.
  • name: this is the name of the data-plane instance, and it must be unique for any given Mesh. We might have multiple instances of a Service, and therefore multiple instances of the sidecar data-plane proxy. Each one of those sidecar proxy instances must have a unique name.
  • networking: this is the meaty part of the configuration. It determines the behavior of the data-plane on incoming (inbound) and outgoing (outbound) requests.
    • inbound: an array of interface objects that determines what services are being exposed via the data-plane. Each interface object only supports one port at a time, and you can specify more than one interface in case the service opens up more than one port.
      • interface: determines the routing logic for incoming requests in the format of {address}:{dataplane-port}:{service-port}.
      • tags: each data-plane can include any arbitrary number of tags, with the only requirement that service is mandatory and it identifies the name of service. You can include tags like version, cloud, region, and so on to give more attributes to the Dataplane (attributes that can later on be used to apply policies).
    • gateway: determines if the data-plane will operate in Gateway mode. It replaces the inbound object and enables Kuma to integrate with existing API gateways like KongDPs and Data Model - 图4.
      • tags: each data-plane can include any arbitrary number of tags, with the only requirement that service is mandatory and it identifies the name of service. You can include tags like version, cloud, region, and so on to give more attributes to the Dataplane (attributes that can later on be used to apply policies).
    • outbound: every outgoing request made by the service must also go thorugh the DP. This object specifies ports that the DP will have to listen to when accepting outgoing requests by the service:
      • interface: the address inclusive of the port that the service needs to consume locally to make a request to the external service
      • service: the name of the service associated with the interface.

On Kubernetes this whole process is automated via transparent proxying and without changing your application’s code. On Universal Kuma doesn’t support transparent proxying yet, and the outbound service dependencies have to be manually specified in the Dataplane entity. This also means that in Universal you must update your codebases to consume those external services on 127.0.0.1 on the port specified in the outbound section.

Kubernetes

On Kubernetes the data-planes are automatically injected via the kuma-injector executable as long as the K8s Namespace includes the following label:

  1. kuma.io/sidecar-injection: enabled

On Kubernetes the Dataplane entity is also automatically created for you, and because transparent proxying is being used to communicate between the service and the sidecar proxy, no code changes are required in your applications.

Gateway

The Dataplane can operate in Gateway mode. This way you can integrate Kuma with existing API Gateways like KongDPs and Data Model - 图5.

When you use a Dataplane with a service, both inbound traffic to a service and outbound traffic from the service flows through the Dataplane. API Gateway should be deployed as any other service within the mesh. However, in this case we want inbound traffic to go directly to API Gateway, otherwise clients would have to be provided with certificates that are generated dynamically for communication between services within the mesh. Security for an entrance to the mesh should be handled by API Gateway itself.

Gateway mode lets you skip exposing inbound listeners so it won’t be intercepting ingress traffic.

Universal

On Universal, you can define such Dataplane like this:

  1. type: Dataplane
  2. mesh: default
  3. name: kong-01
  4. networking:
  5. gateway:
  6. tags:
  7. service: kong
  8. outbound:
  9. - interface: :33033
  10. service: backend

When configuring your API Gateway to pass traffic to backend set the url to http://localhost:33033

Kubernetes

On Kubernetes, Dataplane entities are automatically generated. To inject gateway Dataplane, mark your API Gateway’s Pod with kuma.io/gateway: enabled annotation. Here is example with Kong for Kubernetes:

  1. apiVersion: apps/v1
  2. kind: Deployment
  3. metadata:
  4. labels:
  5. app: ingress-kong
  6. name: ingress-kong
  7. namespace: kong
  8. spec:
  9. template:
  10. metadata:
  11. annotations:
  12. kuma.io/gateway: enabled
  13. spec:
  14. containers:
  15. image: kong:1.3
  16. ...

The optimal gateway in Kubernetes mode would be Kong. You can use Kong for KubernetesDPs and Data Model - 图6 to implement authentication, transformations, and other functionalities across Kubernetes clusters with zero downtime. When integrating Kong for KubernetesDPs and Data Model - 图7 with Kuma you have to annotate every Service that you want to pass traffic to with ingress.kubernetes.io/service-upstream=trueDPs and Data Model - 图8 annotation. Otherwise Kong will do the load balancing which unables Kuma to do the load balancing and apply policies.

For an in-depth example on deploying Kuma with Kong for KubernetesDPs and Data Model - 图9, please follow this demo application guideDPs and Data Model - 图10.