# Traefik

[Traefik](https://doc.traefik.io/) provides a service mesh and ingress solution.

We will run through some examples as shown in the notebook `service-meshes/traefik/traefik.ipynb`

## Single Model

* A Seldon Iris Model
* Traefik Service
* Traefik IngressRoute
* Traefik Middleware for adding a header

```yaml
apiVersion: v1
kind: Service
metadata:
  name: myapps
  namespace: seldon-mesh
spec:
  ports:
  - name: web
    port: 80
    protocol: TCP
  selector:
    app: traefik-ingress-lb
  type: LoadBalancer
---
apiVersion: mlops.seldon.io/v1alpha1
kind: Model
metadata:
  name: iris
  namespace: seldon-mesh
spec:
  requirements:
  - sklearn
  storageUri: gs://seldon-models/mlserver/iris
---
apiVersion: traefik.containo.us/v1alpha1
kind: IngressRoute
metadata:
  name: iris
  namespace: seldon-mesh
spec:
  entryPoints:
  - web
  routes:
  - kind: Rule
    match: PathPrefix(`/`)
    middlewares:
    - name: iris-header
    services:
    - name: seldon-mesh
      port: 80
      scheme: h2c
---
apiVersion: traefik.containo.us/v1alpha1
kind: Middleware
metadata:
  name: iris-header
  namespace: seldon-mesh
spec:
  headers:
    customRequestHeaders:
      seldon-model: iris
```

## Traffic Split

{% hint style="warning" %}
**Warning** Traffic splitting does not presently work due to this [issue](https://github.com/emissary-ingress/emissary/issues/4062). We recommend you use a Seldon Experiment instead.
{% endhint %}

## Traefik Examples

Assumes

* You have installed Traefik as per their [docs](https://doc.traefik.io/traefik/getting-started/install-traefik/#use-the-helm-chart) into namespace traefik-v2

Tested with traefik-10.19.4

```python
INGRESS_IP=!kubectl get svc traefik -n traefik-v2 -o jsonpath='{.status.loadBalancer.ingress[0].ip}'
INGRESS_IP=INGRESS_IP[0]
import os
os.environ['INGRESS_IP'] = INGRESS_IP
INGRESS_IP
```

```
'172.21.255.1'
```

### Traefik Single Model Example

```python
!kustomize build config/single-model
```

```
apiVersion: v1
kind: Service
metadata:
  name: myapps
  namespace: seldon-mesh
spec:
  ports:
  - name: web
    port: 80
    protocol: TCP
  selector:
    app: traefik-ingress-lb
  type: LoadBalancer
---
apiVersion: mlops.seldon.io/v1alpha1
kind: Model
metadata:
  name: iris
  namespace: seldon-mesh
spec:
  requirements:
  - sklearn
  storageUri: gs://seldon-models/mlserver/iris
---
apiVersion: traefik.containo.us/v1alpha1
kind: IngressRoute
metadata:
  name: iris
  namespace: seldon-mesh
spec:
  entryPoints:
  - web
  routes:
  - kind: Rule
    match: PathPrefix(`/`)
    middlewares:
    - name: iris-header
    services:
    - name: seldon-mesh
      port: 80
      scheme: h2c
---
apiVersion: traefik.containo.us/v1alpha1
kind: Middleware
metadata:
  name: iris-header
  namespace: seldon-mesh
spec:
  headers:
    customRequestHeaders:
      seldon-model: iris
```

```python
!kustomize build config/single-model | kubectl apply -f -
```

```
service/myapps created
model.mlops.seldon.io/iris created
ingressroute.traefik.containo.us/iris created
middleware.traefik.containo.us/iris-header created
```

```python
!kubectl wait --for condition=ready --timeout=300s model --all -n seldon-mesh
```

```
model.mlops.seldon.io/iris condition met
```

```python
!curl -v http://${INGRESS_IP}/v2/models/iris/infer -H "Content-Type: application/json" \
        -d '{"inputs": [{"name": "predict", "shape": [1, 4], "datatype": "FP32", "data": [[1, 2, 3, 4]]}]}'
```

```
*   Trying 172.21.255.1...
* Connected to 172.21.255.1 (172.21.255.1) port 80 (#0)
> POST /v2/models/iris/infer HTTP/1.1
> Host: 172.21.255.1
> User-Agent: curl/7.47.0
> Accept: */*
> Content-Type: application/json
> Content-Length: 94
> 
* upload completely sent off: 94 out of 94 bytes
< HTTP/1.1 200 OK
< Content-Length: 196
< Content-Type: application/json
< Date: Sat, 16 Apr 2022 15:53:27 GMT
< Seldon-Route: iris_1
< Server: envoy
< X-Envoy-Upstream-Service-Time: 895
< 
* Connection #0 to host 172.21.255.1 left intact
{"model_name":"iris_1","model_version":"1","id":"0dccf477-78fa-4a11-92ff-4d7e4f1cdda8","parameters":null,"outputs":[{"name":"predict","shape":[1],"datatype":"INT64","parameters":null,"data":[2]}]}
```

```python
!grpcurl -d '{"model_name":"iris","inputs":[{"name":"input","contents":{"fp32_contents":[1,2,3,4]},"datatype":"FP32","shape":[1,4]}]}' \
    -plaintext \
    -import-path ../../apis \
    -proto ../../apis/mlops/v2_dataplane/v2_dataplane.proto \
    ${INGRESS_IP}:80 inference.GRPCInferenceService/ModelInfer
```

```
{
  "modelName": "iris_1",
  "modelVersion": "1",
  "outputs": [
    {
      "name": "predict",
      "datatype": "INT64",
      "shape": [
        "1"
      ],
      "contents": {
        "int64Contents": [
          "2"
        ]
      }
    }
  ]
}
```

```python
!kustomize build config/single-model | kubectl delete -f -
```

```
service "myapps" deleted
model.mlops.seldon.io "iris" deleted
ingressroute.traefik.containo.us "iris" deleted
middleware.traefik.containo.us "iris-header" deleted
```

```python
```


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