WebAssembly / WASI Workloads
Overview
CAPZ enables you to create WebAssembly (Wasm) / WASI pod workloads targeting the Deislabs Slight, Fermyon Spin, Lunatic, or VMware Wasm Workers Server frameworks for building and running fast, secure microservices on Kubernetes.
NOTE: Images built with image-builder version v0.1.22 or later support all four Wasm runtimes.
All of the runtimes (lunatic, slight, spin, and wws) for running Wasm workloads are embedded in containerd shims by the deislabs/containerd-wasm-shims project which is built upon containerd/runwasi. These containerd shims enable Kubernetes to run Wasm workloads without needing to embed the Wasm runtime in each OCI image.
Deislabs Slight (SpiderLightning)
Slight (or SpiderLightning) is an open source wasmtime-based runtime that provides cloud capabilities to Wasm microservices. These capabilities include key/value, pub/sub, and much more.
Fermyon Spin
Spin is an open source framework for building and running fast, secure, and composable cloud microservices with WebAssembly. It aims to be the easiest way to get started with WebAssembly microservices, and takes advantage of the latest developments in the WebAssembly component model and Wasmtime runtime.
Lunatic
Lunatic is a universal open source runtime for fast, robust and scalable server-side applications. It’s inspired by Erlang and can be used from any language that compiles to WebAssembly.
VMware Wasm Workers Server
Wasm Workers Server is an open source framework that allows you to develop and run serverless applications using a lightweight construct called “workers”. The server itself is implemented as a self-contained binary that routes HTTP requests to a WebAssembly runtime that hosts the workers.
Applying the Wasm Runtime Classes
By default, CAPZ virtual machine images include containerd shims to run lunatic, slight, spin, and wws workloads. To inform Kubernetes about the ability to run Wasm workloads on CAPZ nodes, you must apply a runtime class for one or more runtimes to your workload cluster.
Create a wasm-runtimes.yaml file with the following contents to enable all four runtimes:
---
apiVersion: node.k8s.io/v1
kind: RuntimeClass
metadata:
name: "wasmtime-lunatic-v1"
handler: "lunatic"
---
apiVersion: node.k8s.io/v1
kind: RuntimeClass
metadata:
name: "wasmtime-slight-v1"
handler: "slight"
---
apiVersion: node.k8s.io/v1
kind: RuntimeClass
metadata:
name: "wasmtime-spin-v2"
handler: "spin"
---
apiVersion: node.k8s.io/v1
kind: RuntimeClass
metadata:
name: "wasmtime-wws-v1"
handler: "wws"
Deploy these resources to your workload cluster:
kubectl --kubeconfig=<workload-kubeconfig> apply -f wasm-runtimes.yaml
The preceding YAML document will register runtime classes for lunatic, slight, spin, and wws, which will direct containerd to use the appropriate shim when a pod workload is scheduled onto a cluster node.
Running an Example Spin Workload
With the runtime classes registered, we can now schedule Wasm workloads on our nodes by creating a Kubernetes Deployment and Service. Create a spin.yaml file with the following contents:
---
apiVersion: apps/v1
kind: Deployment
metadata:
name: wasm-spin
spec:
replicas: 3
selector:
matchLabels:
app: wasm-spin
template:
metadata:
labels:
app: wasm-spin
spec:
runtimeClassName: wasmtime-spin-v2
containers:
- name: spin-hello
image: ghcr.io/deislabs/containerd-wasm-shims/examples/spin-rust-hello:latest
command: ["/"]
resources:
requests:
cpu: 10m
memory: 10Mi
limits:
cpu: 500m
memory: 128Mi
---
apiVersion: v1
kind: Service
metadata:
name: wasm-spin
spec:
type: LoadBalancer
ports:
- protocol: TCP
port: 80
targetPort: 80
selector:
app: wasm-spin
Deploy these resources to your workload cluster:
kubectl --kubeconfig=<workload-kubeconfig> apply -f spin.yaml
The preceding deployment and service will create a load-balanced “hello world” service with 3 Spin microservices. Note the runtimeClassName applied to the Deployment, wasmtime-spin-v2, which informs containerd on the cluster node to run the workload with the Spin v2 shim.
A Running Spin Microservice
With the service and the deployment applied, you should now have a Spin microservice running in your workload cluster. If you run the following command against the workload cluster, you can find the IP for the wasm-spin service.
kubectl --kubeconfig=<workload-kubeconfig> get services -w
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE
kubernetes ClusterIP 10.96.0.1 <none> 443/TCP 14m
wasm-spin LoadBalancer 10.105.51.137 20.121.244.48 80:30197/TCP 3m8s
In the preceding output, we can see the wasm-spin service with an external IP of 20.121.244.48. Your external IP will be different, but that is expected.
Next, let’s connect to the service and get a response from our Wasm microservice. You will need to replace the placeholder IP address below with the your external IP address from the preceding output.
curl http://20.121.244.48/hello
Hello world from Spin!
In the preceding output, we see the HTTP response from our Spin microservice, “Hello world from Spin!”.
Building a Lunatic, Spin, Slight, or WWS Application
At this point, you might be asking “How do I build my own Wasm microservice?” Here are some pointers to help you get started.
Example lunatic Application
To learn more about building lunatic applications, see the Lunatic README.
Example slight Application
The slight example in deislabs/containerd-wasm-shims repo demonstrates a project layout for creating a container image consisting of a slight app.wasm and a slightfile.toml, both of which are needed to run the microservice.
To learn more about building slight applications, see Deislabs Slight.
Example spin Application
The spin example in deislabs/containerd-wasm-shims repo demonstrates a project layout for creating a container image consisting of two spin apps, spin_rust_hello.wasm and spin_go_hello.wasm, and a spin.toml file.
To learn more about building spin applications, see Fermyon Spin.
Example wws Application
The wws examples in vmware-labs/wasm-workers-server repo demonstrate project layouts for wws workers in multiple languages.
To learn more about building wws applications, see VMware Wasm Workers Server.
Constraining Scheduling of Wasm Workloads
You may have a cluster where not all nodes are able to run Wasm workloads. In this case, you would want to constrain the nodes that are able to have Wasm workloads scheduled.
If you would like to constrain the nodes that will run the Wasm workloads, you can apply a node label selector to the runtime classes, then apply node labels to the cluster nodes you’d like to run the workloads.
Create a wasm-runtimes-constrained.yaml file with the following contents:
---
apiVersion: node.k8s.io/v1
kind: RuntimeClass
metadata:
name: "wasmtime-lunatic-v1"
handler: "lunatic"
scheduling:
nodeSelector:
"cluster.x-k8s.io/wasmtime-lunatic-v1": "true"
---
apiVersion: node.k8s.io/v1
kind: RuntimeClass
metadata:
name: "wasmtime-slight-v1"
handler: "slight"
scheduling:
nodeSelector:
"cluster.x-k8s.io/wasmtime-slight-v1": "true"
---
apiVersion: node.k8s.io/v1
kind: RuntimeClass
metadata:
name: "wasmtime-spin-v2"
handler: "spin"
scheduling:
nodeSelector:
"cluster.x-k8s.io/wasmtime-spin-v2": "true"
---
apiVersion: node.k8s.io/v1
kind: RuntimeClass
metadata:
name: "wasmtime-wws-v1"
handler: "wws"
scheduling:
nodeSelector:
"cluster.x-k8s.io/wasmtime-wws-v1": "true"
Deploy these resources to your workload cluster:
kubectl --kubeconfig=<workload-kubeconfig> apply -f wasm-runtimes-constrained.yaml
In the preceding YAML, note the nodeSelector and the label. The Kubernetes scheduler will select nodes with the cluster.x-k8s.io/wasmtime-lunatic-v1: "true", cluster.x-k8s.io/wasmtime-slight-v1: "true", cluster.x-k8s.io/wasmtime-spin-v2: "true", or cluster.x-k8s.io/wasmtime-wws-v1: "true" label to determine where to schedule Wasm workloads.
You will also need to pair the above runtime classes with labels applied to your cluster nodes. To label your nodes, use a command like the following:
kubectl --kubeconfig=<workload-kubeconfig> label nodes <your-node-name> <label>
Once you have applied node labels, you can safely schedule Wasm workloads to a constrained set of nodes in your cluster.