Migrating From Azure Functions to Knative

Knative is an open source platform that extends Kubernetes to manage serverless workloads. It provides tools to deploy, run, and manage serverless applications and functions, enabling automatic scaling and efficient resource utilization. Knative consists of several components:

• Serving: Deploys and runs serverless containers.
• Eventing: Manages event-driven architectures.
• Functions: Deploys and runs functions locally and on Kubernetes.

This guide walks through the process of migrating an Azure function to a Knative function running on Linode Kubernetes Engine (LKE).

Before You Begin

1. Read our Getting Started with Linode guide, and create a Linode account if you do not already have one.

2. Create a personal access token using the instructions in our Manage personal access tokens guide.

3. Follow the steps in the Install kubectl section of our Getting started with LKE guide to install kubectl.

4. Install the Linode CLI using the instructions in our Install and configure the CLI guide.

5. Follow the instructions in our Installing and Using NVM (Node Version Manager) guide to install NVM and the latest Long Term Support (LTS) release of Node.

6. Ensure that you have Knative’s func CLI installed.

7. Ensure that you have Docker installed and have a Docker Hub account.

8. Ensure that you have Git installed.

9. Install jq, a lightweight command line JSON processor:

   sudo apt install jq

10. Install tree, a command line utility that displays directory structures in a tree-like format:

    sudo apt install tree

11. Install npm, a package manager for JavaScript that can install, update, and manage libraries:

    sudo apt install npm

Provision a Kubernetes Cluster

While there are several ways to create a Kubernetes cluster on Linode, this guide uses the Linode CLI to provision resources.

1. Use the Linode CLI command (linode) to see available Kubernetes versions:

   linode lke versions-list

   ┌──────┐
   │ id   │
   ├──────┤
   │ 1.31 │
   ├──────┤
   │ 1.30 │
   ├──────┤
   │ 1.29 │
   └──────┘

   It’s generally recommended to provision the latest version of Kubernetes unless specific requirements dictate otherwise.

2. Use the following command to list available Linode plans, including plan ID, pricing, and performance details. For more detailed pricing information, see Akamai Connected Cloud: Pricing:

   linode linodes types

3. The examples in this guide use the g6-standard-2 Linode, which features two CPU cores and 4 GB of memory. Run the following command to display detailed information in JSON for this Linode plan:

   linode linodes types --label "Linode 4GB" --json --pretty

   [
     {
       "addons": {
         "backups": {
           "price": {
             "hourly": 0.008,
             "monthly": 5.0
           },
           "region_prices": [
             {
               "hourly": 0.009,
               "id": "id-cgk",
               "monthly": 6.0
             },
             {
               "hourly": 0.01,
               "id": "br-gru",
               "monthly": 7.0
             }
           ]
         }
       },
       "class": "standard",
       "disk": 81920,
       "gpus": 0,
       "id": "g6-standard-2",
       "label": "Linode 4GB",
       "memory": 4096,
       "network_out": 4000,
       "price": {
         "hourly": 0.036,
         "monthly": 24.0
       },
       "region_prices": [
         {
           "hourly": 0.043,
           "id": "id-cgk",
           "monthly": 28.8
         },
         {
           "hourly": 0.05,
           "id": "br-gru",
           "monthly": 33.6
         }
       ],
       "successor": null,
       "transfer": 4000,
       "vcpus": 2
     }
   ]

4. View available regions with the regions list command:

   linode regions list

5. With a Kubernetes version and Linode type selected, use the following command to create a cluster named knative-playground in the us-mia (Miami, FL) region with three nodes and auto-scaling. Replace knative-playground and us-mia with a cluster label and region of your choosing, respectively:

   linode lke cluster-create \
     --label knative-playground \
     --k8s_version 1.31 \
     --region us-mia \
     --node_pools '[{
       "type": "g6-standard-2",
       "count": 3,
       "autoscaler": {
         "enabled": true,
         "min": 3,
         "max": 8
       }
     }]'

   Once your cluster is successfully created, you should see output similar to the following:

   Using default values: {}; use the --no-defaults flag to disable defaults
   ┌────────────────────┬────────┬─────────────┐
   │ label              │ region │ k8s_version │
   ├────────────────────┼────────┼─────────────┤
   │ knative-playground │ us-mia │ 1.31        │
   └────────────────────┴────────┴─────────────┘

Access the Kubernetes Cluster

To access your Kubernetes cluster, fetch the cluster credentials in the form of a kubeconfig file.

1. Use the following command to retrieve the cluster’s ID:

   CLUSTER_ID=$(linode lke clusters-list --json | \
       jq -r \
         '.[] | select(.label == "knative-playground") | .id')

2. Create a hidden .kube folder in your user’s home directory:

   mkdir ~/.kube

3. Retrieve the kubeconfig file and save it to ~/.kube/lke-config:

   linode lke kubeconfig-view --json "$CLUSTER_ID" | \
       jq -r '.[0].kubeconfig' | \
       base64 --decode > ~/.kube/lke-config

4. Once you have the kubeconfig file saved, access your cluster by using kubectl and specifying the file:

   kubectl get no --kubeconfig ~/.kube/lke-config

   NAME                            STATUS   ROLES    AGE   VERSION
   lke245800-389937-0a22126f0000   Ready    <none>   18m   v1.31.0
   lke245800-389937-4f8a81a50000   Ready    <none>   18m   v1.31.0
   lke245800-389937-5afba7a80000   Ready    <none>   18m   v1.31.0

   Note

   Optionally, to avoid specifying --kubeconfig ~/.kube/lke-config with every kubectl command, you can set an environment variable for your current terminal window session:

   export KUBECONFIG=~/.kube/lke-config

   Then run:

   kubectl get no

Set Up Knative on LKE

There are multiple ways to install Knative on a Kubernetes cluster. The examples in this guide use the YAML manifests method.

Install Knative

1. Run the following command to install the Knative Custom Resource Definitions (CRDs):

   RELEASE=releases/download/knative-v1.15.2/serving-crds.yaml
   kubectl apply -f "https://github.com/knative/serving/$RELEASE"

   Upon successful execution, you should see a similar output indicating that the CRDs are configured:

   customresourcedefinition.apiextensions.k8s.io/certificates.networking.internal.knative.dev configured
   customresourcedefinition.apiextensions.k8s.io/configurations.serving.knative.dev configured
   customresourcedefinition.apiextensions.k8s.io/clusterdomainclaims.networking.internal.knative.dev configured
   customresourcedefinition.apiextensions.k8s.io/domainmappings.serving.knative.dev configured
   customresourcedefinition.apiextensions.k8s.io/ingresses.networking.internal.knative.dev configured
   customresourcedefinition.apiextensions.k8s.io/metrics.autoscaling.internal.knative.dev configured
   customresourcedefinition.apiextensions.k8s.io/podautoscalers.autoscaling.internal.knative.dev configured
   customresourcedefinition.apiextensions.k8s.io/revisions.serving.knative.dev configured
   customresourcedefinition.apiextensions.k8s.io/routes.serving.knative.dev configured
   customresourcedefinition.apiextensions.k8s.io/serverlessservices.networking.internal.knative.dev configured
   customresourcedefinition.apiextensions.k8s.io/services.serving.knative.dev configured
   customresourcedefinition.apiextensions.k8s.io/images.caching.internal.knative.dev configured

2. Next, install the Knative Serving component:

   RELEASE=releases/download/knative-v1.15.2/serving-core.yaml
   kubectl apply -f "https://github.com/knative/serving/$RELEASE"

   You should see a similar output indicating that various resources are now created:

   namespace/knative-serving created
   role.rbac.authorization.k8s.io/knative-serving-activator created
   clusterrole.rbac.authorization.k8s.io/knative-serving-activator-cluster created
   clusterrole.rbac.authorization.k8s.io/knative-serving-aggregated-addressable-resolver created
   clusterrole.rbac.authorization.k8s.io/knative-serving-addressable-resolver created
   clusterrole.rbac.authorization.k8s.io/knative-serving-namespaced-admin created
   clusterrole.rbac.authorization.k8s.io/knative-serving-namespaced-edit created
   clusterrole.rbac.authorization.k8s.io/knative-serving-namespaced-view created
   clusterrole.rbac.authorization.k8s.io/knative-serving-core created
   clusterrole.rbac.authorization.k8s.io/knative-serving-podspecable-binding created
   serviceaccount/controller created
   clusterrole.rbac.authorization.k8s.io/knative-serving-admin created
   clusterrolebinding.rbac.authorization.k8s.io/knative-serving-controller-admin created
   clusterrolebinding.rbac.authorization.k8s.io/knative-serving-controller-addressable-resolver created
   serviceaccount/activator created
   rolebinding.rbac.authorization.k8s.io/knative-serving-activator created
   clusterrolebinding.rbac.authorization.k8s.io/knative-serving-activator-cluster created
   customresourcedefinition.apiextensions.k8s.io/images.caching.internal.knative.dev unchanged
   certificate.networking.internal.knative.dev/routing-serving-certs created
   customresourcedefinition.apiextensions.k8s.io/certificates.networking.internal.knative.dev unchanged
   customresourcedefinition.apiextensions.k8s.io/configurations.serving.knative.dev unchanged
   customresourcedefinition.apiextensions.k8s.io/clusterdomainclaims.networking.internal.knative.dev unchanged
   customresourcedefinition.apiextensions.k8s.io/domainmappings.serving.knative.dev unchanged
   customresourcedefinition.apiextensions.k8s.io/ingresses.networking.internal.knative.dev unchanged
   customresourcedefinition.apiextensions.k8s.io/metrics.autoscaling.internal.knative.dev unchanged
   customresourcedefinition.apiextensions.k8s.io/podautoscalers.autoscaling.internal.knative.dev unchanged
   customresourcedefinition.apiextensions.k8s.io/revisions.serving.knative.dev unchanged
   customresourcedefinition.apiextensions.k8s.io/routes.serving.knative.dev unchanged
   customresourcedefinition.apiextensions.k8s.io/serverlessservices.networking.internal.knative.dev unchanged
   customresourcedefinition.apiextensions.k8s.io/services.serving.knative.dev unchanged
   image.caching.internal.knative.dev/queue-proxy created
   configmap/config-autoscaler created
   configmap/config-certmanager created
   configmap/config-defaults created
   configmap/config-deployment created
   configmap/config-domain created
   configmap/config-features created
   configmap/config-gc created
   configmap/config-leader-election created
   configmap/config-logging created
   configmap/config-network created
   configmap/config-observability created
   configmap/config-tracing created
   horizontalpodautoscaler.autoscaling/activator created
   poddisruptionbudget.policy/activator-pdb created
   deployment.apps/activator created
   service/activator-service created
   deployment.apps/autoscaler created
   service/autoscaler created
   deployment.apps/controller created
   service/controller created
   horizontalpodautoscaler.autoscaling/webhook created
   poddisruptionbudget.policy/webhook-pdb created
   deployment.apps/webhook created
   service/webhook created
   validatingwebhookconfiguration.admissionregistration.k8s.io/config.webhook.serving.knative.dev created
   mutatingwebhookconfiguration.admissionregistration.k8s.io/webhook.serving.knative.dev created
   validatingwebhookconfiguration.admissionregistration.k8s.io/validation.webhook.serving.knative.dev created
   secret/webhook-certs created

Install Kourier

1. Knative relies on an underlying networking layer. Kourier is designed specifically for Knative, and the examples in this guide use Kourier for Knative networking. Use the commands below to download and install the latest Kourier release:

   RELEASE=releases/download/knative-v1.15.1/kourier.yaml
   kubectl apply -f "https://github.com/knative/net-kourier/$RELEASE"

   The output should again indicate the creation of multiple new elements:

   namespace/kourier-system created
   configmap/kourier-bootstrap created
   configmap/config-kourier created
   serviceaccount/net-kourier created
   clusterrole.rbac.authorization.k8s.io/net-kourier created
   clusterrolebinding.rbac.authorization.k8s.io/net-kourier created
   deployment.apps/net-kourier-controller created
   service/net-kourier-controller created
   deployment.apps/3scale-kourier-gateway created
   service/kourier created
   service/kourier-internal created
   horizontalpodautoscaler.autoscaling/3scale-kourier-gateway created
   poddisruptionbudget.policy/3scale-kourier-gateway-pdb created

2. The following command configures Knative to use Kourier as the default ingress controller:

   kubectl patch configmap/config-network \
       --namespace knative-serving \
       --type merge \
       --patch \
         '{"data":{"ingress-class":"kourier.ingress.networking.knative.dev"}}'

   configmap/config-network patched

   Note

   If Istio is already installed in your cluster, you may choose to reuse it for Knative.

3. With Kourier configured, the Knative serving installation now has a LoadBalancer service for external access. Use the following command to retrieve the external IP address in case you want to set up your own DNS later:

   kubectl get service kourier -n kourier-system

   The output should display the external IP address of the LoadBalancer:

   NAME      TYPE           CLUSTER-IP     EXTERNAL-IP       PORT(S)                      AGE
   kourier   LoadBalancer   10.128.40.59   172.233.168.221   80:32444/TCP,443:32669/TCP   50s

4. Since Kourier adds several deployments, check the updated list to ensure everything functions correctly:

   kubectl get deploy -n knative-serving

   Use the output to confirm availability of the various components:

   NAME                     READY   UP-TO-DATE   AVAILABLE   AGE
   activator                1/1     1            1           2m21s
   autoscaler               1/1     1            1           2m21s
   controller               1/1     1            1           2m20s
   net-kourier-controller   1/1     1            1           68s
   webhook                  1/1     1            1           2m19s

Configure DNS

This guide uses the Magic DNS method to configure DNS, which leverages the sslip.io DNS service. When a request is made to a subdomain of sslip.io containing an embedded IP address, the service resolves that IP address. For example, a request to https://52.0.56.137.sslip.io returns 52.0.56.137 as the IP address.

Use the default-domain job to configure Knative Serving to use sslip.io:

MANIFEST=knative-v1.14.1/serving-default-domain.yaml
kubectl apply -f "https://github.com/knative/serving/releases/download/$MANIFEST"

Upon successful execution, you should see output confirming the creation of the default-domain job and service:

job.batch/default-domain created
service/default-domain-service created

With Knative now operational in your cluster, you can begin working with Knative Functions.

Work with Knative Functions and the func CLI

Knative Functions is a programming model that simplifies writing distributed applications on Kubernetes and Knative. It allows developers to create stateless, event-driven functions without requiring in-depth knowledge of containers, Kubernetes, or Knative itself.

The func CLI provides tools for developers to manage the entire lifecycle of functions (creating, building, deploying, and invoking). This allows for local development and testing of functions without needing a local Kubernetes cluster.

To get started, run the following command:

func

This displays help information for managing Knative function resources:

func is the command line interface for managing Knative Function resources

    Create a new Node.js function in the current directory:
    func create --language node myfunction

    Deploy the function using Docker hub to host the image:
    func deploy --registry docker.io/alice

Learn more about Functions:  https://knative.dev/docs/functions/
Learn more about Knative at: https://knative.dev

Primary Commands:
  create      Create a function
  describe    Describe a function
  deploy      Deploy a function
  delete      Undeploy a function
  list        List deployed functions
  subscribe   Subscribe a function to events

Development Commands:
  run         Run the function locally
  invoke      Invoke a local or remote function
  build       Build a function container

System Commands:
  config      Configure a function
  languages   List available function language runtimes
  templates   List available function source templates
  repository  Manage installed template repositories
  environment Display function execution environment information

Other Commands:
  completion  Output functions shell completion code
  version     Function client version information

Use "func <command> --help" for more information about a given command.

Create a Function

1. Use the following command to create an example TypeScript function (get-emojis-ts) that can be invoked via an HTTP endpoint (the default invocation method):

   func create -l typescript get-emojis-ts

   This command creates a complete directory with multiple files:

   Created typescript function in /home/USERNAME/get-emojis-ts

2. Examine the contents of the newly created ~/get-emojis-ts directory:

   ls -laGh get-emojis-ts

   total 268K
   drwxr-xr-x 5 USERNAME 4.0K Oct 15 18:06 .
   drwxr-x--- 9 USERNAME 4.0K Oct 15 18:06 ..
   -rw-r--r-- 1 USERNAME  458 Oct 15 18:06 .eslintrc
   drwxrwxr-x 2 USERNAME 4.0K Oct 15 18:06 .func
   -rw-r--r-- 1 USERNAME  217 Oct 15 18:06 .funcignore
   -rw-r--r-- 1 USERNAME  171 Oct 15 18:06 func.yaml
   -rw-r--r-- 1 USERNAME  235 Oct 15 18:06 .gitignore
   -rw-r--r-- 1 USERNAME 1.3K Oct 15 18:06 package.json
   -rw-r--r-- 1 USERNAME 210K Oct 15 18:06 package-lock.json
   -rw-r--r-- 1 USERNAME   90 Oct 15 18:06 .prettierrc
   -rw-r--r-- 1 USERNAME 5.1K Oct 15 18:06 README.md
   drwxr-xr-x 2 USERNAME 4.0K Oct 15 18:06 src
   drwxr-xr-x 2 USERNAME 4.0K Oct 15 18:06 test
   -rw-r--r-- 1 USERNAME 1.8K Oct 15 18:06 tsconfig.json

3. While reviewing the purpose of each file is outside the scope of this guide, you should examine the src/index.ts file, the default implementation that Knative generates:

   File: ~/get-emojis-ts/src/index.ts

   1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44

   import { Context, StructuredReturn } from 'faas-js-runtime'; /** * Your HTTP handling function, invoked with each request. This is an example * function that logs the incoming request and echoes its input to the caller. * * It can be invoked with `func invoke` * It can be tested with `npm test` * * It can be invoked with `func invoke` * It can be tested with `npm test` * * @param {Context} context a context object. * @param {object} context.body the request body if any * @param {object} context.query the query string deserialized as an object, if any * @param {object} context.log logging object with methods for 'info', 'warn', 'error', etc. * @param {object} context.headers the HTTP request headers * @param {string} context.method the HTTP request method * @param {string} context.httpVersion the HTTP protocol version * See: https://github.com/knative/func/blob/main/docs/guides/nodejs.md#the-context-object */ const handle = async (context: Context, body: string): Promise<StructuredReturn> => { // YOUR CODE HERE context.log.info(` ----------------------------------------------------------- Headers: ${JSON.stringify(context.headers)} Query: ${JSON.stringify(context.query)} Body: ${JSON.stringify(body)} ----------------------------------------------------------- `); return { body: body, headers: { 'content-type': 'application/json' } }; }; export { handle };

   Note that this function works as a server that returns the body and content-type header from the original request.

Build a Function Image

The next step is to create a container image from your function. Since the function is intended to run on a Kubernetes cluster, it must be containerized. Knative Functions facilitates this process for developers, abstracting the complexities of Docker and Dockerfiles.

1. Navigate into the ~/get-emojis-ts directory:

   cd ~/get-emojis-ts

2. To build your function, run the build command while in the ~/get-emojis-ts directory, specifying Docker Hub (docker.io) as the registry along with your DOCKER_HUB_USERNAME.

   func build --registry docker.io/DOCKER_HUB_USERNAME

   This command fetches a base image and builds a Docker image from your function. You should see output similar to the following as the function image is built:

   Building function image
   Still building
   Still building
   Yes, still building
   Don't give up on me
   Still building
   This is taking a while
   Still building
   Still building
   Yes, still building
   🙌 Function built: index.docker.io/DOCKER_HUB_USERNAME/get-emojis-ts:latest

3. To verify that the image is successfully created, use the following command to list your Docker images:

   docker images | grep -E 'knative|get-emojis-ts|ID'

   REPOSITORY                           TAG       IMAGE ID       CREATED        SIZE
   ghcr.io/knative/builder-jammy-base   0.4.283   204e70721072   44 years ago   1.45GB
   DOCKER_HUB_USERNAME/get-emojis-ts    latest    1585f12d1e54   44 years ago   316MB

   Note

   While the CREATED timestamp may be incorrect, the image is valid.

Run the Function Locally

1. Use the run command to run the function locally:

   func run

   The terminal should display output indicating that the function now runs on localhost at port 8080:

   function up-to-date. Force rebuild with --build
   Running on host port 8080
   {"level":30,"time":1729030761058,"pid":25,"hostname":"8415bd4d2876","node_version":"v20.11.0","msg":"Server listening at http://[::]:8080"}

2. With your function running, open a second terminal session and enter the following command:

   curl "http://localhost:8080?a=1&b=2"

   By default, this initial implementation returns the request body and content-type header:

   {"headers":{"content-type":"application/json"}}

   Meanwhile, the resulting output in the original terminal should be similar to:

   {"level":30,"time":1729720553354,"pid":26,"hostname":"25f720307638","node_version":"v20.11.0","reqId":"req-2","req":{"method":"GET","url":"/","hostname":"localhost:8080","remoteAddress":"::ffff:172.17.0.1","remotePort":52786},"msg":"incoming request"}
   {"level":30,"time":1729720553360,"pid":26,"hostname":"25f720307638","node_version":"v20.11.0","reqId":"req-2","msg":"\n-----------------------------------------------------------\nHeaders:\n{\"host\":\"localhost:8080\",\"user-agent\":\"curl/7.81.0\",\"accept\":\"*/*\"}\n\nQuery:\n{}\n\nBody:\nundefined\n-----------------------------------------------------------\n"}
   {"level":30,"time":1729720553362,"pid":26,"hostname":"25f720307638","node_version":"v20.11.0","reqId":"req-2","res":{"statusCode":200},"responseTime":2.6785800009965897,"msg":"request completed"}

3. When done, close the second terminal and stop the function in the original terminal by pressing the CTRL+C keys.

Deploy the Function

1. Use the deploy command to deploy your function to your Kubernetes cluster as a Knative function and push it to the Docker registry:

   func deploy

   function up-to-date. Force rebuild with --build
   Pushing function image to the registry "index.docker.io" using the "DOCKER_HUB_USERNAME" user credentials
   🎯 Creating Triggers on the cluster
   ✅ Function deployed in namespace "default" and exposed at URL:
      http://get-emojis-ts.default.EXTERNAL_IP_ADDRESS.sslip.io

   Once the function is deployed and the Magic DNS record is established, your Knative function is accessible through this public HTTP endpoint. The new get-emojis-ts repository should also now exist on your Docker Hub account:

2. To invoke your Knative function, open a web browser and visit your function’s URL. An example invocation may look like this:

With your Knative function accessible through a public HTTP endpoint, the next step is to migrate an Azure Function to Knative.

Migrate Azure Functions to Knative

This guide examines a sample Azure function and walks through how to migrate it to Knative. Azure functions are similar to Knative functions - both have a trigger and extract their input arguments from a context, event, or HTTP request.

The main application logic is highlighted in the example Azure function below:

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28

import { app, HttpRequest, HttpResponseInit, InvocationContext } from "@azure/functions"; import { FuzzEmoji } from './fuzz-emoji'; export async function fuzzEmoji(request: HttpRequest, context: InvocationContext): Promise<HttpResponseInit> { context.log(`Http function processed request for url "${request.url}"`); const descriptionsParam = request.query.get('descriptions'); const descriptions = descriptionsParam.split(','); const fuzzer = new FuzzEmoji(); const result = await fuzzer.getEmojis(descriptions); const body = Object.entries(result) .map(([k, v]) => `${k}: (${v})`) .join('\n'); return { body }; }; app.http('fuzzEmoji', { methods: ['GET', 'POST'], authLevel: 'anonymous', handler: fuzzEmoji });

The example function instantiates a FuzzEmoji object and calls its getEmojis() method, passing a list of emoji descriptions. The emoji descriptions may or may not map to official emoji names like “fire” (🔥) or “sunrise” (🌅). The function performs a “fuzzy” search of the descriptions to find matching emojis.

The remainder of the code focuses on extracting emoji descriptions from the query parameters in the request and returning the result, which becomes the body of the response object.

At the time of this writing, this example Azure function was deployed and available at the following HTTP endpoint:

curl https://fuzz-emoji.azurewebsites.net/api/fuzzemoji?descriptions=spectacles,flame

Invoking the function returns the following result:

spectacles: (glasses,👓)
flame: (fire,🔥)

The function successfully returns the “fire” (🔥) emoji for the description “flame” and the “glasses” emoji (👓) for the description “spectacles.”

Isolating the Azure Function Code from Azure Specifics

To migrate the Azure function to Knative, the core application logic must be decoupled from Azure-specific dependencies. In this scenario, this is already done since the interface for the getEmojis() method accepts a TypeScript array of strings as descriptions.

If the getEmojis() method accessed Azure Blob Storage to fetch synonyms, it would not be compatible with Knative and would require some refactoring.

Migrating a Single-File Function to a Knative Function

The core logic of the function is encapsulated into a single TypeScript file called fuzz-emoji.ts, which can be migrated to your Knative function.

1. Using a text editor of your choice, create the fuzz-emoji.ts file in the src sub-directory in the main get-emojis-ts directory:

   nano ~/get-emojis-ts/src/fuzz-emoji.ts

   Give the file the following content:

   File: ~/get-emojis-ts/src/fuzz-emoji.ts

   1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62

   import emojilib from 'emojilib'; import axios from 'axios'; export class FuzzEmoji { private emojiDict: { [key: string]: string } = {}; constructor() { // Check if emojilib is undefined if (!emojilib) { throw new Error('emojilib is not defined or imported correctly'); } // Use emojilib to build the emoji dictionary for (const [emojiChar, keywords] of Object.entries(emojilib)) { if (keywords.length > 0) { // Use only the first keyword const firstKeyword = keywords[0]; this.emojiDict[firstKeyword.toLowerCase()] = emojiChar; } } } private static async getSynonyms(word: string): Promise<string[]> { try { const response = await axios.get(`https://api.datamuse.com/words?rel_syn=${word}`); if (response.status === 200) { return response.data.map((wordData: { word: string }) => wordData.word); } } catch (error) { if (axios.isAxiosError(error) && error.response) { throw new Error(error.response.data || 'Error fetching synonyms'); } throw new Error('Error fetching synonyms'); } return []; } public async getEmoji(description: string): Promise<[string, string]> { description = description.toLowerCase(); // Direct match if (description in this.emojiDict) { return [description, this.emojiDict[description]]; } // Subset match for (const name in this.emojiDict) { if (name.includes(description)) { return [name, this.emojiDict[name]]; } } const synonyms = await FuzzEmoji.getSynonyms(description); // Synonym match for (const syn of synonyms) { if (syn in this.emojiDict) { return [syn, this.emojiDict[syn]]; } } return ['', '']; } }

   When complete, save your changes.

2. Run the tree command on the ~/get-emojis-ts directory to confirm the new folder structure:

   tree ~/get-emojis-ts -L 2 -I 'node_modules'

   The folder structure should now look like this:

   /home/aovera/get-emojis-ts
   ├── func.yaml
   ├── package.json
   ├── package-lock.json
   ├── README.md
   ├── src
   │   ├── fuzz-emoji.ts
   │   └── index.ts
   ├── test
   │   ├── integration.ts
   │   └── unit.ts
   └── tsconfig.json
   
   2 directories, 9 files

3. Edit your index.ts file so that it uses the fuzz-emoji module:

   nano ~/get-emojis-ts/src/index.ts

   Replace the existing content with the following. Remember to save your changes:

   File: ~/get-emojis-ts/src/index.ts

   1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37

   import { Context, StructuredReturn } from 'faas-js-runtime'; import { FuzzEmoji } from './fuzz-emoji'; /** * Your HTTP handling function, invoked with each request. This is an example * function that logs the incoming request and echoes its input to the caller. * * It can be invoked with `func invoke` * It can be tested with `npm test` * * It can be invoked with `func invoke` * It can be tested with `npm test` * * @param {Context} context a context object. * @param {object} context.body the request body if any * @param {object} context.query the query string deserialized as an object, if any * @param {object} context.log logging object with methods for 'info', 'warn', 'error', etc. * @param {object} context.headers the HTTP request headers * @param {string} context.method the HTTP request method * @param {string} context.httpVersion the HTTP protocol version * See: https://github.com/knative/func/blob/main/docs/guides/nodejs.md#the-context-object */ const handle = async (context: Context, _: string): Promise<StructuredReturn> => { _; const descriptions = context.query?.['descriptions']?.split(',') || []; const fuzzer = new FuzzEmoji(); const results = await Promise.all(descriptions.map(desc => fuzzer.getEmoji(desc))); return { body: JSON.stringify(results), headers: { 'content-type': 'application/json' } }; }; export { handle };

   Below is a breakdown of the file code functionality:

   • Imports modules related to the function as a service machinery.
   • Imports the FuzzEmoji class with the core logic from the fuzz-emoji module.
   • The handle() function takes a Context and the body of the request (unused, and marked as _ here) and returns a promise of a StructuredReturn.
   • The context argument contains query parameters with the descriptions.
   • Extract the emoji descriptions from the query parameters. The function expects the descriptions to be a single comma-separated string, which it splits to get a list called descriptions.
   • Instantiates a new FuzzEmoji object.
   • Call the getEmojis() method, passing the list of descriptions that were extracted
   • Converts the result to JSON and returns it with the proper content-type header.

4. Before continuing, use npm to add the dependencies used in fuzz-emoji.ts (emojilib and axios) to your project:

   npm install --save emojilib axios

5. Inspect the package.json file to verify that it now includes these dependencies:

   cat ~/get-emojis-ts/package.json

   Ensure the two highlighted lines are present:

   File: package.json

   1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42

   { "name": "event-handler", "version": "0.1.0", "description": "TypeScript HTTP Handler", "license": "Apache-2.0", "repository": { "type": "git", "url": "" }, "scripts": { "build": "npx -p typescript tsc", "pretest": "npm run lint && npm run build", "test:unit": "ts-node node_modules/tape/bin/tape test/unit.ts", "test:integration": "ts-node node_modules/tape/bin/tape test/integration.ts", "test": "npm run test:unit && npm run test:integration", "start": "FUNC_LOG_LEVEL=info faas-js-runtime ./build/index.js", "lint": "eslint \"src/**/*.{js,ts,tsx}\" \"test/**/*.{js,ts,tsx}\" --quiet", "debug": "nodemon --inspect ./node_modules/faas-js-runtime/bin/cli.js ./build/index.js" }, "devDependencies": { "@types/tape": "^5.6.4", "@typescript-eslint/eslint-plugin": "^7.14.1", "@typescript-eslint/parser": "^7.14.1", "eslint": "^8.56.0", "eslint-config-prettier": "^9.1.0", "eslint-plugin-prettier": "^5.1.3", "nodemon": "^3.1.4", "prettier": "^3.3.2", "supertest": "^7.0.0", "tape": "^5.8.1", "ts-node": "^10.9.2", "tsd": "^0.31.1", "tslint-config-prettier": "^1.18.0", "typescript": "^5.5.2" }, "dependencies": { "@types/node": "^20.14.9", "axios": "^1.7.7", "emojilib": "^4.0.0", "faas-js-runtime": "^2.4.0" } }

6. Re-build and re-deploy the container:

   func build --registry docker.io/DOCKER_HUB_USERNAME
   func deploy

7. To invoke your Knative function, open a web browser and visit to your function’s URL with some descriptions added. For example:

   http://get-emojis-ts.default.EXTERNAL_IP_ADDRESS.sslip.io?descriptions=flame,hound,pol

   The descriptions provided as a query parameter are echoed back, along with a corresponding emoji name and emoji for each description:

This confirms that the Knative function works as expected.

Migrating a Multi-File Function to a Knative Function

In the previous example, the entire application logic was contained in a single file called fuzz-emoji.ts. For larger workloads, your function may involve multiple files or multiple directories and packages.

Migrating such a setup to Knative follows a similar process:

1. Copy all relevant files and directories into the src subfolder of your Knative function folder.

2. Import any required packages in index.ts.

3. Update the package.json file to include all of the dependencies used across any of the packages.

Migrating External Dependencies

When migrating an Azure function, it may depend on various Azure services such as Azure Blob Storage, Azure SQL DB, Azure Cosmos DB, or Azure Service Bus. It’s important to evaluate each dependency to determine the best option to suit your situation.

There are typically three options to consider:

1. Keep it as-is: Continue using the Knative function to interact with the Azure services.
2. Replace the service: For example, you might switch from an Azure service like Azure Cosmos DB to an alternative key-value store in the Kubernetes cluster.
3. Drop the functionality: Eliminate certain functionalities, such as no longer writing messages to Azure Service Bus.

Namespace and Service Account

The Knative function eventually runs as a pod in the Kubernetes cluster. This means it runs in a namespace and has a Kubernetes service account associated with it. These are determined when you run the func deploy command. You can specify them using the -n (or --namespace) and --service-account arguments.

If these options are not specified, the function deploys in the currently configured namespace and uses the default service account of the namespace.

If your Knative function needs to access any Kubernetes resources, it’s recommended to explicitly specify a dedicated namespace and create a dedicated service account. This is the preferred approach since it avoids granting excessive permissions to the default service account.

Configuration and Secrets

If your Azure function uses Azure App Configuration and Azure Key Vault for configuration and sensitive information, these details should not be embedded directly in the function’s image. For example, if your function needs to access Azure services, it would require Azure credentials to authenticate.

Kubernetes offers the ConfigMap and Secret resources for this purpose. The migration process involves the following steps:

1. Identify all the parameters and secrets the Azure function uses.
2. Create corresponding ConfigMap and Secret resources in the namespace for your Knative function.
3. Grant the service account for your Knative function permissions to read the ConfigMap and Secret.

Roles and Permissions

Your Knative function may need to interact with various Kubernetes resources and services during migration, such as data stores, ConfigMaps, and Secrets. To enable this, create a dedicated role with the necessary permissions and bind it to the function’s service account.

If your architecture includes multiple Knative functions, it is considered a best practice to share the same service account, role, and role bindings between all the Knative functions.

Logging, Metrics, and Distributed Tracing

The logging experience in Knative is similar to printing something in your Azure function. With Azure, output is automatically logged to Azure Monitor. In Knative, that same print statement automatically sends log messages to your container’s logs. If you have centralized logging, these messages are automatically recorded in your log system.

LKE provides the native Kubernetes dashboard by default. It runs on the control plane, so it doesn’t take resources from your workloads. You can use the dashboard to explore your entire cluster:

For production systems, consider using a centralized logging system like ELK/EFK, Loki, or Graylog, along with an observability solution consisting of Prometheus and Grafana. You can also supplement your observability by leveraging a telemetry data-oriented solution such as OpenTelemetry. These tools can enhance your ability to monitor, troubleshoot, and optimize application performance while ensuring reliability and scalability.

Knative also has built-in support for distributed tracing, which can be configured globally. This means your Knative function automatically participates in tracing without requiring additional changes.

The Debugging Experience

Knative offers debugging at multiple levels:

• Unit test your core logic
• Unit test your Knative function
• Invoke your function locally

When you create a TypeScript Knative function, Knative generates skeletons for a unit test (unit.ts) and integration test (integration.ts) in the test subfolder.

1. Open the integration.ts file in the get-emojis-ts/test directory:

   nano ~/get-emojis-ts/test/integration.ts

   Replace its content with the integration test code below, and save your changes. This code is updated for testing the fuzzy emoji search functionality:

   File: ~/get-emojis-ts/test/integration.ts

   1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30

   'use strict'; import { start, InvokerOptions } from 'faas-js-runtime'; import request from 'supertest'; import * as func from '../build'; import test, { Test } from 'tape'; const errHandler = (t: Test) => (err: Error) => { t.error(err); t.end(); }; test('Integration: handles a valid request with query parameter', (t) => { const expected = [['fire', '🔥'], ['dog', '🐕']]; start(func.handle, {} as InvokerOptions).then((server) => { t.plan(3); request(server) .post('/') .query({ descriptions: 'fire,dog' }) // Add the query parameter here .expect(200) .expect('Content-Type', /json/) .end((err, result) => { t.error(err, 'No error'); t.ok(result.body, 'Response should be truthy'); t.deepEqual(result.body, expected, 'Response matches the expected structure'); t.end(); server.close(); }); }, errHandler(t)); });

2. Open the unit.ts file in the get-emojis-ts/test directory:

   nano ~/get-emojis-ts/test/unit.ts

   Replace its content with the unit test code below, and save your changes. This code tests the FuzzEmoji class for correct emoji retrieval:

   File: ~/get-emojis-ts/test/unit.ts

   1 2 3 4 5 6 7 8 9 10 11

   import test from 'tape'; import { FuzzEmoji } from '../src/fuzz-emoji'; const fuzzer = new FuzzEmoji(); test('FuzzEmoji: returns correct emoji for exact matches', async (t) => { const [desc1, emoji1] = await fuzzer.getEmoji('fire'); t.equal(desc1, 'fire', 'Description should match "fire"'); t.equal(emoji1, '🔥', 'Emoji should be fire emoji 🔥'); t.end(); });

3. From within the get-emojis-ts directory, use npx to build the TypeScript code:

   npx tsc

4. This should create a build sub-directory containing an index.js file. Use tree to verify that the build sub-directory and index.js file exist:

   tree ~/get-emojis-ts -L 2 -I 'node_modules'

   /home/USERNAME/get-emojis-ts
   ├── build
   │   ├── fuzz-emoji.js
   │   └── index.js
   ├── func.yaml
   ├── package.json
   ├── package-lock.json
   ├── README.md
   ├── src
   │   ├── fuzz-emoji.ts
   │   └── index.ts
   ├── test
   │   ├── integration.ts
   │   └── unit.ts
   └── tsconfig.json
   
   3 directories, 11 files

5. Use ts-node to run the integration test:

   npx ts-node ~/get-emojis-ts/test/integration.ts

   A successful output should look like this:

   TAP version 13
   # Integration: handles a valid request with query parameter
   ok 1 No error
   ok 2 should be truthy
   ok 3 Response mathces the expected structure
   
   1..3
   # tests 3
   # pass  3
   
   # ok

6. Use ts-node to run the unit test:

   npx ts-node ~/get-emojis-ts/test/unit.ts

   A successful output should look like this:

   TAP version 13
   # FuzzEmoji: returns correct emoji for exact matches
   ok 1 Description should match "fire"
   ok 2 Emoji should be fire emoji 🔥
   
   1..2
   # tests 2
   # pass  2
   
   # ok

Once the code behaves as expected, you can test the function locally by packaging it in a Docker container and using func invoke to run it. This approach is handled completely through Docker, without need for a local Kubernetes cluster.

After local testing, you may want to optimize the function’s image size by removing any redundant dependencies to improve resource utilization. Deploy your function to a staging environment (a Kubernetes cluster with Knative installed) using func deploy. In the staging environment, you can conduct integration, regression, and stress testing.

If your function interacts with external services or the Kubernetes API server, you should “mock” these dependencies. Mocking, or simulating external services or components that a function interacts with, allows you to isolate a specific function or piece of code to ensure it behaves correctly.

See More Information below for resources to help you get started with migrating Azure functions to Knative functions on Linode Kubernetes Engine (LKE).

More Information

You may wish to consult the following resources for additional information on this topic. While these are provided in the hope that they will be useful, please note that we cannot vouch for the accuracy or timeliness of externally hosted materials.

• Knative
• Knative Functions
• Knative Functions - Deep Dive (Video)
• Accessing request traces - Knative
• Azure Functions documentation | Microsoft Learn
• Prometheus
• Grafana Labs - Loki, Grafana, Tempo, Mimir
• OpenTelemetry
• Azure Function
• Knative function (TypeScript)