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This doc explains how to setup a development environment so you can get started
contributing
to kfserving
. Also take a look at:
Follow the instructions below to set up your development environment. Once you meet these requirements, you can make changes and deploy your own version of kfserving!
Before submitting a PR, see also CONTRIBUTING.md.
You must install these tools:
go
: KFServing controller is written in Go and requires Go 1.13.0+.git
: For source control.Go Module
: Go's new dependency management system.ko
: For development.kubectl
: For managing development environments.kustomize
To customize YAMLs for different environments, requires v3.5.4+.yq
yq is used in the project makefiles to parse and display YAML output
KFServing currently requires Knative Serving
for auto-scaling, canary rollout, Istio
for traffic routing and ingress.
-
To install Knative components on your Kubernetes cluster, follow the generic cluster installation guide or alternatively, use the Knative Operators to manage your installation. Observability, tracing and logging are optional but are often very valuable tools for troubleshooting difficult issues - they can be installed via the directions here.
-
If you already have
Istio
orKnative
(e.g. from a Kubeflow install) then you don't need to install them explictly, as long as version dependencies are satisfied. With Kubeflow v0.7, KNative 0.8 and Istio 1.1.6 are installed by default as part of the Kubeflow installation. From Kubeflow 1.0 onwards, KNative 0.11.1 and Istio 1.1.6 are installed by default. If you are using DEX based config for Kubeflow 1.0, Istio 1.3.1 is installed by default in your Kubeflow cluster. To summarize, we would recommend KNative 0.11.1 at a minimum for KFServing 0.3.0 and for the KFServing code in master. For Istio use versions 1.1.6 and 1.3.1 which have been tested, and for Kubernetes use 1.15+ -
You need follow the instructions on Updating your install to use cluster local gateway to add cluster local gateway to your cluster to serve cluster-internal traffic for transformer and explainer use cases.
To start your environment you'll need to set these environment variables (we
recommend adding them to your .bashrc
):
GOPATH
: If you don't have one, simply pick a directory and addexport GOPATH=...
$GOPATH/bin
onPATH
: This is so that tooling installed viago get
will work properly.KO_DOCKER_REPO
: The docker repository to which developer images should be pushed (e.g.docker.io/<username>/[project]
).
- Note: Set up a docker repository for pushing images. You can use any container image registry by adjusting the authentication methods and repository paths mentioned in the sections below.
- Note: if you are using docker hub to store your images your
KO_DOCKER_REPO
variable should bedocker.io/<username>
. - Note: Currently Docker Hub doesn't let you create subdirs under your username.
.bashrc
example:
export GOPATH="$HOME/go"
export PATH="${PATH}:${GOPATH}/bin"
export KO_DOCKER_REPO='docker.io/<username>'
The Go tools require that you clone the repository to the
src/github.com/kubeflow/kfserving
directory in your
GOPATH
.
To check out this repository:
- Create your own fork of this repo
- Clone it to your machine:
mkdir -p ${GOPATH}/src/github.com/kubeflow
cd ${GOPATH}/src/github.com/kubeflow
git clone git@github.com:${YOUR_GITHUB_USERNAME}/kfserving.git
cd kfserving
git remote add upstream git@github.com:kubeflow/kfserving.git
git remote set-url --push upstream no_push
Adding the upstream
remote sets you up nicely for regularly
syncing your fork.
Once you reach this point you are ready to do a full build and deploy as described below.
Once you've setup your development environment, you can see things running with:
$ kubectl -n knative-serving get pods
NAME READY STATUS RESTARTS AGE
activator-c8495dc9-z7xpz 2/2 Running 0 6d
autoscaler-66897845df-t5cwg 2/2 Running 0 6d
controller-699fb46bb5-xhlkg 1/1 Running 0 6d
webhook-76b87b8459-tzj6r 1/1 Running 0 6d
We suggest using cert manager for provisioning the certificates for the KFServing webhook server. Other solutions should also work as long as they put the certificates in the desired location.
You can follow the cert manager documentation to install it.
If you don't want to install cert manager, you can set the KFSERVING_ENABLE_SELF_SIGNED_CA
environment variable to true.
KFSERVING_ENABLE_SELF_SIGNED_CA
will execute a script to create a self-signed CA and patch it to the webhook config.
export KFSERVING_ENABLE_SELF_SIGNED_CA=true
After that you can run following command to deploy KFServing
, you can skip above step once cert manager is installed.
make deploy
Optional: you can set CPU and memory limits when deploying KFServing
.
make deploy KFSERVING_CONTROLLER_CPU_LIMIT=<cpu_limit> KFSERVING_CONTROLLER_MEMORY_LIMIT=<memory_limit>
or
export KFSERVING_CONTROLLER_CPU_LIMIT=<cpu_limit>
export KFSERVING_CONTROLLER_MEMORY_LIMIT=<memory_limit>
make deploy
After above step you can see things running with:
$ kubectl get pods -n kfserving-system -l control-plane=kfserving-controller-manager
NAME READY STATUS RESTARTS AGE
kfserving-controller-manager-0 2/2 Running 0 13m
- Note: By default it installs to
kfserving-system
namespace with the publishedkfserving-controller-manager
image.
make deploy-dev
- Note:
deploy-dev
builds the image from your local code, publishes toKO_DOCKER_REPO
and deploys thekfserving-controller-manager
andlogger
with the image digest to your cluster for testing. Please also ensure you are logged in toKO_DOCKER_REPO
from your client machine.
There's also commands to build and deploy the image from your local code for the models, explainer and storage-initializer, you can choose to use one of below commands for your development purpose.
make deploy-dev-sklearn
make deploy-dev-xgb
make deploy-dev-pytorch
make deploy-dev-alibi
make deploy-dev-storageInitializer
- Note: These commands also publishes to
KO_DOCKER_REPO
with the image of version 'latest', and change the configmap of your cluster to point to the new built images. It's just for development and testing purpose so you need to do it one by one. In configmap, for predictors it will just keep the one in development, for exlainer and storage initializer will just change the item impacted and set all others images including thekfserving-controller-manager
andlogger
to be default.
kubectl apply -f docs/samples/tensorflow/tensorflow.yaml
You should see model serving deployment running under default or your specified namespace.
$ kubectl get inferenceservices -n default
NAME READY URL DEFAULT TRAFFIC CANARY TRAFFIC AGE
flowers-sample True flowers-sample.default.example.com 100 1h
$ kubectl get pods -n default -l serving.kubeflow.org/inferenceservice=flowers-sample
NAME READY STATUS RESTARTS AGE
flowers-sample-default-htz8r-deployment-8fd979f9b-w2qbv 3/3 Running 0 10s
NOTE: KFServing scales pods to 0 in the absence of traffic. If you don't see any pods, try sending out a query via curl using instructions in the tensorflow sample: https://github.com/kubeflow/kfserving/tree/master/docs/samples/tensorflow
As you make changes to the code-base, there are two special cases to be aware of:
-
If you change an input to generated code, then you must run
make manifests
. Inputs include:- API type definitions in pkg/apis/serving/v1alpha2/,
- Manifests or kustomize patches stored in config.
-
If you want to add new dependencies, then you add the imports and the specific version of the dependency module in
go.mod
. When it encounters an import of a package not provided by any module ingo.mod
, the go command automatically looks up the module containing the package and adds it togo.mod
using the latest version. -
If you want to upgrade the dependency, then you run go get command e.g
go get golang.org/x/text
to upgrade to the latest version,go get golang.org/x/text@v0.3.0
to upgrade to a specific version.
make deploy-dev
- If you are on kubernetes 1.15+, we highly recommend adding object selector on kfserving pod mutating webhook configuration so that only pods managed by kfserving go through the kfserving pod mutator
kubectl patch mutatingwebhookconfiguration inferenceservice.serving.kubeflow.org --patch '{"webhooks":[{"name": "inferenceservice.kfserving-webhook-server.pod-mutator","objectSelector":{"matchExpressions":[{"key":"serving.kubeflow.org/inferenceservice", "operator": "Exists"}]}}]}'
- You may get one of the following errors after deploying KFServing
Reissued from statefulset/default: create Pod default-0 in StatefulSet default failed error: Internal error occurred: failed calling webhook "inferenceservice.kfserving-webhook-server.pod.mutator": Post https://kfserving-webhook-server-service.kubeflow.svc:443/mutate-pods?timeout=30s: service "kfserving-webhook-service" not found
Or while you are deploying the models
kubectl apply -f docs/samples/tensorflow/tensorflow.yaml
Error from server (InternalError): error when creating "docs/samples/tensorflow/tensorflow.yaml":
Internal error occurred: failed calling webhook "inferenceservice.kfserving-webhook-server.defaulter":
Post https://kfserving-webhook-server-service.kfserving-system.svc:443/mutate-inferenceservices?timeout=30s:
context deadline exceeded
unexpected EOF
dial tcp x.x.x.x:443: connect: connection refused
If above errors appear, first thing to check is if the KFServing controller is running
kubectl get po -n kfserving-system
NAME READY STATUS RESTARTS AGE
kfserving-controller-manager-0 2/2 Running 2 13m
If it is, more often than not, it is caused by a stale webhook, since webhooks are immutable. Even if the KFServing controller is not running, you might have stale webhooks from last deployment causing other issues. Best is to delete them, and test again
kubectl delete mutatingwebhookconfigurations inferenceservice.serving.kubeflow.org && kubectl delete validatingwebhookconfigurations inferenceservice.serving.kubeflow.org && kubectl delete po kfserving-controller-manager-0 -n kfserving-system
mutatingwebhookconfiguration.admissionregistration.k8s.io "inferenceservice.serving.kubeflow.org" deleted
validatingwebhookconfiguration.admissionregistration.k8s.io "inferenceservice.serving.kubeflow.org" deleted
- When you run make deploy, you may encounter an error like this:
error: error validating "STDIN": error validating data: ValidationError(CustomResourceDefinition.spec.validation.openAPIV3Schema.properties.status.properties.conditions.properties.conditions.items): invalid type for io.k8s.apiextensions-apiserver.pkg.apis.apiextensions.v1beta1.JSONSchemaPropsOrArray: got "map", expected ""; if you choose to ignore these errors, turn validation off with --validate=false
make: *** [deploy] Error 1
To fix it, please ensure you have a matching version of kubectl client as the master. If not, please update accordingly.
kubectl version
Client Version: version.Info{Major:"1", Minor:"13", GitVersion:"v1.13.6", GitCommit:"abdda3f9fefa29172298a2e42f5102e777a8ec25", GitTreeState:"clean", BuildDate:"2019-05-08T13:53:53Z", GoVersion:"go1.11.5", Compiler:"gc", Platform:"darwin/amd64"}
Server Version: version.Info{Major:"1", Minor:"13", GitVersion:"v1.13.6+IKS", GitCommit:"ac5f7341d5d0ce8ea8f206ba5b030dc9e9d4cc97", GitTreeState:"clean", BuildDate:"2019-05-09T13:26:51Z", GoVersion:"go1.11.5", Compiler:"gc", Platform:"linux/amd64"}
- When you run make deploy-dev, you may see an error like the one below:
2019/05/17 15:13:54 error processing import paths in "config/default/manager/manager.yaml": unsupported status code 401; body:
kustomize build config/overlays/development | kubectl apply -f -
Error: reading strategic merge patches [manager_image_patch.yaml]: evalsymlink failure on '/Users/animeshsingh/go/src/github.com/kubeflow/kfserving/config/overlays/development/manager_image_patch.yaml' : lstat /Users/animeshsingh/go/src/github.com/kubeflow/kfserving/config/overlays/development/manager_image_patch.yaml: no such file or directory
It`s a red herring. To resolve it, please ensure you have logged into dockerhub from you client machine.
- When you deploy the tensorflow sample, you may encounter an error like the one blow:
2019-09-28 01:52:23.345692: E tensorflow_serving/sources/storage_path/file_system_storage_path_source.cc:362] FileSystemStoragePathSource encountered a filesystem access error: Could not find base path /mnt/models for servable flowers-sample
Please make sure not to deploy the inferenceservice in the kfserving-system
or other namespaces where namespace has control-plane
as a label. The storage-initializer
init container does not get injected for deployments in those namespaces since they do not go through the mutating webhook.
- Older version of controller-tools does not allow generators to run successfully:
% make deploy
/Users/theofpa/go/bin/controller-gen "crd:maxDescLen=0" paths=./pkg/apis/serving/... output:crd:dir=config/crd
/usr/local/Cellar/go/1.15.2/libexec/src/net/url/url.go:359:2: encountered struct field "Scheme" without JSON tag in type "URL"
/usr/local/Cellar/go/1.15.2/libexec/src/net/url/url.go:360:2: encountered struct field "Opaque" without JSON tag in type "URL"
/usr/local/Cellar/go/1.15.2/libexec/src/net/url/url.go:361:2: encountered struct field "User" without JSON tag in type "URL"
/usr/local/Cellar/go/1.15.2/libexec/src/net/url/url.go:362:2: encountered struct field "Host" without JSON tag in type "URL"
/usr/local/Cellar/go/1.15.2/libexec/src/net/url/url.go:363:2: encountered struct field "Path" without JSON tag in type "URL"
/usr/local/Cellar/go/1.15.2/libexec/src/net/url/url.go:364:2: encountered struct field "RawPath" without JSON tag in type "URL"
/usr/local/Cellar/go/1.15.2/libexec/src/net/url/url.go:365:2: encountered struct field "ForceQuery" without JSON tag in type "URL"
/usr/local/Cellar/go/1.15.2/libexec/src/net/url/url.go:366:2: encountered struct field "RawQuery" without JSON tag in type "URL"
/usr/local/Cellar/go/1.15.2/libexec/src/net/url/url.go:367:2: encountered struct field "Fragment" without JSON tag in type "URL"
/usr/local/Cellar/go/1.15.2/libexec/src/net/url/url.go:368:2: encountered struct field "RawFragment" without JSON tag in type "URL"
/Users/theofpa/go/pkg/mod/knative.dev/pkg@v0.0.0-20191217184203-cf220a867b3d/apis/volatile_time.go:26:2: encountered struct field "Inner" without JSON tag in type "VolatileTime"
Error: not all generators ran successfully
run `controller-gen crd:maxDescLen=0 paths=./pkg/apis/serving/... output:crd:dir=config/crd -w` to see all available markers, or `controller-gen crd:maxDescLen=0 paths=./pkg/apis/serving/... output:crd:dir=config/crd -h` for usage
make: *** [manifests] Error 1
% controller-gen --version
Version: v0.3.0
Deleting $GOPATH/bin/controller-gen helps to resolve this issue, as Makefile will fetch the correct version.