From ec1e45cf50c7e950dc8b98ea66834b3cd9609b32 Mon Sep 17 00:00:00 2001 From: cliveseldon Date: Mon, 30 Mar 2020 17:32:37 +0100 Subject: [PATCH] remove docs folder --- docs/autoscaling.md | 97 ----------------------------- docs/developer/kubernetes-client.md | 40 ------------ 2 files changed, 137 deletions(-) delete mode 100644 docs/autoscaling.md delete mode 100644 docs/developer/kubernetes-client.md diff --git a/docs/autoscaling.md b/docs/autoscaling.md deleted file mode 100644 index 2c9805706a..0000000000 --- a/docs/autoscaling.md +++ /dev/null @@ -1,97 +0,0 @@ -# Autoscaling Seldon Deployments - -To autoscale your Seldon Deployment resources you can add Horizontal Pod Template Specifications to the Pod Template Specifications you create. There are three steps: - - 1. Ensure you have a resource request for the metric you want to scale on if it is a standard metric such as cpu or memory. - 1. Add a HPA Spec refering to this Deployment. (We presently support v1beta1 version of k8s HPA Metrics spec) - -To illustrate this we have an example Seldon Deployment below: - -```json -{ - "apiVersion": "machinelearning.seldon.io/v1alpha2", - "kind": "SeldonDeployment", - "metadata": { - "name": "seldon-model" - }, - "spec": { - "name": "test-deployment", - "oauth_key": "oauth-key", - "oauth_secret": "oauth-secret", - "predictors": [ - { - "componentSpecs": [{ - "spec": { - "containers": [ - { - "image": "seldonio/mock_classifier:1.0", - "imagePullPolicy": "IfNotPresent", - "name": "classifier", - "resources": { - "requests": { - "cpu": "0.5" - } - } - } - ], - "terminationGracePeriodSeconds": 1 - }, - "hpaSpec": - { - "minReplicas": 1, - "maxReplicas": 4, - "metrics": - [ { - "type": "Resource", - "resource": { - "name": "cpu", - "targetAverageUtilization": 10 - } - }] - } - }], - "graph": { - "children": [], - "name": "classifier", - "endpoint": { - "type" : "REST" - }, - "type": "MODEL" - }, - "name": "example", - "replicas": 1 - } - ] - } -} -``` - -In the above we can see, we added resource requests for the cpu: - -``` -"resources": { - "requests": { - "cpu": "0.5" - } -} -``` - -We added an HPA spec referring to the PodTemplateSpec: - -``` -"hpaSpecs":[ - { - "minReplicas": 1, - "maxReplicas": 4, - "metrics": - [ { - "type": "Resource", - "resource": { - "name": "cpu", - "targetAverageUtilization": 10 - } - }] - }], -``` - -For a worked example see [this notebook](../examples/models/autoscaling/autoscaling_example.ipynb). diff --git a/docs/developer/kubernetes-client.md b/docs/developer/kubernetes-client.md deleted file mode 100644 index 4c8b7208ba..0000000000 --- a/docs/developer/kubernetes-client.md +++ /dev/null @@ -1,40 +0,0 @@ -# Kubernetes Client - -We use the official Java Kubernetes client. To insure for correct use make sure all 3 java projects are updated at same time to new versions in pom.xml, - -``` - - io.kubernetes - client-java - 3.0.0 - compile - -``` - -Also ensure the part of the pom.xml that compiles the proto buffers has `excludes` for any Kubernetes classes that would be found in the Kubernetes Java client: - -``` - - org.xolstice.maven.plugins - protobuf-maven-plugin - 0.5.0 - - com.google.protobuf:protoc:3.1.0:exe:${os.detected.classifier} - grpc-java - io.grpc:protoc-gen-grpc-java:${grpc.version}:exe:${os.detected.classifier} - false - - k8s.io/**/*.proto - **/v1.proto - - - - - - compile - compile-custom - - - - -``` \ No newline at end of file