[Docs] Bump docs docker tag to 1.0.4 (#2046)

dockerfiles/README.md

@@ -32,13 +32,13 @@ Where:<br>
 * `MLRUN_DOCKER_REGISTRY` is the docker registry (e.g. `quay.io/`, `gcr.io/`, defaults to empty (docker hub))
 
 
-For example, running `MLRUN_VERSION=1.0.3 make docker-images` will generate the following images:
-  * `mlrun/mlrun-api:1.0.3`
-  * `mlrun/mlrun:1.0.3`
-  * `mlrun/jupyter:1.0.3`
-  * `mlrun/ml-base:1.0.3`
-  * `mlrun/ml-models:1.0.3`
-  * `mlrun/ml-models-gpu:1.0.3` 
+For example, running `MLRUN_VERSION=1.0.4 make docker-images` will generate the following images:
+  * `mlrun/mlrun-api:1.0.4`
+  * `mlrun/mlrun:1.0.4`
+  * `mlrun/jupyter:1.0.4`
+  * `mlrun/ml-base:1.0.4`
+  * `mlrun/ml-models:1.0.4`
+  * `mlrun/ml-models-gpu:1.0.4` 
 
 It's also possible to build only a specific image - `make api` (will build only the api image)<br>
 Or a set of images - `make mlrun jupyter base`

docs/cli.md

@@ -242,7 +242,7 @@ spec:
   image: .mlrun/func-default-remote-demo-ps-latest
   image_pull_policy: Always
   build:
-    base_image: mlrun/mlrun:1.0.3
+    base_image: mlrun/mlrun:1.0.4
     source: git://github.com/mlrun/mlrun
 ```
 
@@ -272,7 +272,7 @@ spec:
   image_pull_policy: Always
   build:
     commands: []
-    base_image: mlrun/mlrun:1.0.3
+    base_image: mlrun/mlrun:1.0.4
     source: git://github.com/mlrun/ci-demo.git
 ```
 
@@ -300,7 +300,7 @@ spec:
   image_pull_policy: Always
   build:
     commands: []
-    base_image: mlrun/mlrun:1.0.3
+    base_image: mlrun/mlrun:1.0.4
 ```
 
 Next, run the following MLRun CLI command to build the function; replace the `<...>` placeholders to match your configuration:

docs/install/compose.with-jupyter.yaml

@@ -1,6 +1,6 @@
 services:
   jupyter:
-    image: "mlrun/jupyter:${TAG:-1.0.3}"
+    image: "mlrun/jupyter:${TAG:-1.0.4}"
     ports:
       - "8080:8080"
       - "8888:8888"
@@ -16,7 +16,7 @@ services:
       - mlrun
 
   mlrun-ui:
-    image: "mlrun/mlrun-ui:${TAG:-1.0.3}"
+    image: "mlrun/mlrun-ui:${TAG:-1.0.4}"
     ports:
       - "8060:80"
     environment:

docs/install/compose.yaml

@@ -1,6 +1,6 @@
 services:
   mlrun-api:
-    image: "mlrun/mlrun-api:${TAG:-1.0.3}"
+    image: "mlrun/mlrun-api:${TAG:-1.0.4}"
     ports:
       - "8080:8080"
     environment:
@@ -17,7 +17,7 @@ services:
       - mlrun
 
   mlrun-ui:
-    image: "mlrun/mlrun-ui:${TAG:-1.0.3}"
+    image: "mlrun/mlrun-ui:${TAG:-1.0.4}"
     ports:
       - "8060:80"
     environment:

docs/runtimes/images.md

@@ -18,12 +18,12 @@ See [README](https://github.com/mlrun/mlrun/blob/development/dockerfiles/README.
 ## MLRun images and external docker images
 
 There is no difference in the usage between the MLRun images and external docker images. However:
-- MLRun images resolve auto tags: If you specify ```image="mlrun/mlrun"``` the API fills in the tag by the client version, e.g. changes it to `mlrun/mlrun:1.0.3`. So, if the client gets upgraded you'll automatically get a new image tag. 
-- Where the data node registry exists, MLRun: Appends the registry prefix, so the image loads from the datanode registry. This pulls the image more quickly, and also supports air-gapped sites. When you specify an MLRun image, for example `mlrun/mlrun:1.0.3`, the actual image used is similar to `datanode-registry.iguazio-platform.app.vm/mlrun/mlrun:1.0.3`.
+- MLRun images resolve auto tags: If you specify ```image="mlrun/mlrun"``` the API fills in the tag by the client version, e.g. changes it to `mlrun/mlrun:1.0.4`. So, if the client gets upgraded you'll automatically get a new image tag. 
+- Where the data node registry exists, MLRun: Appends the registry prefix, so the image loads from the datanode registry. This pulls the image more quickly, and also supports air-gapped sites. When you specify an MLRun image, for example `mlrun/mlrun:1.0.4`, the actual image used is similar to `datanode-registry.iguazio-platform.app.vm/mlrun/mlrun:1.0.4`.
 
 These characteristics are great when you’re working in a POC or development environment. But MLRun typically upgrades packages as part of the image, and therefore the default MLRun images can break your product flow. 
 
 ### Working with images in production
 For production you should create your own images to ensure that the image is fixed.
-- Pin the image tag, e.g. `image="mlrun/mlrun:1.0.3"`. This maintains the image tag at 1.0.3 even when the client is upgraded. Otherwise, an upgrade of the client would also upgrade the image. (If you specify an external (not MLRun images) docker image, like python, the result is the docker/k8s default behavior, which defaults to `latest` when the tag is not provided.)
+- Pin the image tag, e.g. `image="mlrun/mlrun:1.0.4"`. This maintains the image tag at 1.0.3 even when the client is upgraded. Otherwise, an upgrade of the client would also upgrade the image. (If you specify an external (not MLRun images) docker image, like python, the result is the docker/k8s default behavior, which defaults to `latest` when the tag is not provided.)
 - Pin the versions of requirements, again to avoid breakages, e.g. `pandas==1.4.0`. (If you only specify the package name, e.g. pandas, then pip/conda (python's package managers) just pick up the latest version.)

hack/local/README.md

@@ -28,12 +28,12 @@ To use MLRun with your local Docker registry, run the MLRun API service, dashboa
 ```
 SHARED_DIR=~/mlrun-data
 
-docker pull mlrun/jupyter:1.0.3
-docker pull mlrun/mlrun-ui:1.0.3
+docker pull mlrun/jupyter:1.0.4
+docker pull mlrun/mlrun-ui:1.0.4
 
 docker network create mlrun-network
-docker run -it -p 8080:8080 -p 8888:8888 --rm -d --network mlrun-network --name jupyter -v ${SHARED_DIR}:/home/jovyan/data mlrun/jupyter:1.0.3
-docker run -it -p 4000:80 --rm -d --network mlrun-network --name mlrun-ui -e MLRUN_API_PROXY_URL=http://jupyter:8080 mlrun/mlrun-ui:1.0.3
+docker run -it -p 8080:8080 -p 8888:8888 --rm -d --network mlrun-network --name jupyter -v ${SHARED_DIR}:/home/jovyan/data mlrun/jupyter:1.0.4
+docker run -it -p 4000:80 --rm -d --network mlrun-network --name mlrun-ui -e MLRUN_API_PROXY_URL=http://jupyter:8080 mlrun/mlrun-ui:1.0.4
 ```
 
 When the execution completes —

hack/local/mljupy.yaml

@@ -63,7 +63,7 @@ spec:
     spec:
       containers:
       - name: jupyter-notebook
-        image: mlrun/jupyter:1.0.3
+        image: mlrun/jupyter:1.0.4
         env:
         - name: MLRUN_NAMESPACE
           valueFrom:

hack/local/mlrun-local.yaml

@@ -17,7 +17,7 @@ spec:
     spec:
       containers:
       - name: mlrun-api
-        image: mlrun/mlrun-api:1.0.3
+        image: mlrun/mlrun-api:1.0.4
         env:
         - name: MLRUN_NAMESPACE
           valueFrom:
@@ -72,7 +72,7 @@ spec:
     spec:
       containers:
       - name: mlrun-ui
-        image: mlrun/mlrun-ui:1.0.3
+        image: mlrun/mlrun-ui:1.0.4
         env:
         - name: MLRUN_API_PROXY_URL
           value: http://mlrun-api:8080

hack/mlrun-all.yaml

@@ -17,7 +17,7 @@ spec:
     spec:
       containers:
       - name: mlrun-api
-        image: mlrun/mlrun-api:1.0.3
+        image: mlrun/mlrun-api:1.0.4
         env:
         - name: MLRUN_NAMESPACE
           valueFrom:
@@ -77,7 +77,7 @@ spec:
     spec:
       containers:
       - name: mlrun-ui
-        image: mlrun/mlrun-ui:1.0.3
+        image: mlrun/mlrun-ui:1.0.4
         env:
         - name: MLRUN_API_PROXY_URL
           value: http://mlrun-api:8080

hack/mlrunapi.yaml

@@ -17,7 +17,7 @@ spec:
     spec:
       containers:
       - name: mlrun-api
-        image: mlrun/mlrun-api:1.0.3
+        image: mlrun/mlrun-api:1.0.4
         env:
         - name: MLRUN_HTTPDB__BUILDER__DOCKER_REGISTRY
           value: "default registry url e.g. index.docker.io/<username>, if repository is not set it will default to mlrun"

hack/mlrunui.yaml

@@ -16,7 +16,7 @@ spec:
     spec:
       containers:
       - name: mlrun-ui
-        image: mlrun/mlrun-ui:1.0.3
+        image: mlrun/mlrun-ui:1.0.4
         env:
         - name: MLRUN_API_PROXY_URL
           value: http://mlrun-api:8080