AnalyticalGraphicsInc · Kyle-Kochel · Sep 18, 2024 · Sep 18, 2024
diff --git a/StkEngineContainerization/linux/stk-parallel-computing-server/README.md b/StkEngineContainerization/linux/stk-parallel-computing-server/README.md
@@ -28,10 +28,10 @@ Note: Since STK Parallel Computing Server consists of multiple containers runnin
     * Copy the `STK_Parallel_Computing_Coordinator${version}.tgz` from the `Linux` folder to the [`coordinator/distributions`](./coordinator/distributions/) folder.
     * Copy the `STK_Parallel_Computing_Agent${version}.tgz` from the `Linux` folder to the [`agent/distributions`](./agent/distributions/) folder.
 3. Build the coordinator image:
-    * If you did not build the `custom-environment` image described in the [Special Configuration](#special-configuration) section, run `docker build -t ansys/stk/stk-parallel-computing-server-coordinator:{version}-ubi-8 coordinator` on the command line in this directory after replacing `{version}` with the version number. i.e `2.8.0`
-    * If you did build the `custom-environment` image described in the [Special Configuration](#special-configuration) section, run `docker build -t ansys/stk/stk-parallel-computing-server-coordinator:{version}-ubi-8 --build-arg baseImage=custom/redhat/ubi8:latest coordinator` on the command line in this directory after replacing `{version}` with the version number. i.e `2.8.0`
-4. Run `docker build -t ansys/stk/stk-parallel-computing-server-python:{version}-ubi-8 python` on the command line in this directory after replacing `{version}` with the version number. i.e `2.8.0`.  This produces an image that includes the STK Parallel Computing Server Python API.  The Agent container extends from this, but it can also be used to execute a client script that submits jobs to the Coordinator service.
-5. Run `docker build -t ansys/stk/stk-parallel-computing-server-agent:{version}-ubi-8 agent` on the command line in this directory after replacing `{version}` with the version number. i.e `2.8.0` to build the agent image.
+    * If you did not build the `custom-environment` image described in the [Special Configuration](#special-configuration) section, run `docker build -t ansys/stk/stk-parallel-computing-server-coordinator:{version}-ubi-8 coordinator` on the command line in this directory after replacing `{version}` with the version number. i.e `2.9.0`
+    * If you did build the `custom-environment` image described in the [Special Configuration](#special-configuration) section, run `docker build -t ansys/stk/stk-parallel-computing-server-coordinator:{version}-ubi-8 --build-arg baseImage=custom/redhat/ubi8:latest coordinator` on the command line in this directory after replacing `{version}` with the version number. i.e `2.9.0`
+4. Run `docker build -t ansys/stk/stk-parallel-computing-server-python:{version}-ubi-8 python` on the command line in this directory after replacing `{version}` with the version number. i.e `2.9.0`.  This produces an image that includes the STK Parallel Computing Server Python API.  The Agent container extends from this, but it can also be used to execute a client script that submits jobs to the Coordinator service.
+5. Run `docker build -t ansys/stk/stk-parallel-computing-server-agent:{version}-ubi-8 agent` on the command line in this directory after replacing `{version}` with the version number. i.e `2.9.0` to build the agent image.
 
 ### Run the Containers
 
@@ -40,18 +40,18 @@ Note: Since STK Parallel Computing Server consists of multiple containers runnin
 The entrypoint of these containers start the Coordinator and Agent servers, with the Coordinator listening on the container's port `9090`. To start the containers:
 
 1. Run `docker network create stk-parallel-computing-server` on the command line in this directory.
-2. Run `docker run -d --rm --name stk-parallel-coordinator --network stk-parallel-computing-server --network-alias coordinator -p 9090:9090 ansys/stk/stk-parallel-computing-server-coordinator:{version}-ubi-8` on the command line in this directory after replacing `{version}` with the version number. i.e `2.8.0`
+2. Run `docker run -d --rm --name stk-parallel-coordinator --network stk-parallel-computing-server --network-alias coordinator -p 9090:9090 ansys/stk/stk-parallel-computing-server-coordinator:{version}-ubi-8` on the command line in this directory after replacing `{version}` with the version number. i.e `2.9.0`
     * If port `9090` is already in use on your machine, map a different port (e.g. `1234:9090`).
 3. Run `docker run -d --rm --name stk-parallel-agent --network stk-parallel-computing-server --network-alias agent --env-file ../configuration/licensing.env -e COORDINATOR=coordinator ansys/stk/stk-parallel-computing-server-agent:{version}-ubi-8`
-on the command line in this directory after replacing `{version}` with the version number. i.e `2.8.0`
+on the command line in this directory after replacing `{version}` with the version number. i.e `2.9.0`
 
 #### Execute Parallel Computing Tasks
 
 This section will show how to execute the [`client_example.py`](./client_example.py) script using a Docker container with Python 3 and the STK Parallel Computing Server Python API installed.
 
 In this example, each task will compute access intervals between a default satellite object and a default place object given the start and stop times of the analysis interval.  Each task's interval is defined as an entry in the `timeIntervals` list.  You can edit this list directly in the script file to add more calculation intervals or modify those already there. The date-times must be in valid ISO-8601 format.
 
-1. Run `docker run --rm -v <ABSOLUTE PATH TO THIS DIRECTORY>/client_example.py:/tmp/client_example.py -e COORDINATOR_HOSTNAME=coordinator -e COORDINATOR_PORT=9090 -w /tmp --network stk-parallel-computing-server ansys/stk/stk-parallel-computing-server-python:{version}-ubi-8 client_example.py` on the command line in this directory after replacing `{version}` with the version number. i.e `2.8.0`
+1. Run `docker run --rm -v <ABSOLUTE PATH TO THIS DIRECTORY>/client_example.py:/tmp/client_example.py -e COORDINATOR_HOSTNAME=coordinator -e COORDINATOR_PORT=9090 -w /tmp --network stk-parallel-computing-server ansys/stk/stk-parallel-computing-server-python:{version}-ubi-8 client_example.py` on the command line in this directory after replacing `{version}` with the version number. i.e `2.9.0`
     * If you changed the host port mapping for the coordinator above, use that port for the value of `COORDINATOR_PORT`
     instead of `9090`.
 

diff --git a/StkEngineContainerization/linux/stk-parallel-computing-server/agent/Dockerfile b/StkEngineContainerization/linux/stk-parallel-computing-server/agent/Dockerfile
@@ -1,4 +1,4 @@
-ARG baseImage=ansys/stk/stk-parallel-computing-server-python:2.8.0-ubi8
+ARG baseImage=ansys/stk/stk-parallel-computing-server-python:2.9.0-ubi8
 FROM ${baseImage} AS builder
 
 # Add the STK Parallel Computing Server Agent packages to the builder stage

diff --git a/StkEngineContainerization/linux/stk-parallel-computing-server/docker-compose.python.yml b/StkEngineContainerization/linux/stk-parallel-computing-server/docker-compose.python.yml
@@ -1,7 +1,7 @@
 version: '3.7'
 services:
     python:
-        image: ansys/stk/stk-parallel-computing-server-python:2.8.0-ubi8
+        image: ansys/stk/stk-parallel-computing-server-python:2.9.0-ubi8
         build:
             context: ./python
             args:

diff --git a/StkEngineContainerization/linux/stk-parallel-computing-server/docker-compose.yml b/StkEngineContainerization/linux/stk-parallel-computing-server/docker-compose.yml
@@ -1,18 +1,18 @@
 version: '3.7'
 services:
     agent:
-        image: ansys/stk/stk-parallel-computing-server-agent:2.8.0-ubi8
+        image: ansys/stk/stk-parallel-computing-server-agent:2.9.0-ubi8
         build:
             context: ./agent
             args:
-                baseImage: ansys/stk/stk-parallel-computing-server-python:2.8.0-ubi8
+                baseImage: ansys/stk/stk-parallel-computing-server-python:2.9.0-ubi8
         env_file: ../configuration/licensing.env
         environment:
             - COORDINATOR=coordinator
         networks:
             - stk-parallel-computing-server
     coordinator:
-        image: ansys/stk/stk-parallel-computing-server-coordinator:2.8.0-ubi8
+        image: ansys/stk/stk-parallel-computing-server-coordinator:2.9.0-ubi8
         build:
             context: ./coordinator
             args:

diff --git a/StkEngineContainerization/windows/stk-parallel-computing-server/README.md b/StkEngineContainerization/windows/stk-parallel-computing-server/README.md
@@ -32,9 +32,9 @@ Note: Since STK Parallel Computing Server consists of multiple containers runnin
     * Copy the `Server\Agent\v{version}` folder from the installation media to the [`agent\distributions`](./agent/distributions/) folder.
     * Copy the `dotnet-runtime*.exe` file from the Prerequirements\DotNet.Core folder to the [`agent\distributions`](./agent/distributions/) AND the [`coordinator\distributions`](./coordinator/distributions/) folders.
 3. Build the coordinator image:
-    Run `docker build --build-arg agreeToLicense=yes -t ansys/stk/stk-parallel-computing-server-coordinator:{version}-windowsservercore-ltsc2019 coordinator` on the command line in this directory after replacing `{version}` with the version number. i.e `2.8.0`. Supplying the agreeToLicense build argument indicates your acceptance of the STK End User License Agreement.
-4. Run `docker build -t ansys/stk/stk-parallel-computing-server-python:{version}-windowsservercore-ltsc2019 python` on the command line in this directory after replacing `{version}` with the version number. i.e `2.8.0`. This produces an image that includes the STK Parallel Computing Server Python API. The Agent container extends from this, but it can also be used to execute a client script that submits jobs to the Coordinator service.
-5. Run `docker build --build-arg agreeToLicense=yes -t ansys/stk/stk-parallel-computing-server-agent:{version}-windowsservercore-ltsc2019 agent` on the command line in this directory to build the agent image after replacing `{version}` with the version number. i.e `2.8.0`. Supplying the agreeToLicense build argument indicates your acceptance of the STK End User License Agreement.
+    Run `docker build --build-arg agreeToLicense=yes -t ansys/stk/stk-parallel-computing-server-coordinator:{version}-windowsservercore-ltsc2019 coordinator` on the command line in this directory after replacing `{version}` with the version number. i.e `2.9.0`. Supplying the agreeToLicense build argument indicates your acceptance of the STK End User License Agreement.
+4. Run `docker build -t ansys/stk/stk-parallel-computing-server-python:{version}-windowsservercore-ltsc2019 python` on the command line in this directory after replacing `{version}` with the version number. i.e `2.9.0`. This produces an image that includes the STK Parallel Computing Server Python API. The Agent container extends from this, but it can also be used to execute a client script that submits jobs to the Coordinator service.
+5. Run `docker build --build-arg agreeToLicense=yes -t ansys/stk/stk-parallel-computing-server-agent:{version}-windowsservercore-ltsc2019 agent` on the command line in this directory to build the agent image after replacing `{version}` with the version number. i.e `2.9.0`. Supplying the agreeToLicense build argument indicates your acceptance of the STK End User License Agreement.
 
 ### Run the Containers
 
@@ -43,17 +43,17 @@ Note: Since STK Parallel Computing Server consists of multiple containers runnin
 The entrypoint of these containers start the Coordinator and Agent servers, with the Coordinator listening on the container's port `9090`. To start the containers:
 
 1. Run `docker network create stk-parallel-computing-server` on the command line in this directory.
-2. Run `docker run -d --rm --name stk-parallel-coordinator --network stk-parallel-computing-server --network-alias coordinator -p 9090:9090 ansys/stk/stk-parallel-computing-server-coordinator:{version}-windowsservercore-ltsc2019` on the command line in this directory after replacing `{version}` with the version number. i.e `2.8.0`
+2. Run `docker run -d --rm --name stk-parallel-coordinator --network stk-parallel-computing-server --network-alias coordinator -p 9090:9090 ansys/stk/stk-parallel-computing-server-coordinator:{version}-windowsservercore-ltsc2019` on the command line in this directory after replacing `{version}` with the version number. i.e `2.9.0`
     * If port `9090` is already in use on your machine, map a different port (e.g. `1234:9090`).
-3. Run `docker run -d --rm --name stk-parallel-agent --network stk-parallel-computing-server --network-alias agent --env-file ..\configuration\licensing.env -e COORDINATOR=coordinator ansys/stk/stk-parallel-computing-server-agent:{version}-windowsservercore-ltsc2019` on the command line in this directory after replacing `{version}` with the version number. i.e `2.8.0`
+3. Run `docker run -d --rm --name stk-parallel-agent --network stk-parallel-computing-server --network-alias agent --env-file ..\configuration\licensing.env -e COORDINATOR=coordinator ansys/stk/stk-parallel-computing-server-agent:{version}-windowsservercore-ltsc2019` on the command line in this directory after replacing `{version}` with the version number. i.e `2.9.0`
 
 #### Execute Parallel Computing Tasks
 
 This section will show how to execute the [`client_example.py`](./client_example.py) script using a Docker container with Python 3 and the STK Parallel Computing Server Python API installed.
 
 In this example, each task will compute access intervals between a default satellite object and a default place object given the start and stop times of the analysis interval. Each task's interval is defined as an entry in the `timeIntervals` list. You can edit this list directly in the script file to add more calculation intervals or modify those already there. The date-times must be in valid ISO-8601 format.
 
-1. Run `docker run --rm -v <ABSOLUTE PATH TO THIS DIRECTORY>\:C:\test\ -e COORDINATOR_HOSTNAME=coordinator -e COORDINATOR_PORT=9090 -w C:\test --network stk-parallel-computing-server ansys/stk/stk-parallel-computing-server-python:{version}-windowsservercore-ltsc2019 client_example.py` on the command line in this directory after replacing `{version}` with the version number. i.e `2.8.0`
+1. Run `docker run --rm -v <ABSOLUTE PATH TO THIS DIRECTORY>\:C:\test\ -e COORDINATOR_HOSTNAME=coordinator -e COORDINATOR_PORT=9090 -w C:\test --network stk-parallel-computing-server ansys/stk/stk-parallel-computing-server-python:{version}-windowsservercore-ltsc2019 client_example.py` on the command line in this directory after replacing `{version}` with the version number. i.e `2.9.0`
     * If you changed the host port mapping for the coordinator above, use that port for the value of `COORDINATOR_PORT` instead of `9090`.
 
 #### Cleanup

diff --git a/StkEngineContainerization/windows/stk-parallel-computing-server/docker-compose.python.yml b/StkEngineContainerization/windows/stk-parallel-computing-server/docker-compose.python.yml
@@ -1,7 +1,7 @@
 version: '3.7'
 services:
     python:
-        image: ansys/stk/stk-parallel-computing-server-python:2.8.0-windowsservercore-ltsc2019
+        image: ansys/stk/stk-parallel-computing-server-python:2.9.0-windowsservercore-ltsc2019
         build:
             context: ./python
             args:

diff --git a/StkEngineContainerization/windows/stk-parallel-computing-server/docker-compose.yml b/StkEngineContainerization/windows/stk-parallel-computing-server/docker-compose.yml
@@ -1,18 +1,18 @@
 version: '3.7'
 services:
     agent:
-        image: ansys/stk/stk-parallel-computing-server-agent:2.8.0-windowsservercore-ltsc2019
+        image: ansys/stk/stk-parallel-computing-server-agent:2.9.0-windowsservercore-ltsc2019
         build:
             context: ./agent
             args:
-                agentBaseImage: ansys/stk/stk-parallel-computing-server-python:2.8.0-windowsservercore-ltsc2019
+                agentBaseImage: ansys/stk/stk-parallel-computing-server-python:2.9.0-windowsservercore-ltsc2019
         env_file: ../configuration/licensing.env
         environment:
             - COORDINATOR=coordinator
         networks:
             - stk-parallel-computing-server
     coordinator:
-        image: ansys/stk/stk-parallel-computing-server-coordinator:2.8.0-windowsservercore-ltsc2019
+        image: ansys/stk/stk-parallel-computing-server-coordinator:2.9.0-windowsservercore-ltsc2019
         build:
             context: ./coordinator
             args: