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Author: guido-orcl

cuopt/introduction/introduction.md

@@ -4,7 +4,7 @@
 
 In this workshop we will run Nvidia container on oci instance with an A10 shape which has GPU. You will launch an A10 instance with oracle linux and run a set of commands to achieve it.
 
-NVIDIA cuOpt is an optimization tool that specializes in routing. It is run as a microservice in the cloud using the container provided. The cuOpt microservice leverages OpenAPI standards, serving endpoints running on port 5000 (by default) to accept optimization input data and return optimized routing solutions.
+NVIDIA cuOpt is an optimization tool that specializes in routing. It is run as a microservice in the cloud using the container provided. The cuOpt microservice leverages OpenAPI standards, serving endpoints running on port 8000 (by default) to accept optimization input data and return optimized routing solutions.
 
 Estimated Workshop Time: 45 minutes
 
@@ -21,11 +21,10 @@ In this workshop, you will learn how to:
 This lab assumes you have:
 
 * An Oracle Cloud account.
-* Administrator permissions or permissions to use the OCI Compute, Identity Domains, A10 images, NGC API Key.
+* Administrator permissions or permissions to use the OCI Compute, Identity Domains and A10 shapes
 
 ## Learn More
 
-* [What Is NGC API Key?](https://docs.nvidia.com/ai-enterprise/deployment-guide-spark-rapids-accelerator/0.1.0/appendix-ngc.html)
 * [What is NVIDIA cuOpt?](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/cuopt/containers/cuopt)
 
 You may now proceed to the next lab.
@@ -35,4 +34,3 @@ You may now proceed to the next lab.
 **Authors**
 
 * **Guido Alejandro Ferreyra**, Principal Cloud Architect, NACIE
-* **Abhinav Jain**, Senior Cloud Engineer, NACIE

cuopt/provision/images/a10.png

@@ -19,15 +19,15 @@ Provisioning of Nvidia container
 This lab assumes you have:
 
 * An Oracle account
-* Administrator permissions or permissions to use the OCI Compute, Identity Domains, A10 images, NGC API Key.
+* Administrator permissions or permissions to use the OCI Compute, Identity Domains, A10 shapes available.
 
 ## Task 1: Launch an A10 instance
 
 1. Go to Compute -> Instance -> Create Instance. Under Image and Shape choose A10 shape as shown in the image below.
 
     ![A10](images/a10.png)
 
-2. Click on Change Image and select Gen2-GPU-2024 (one on the top) as Image Build under Oracle Linux 8. Shown in the image below.
+2. Click on Change Image and select the latest GPU version (one on the top) as Image Build under Oracle Linux 8. Shown in the image below.
 
     ![GPU](images/gpu.png)
 
@@ -37,53 +37,59 @@ Click **Create**
 
 ![Create_Instance](images/create_instance.png)
 
-## Task 2: Run Nvidia Container
+## Task 2: Install NVIDIA container toolkit
 
 1. In few minutes the status of recently created  instance will change from **Provisioning** to **Running**. 
 
-2. Access the instance using the public ip of the instance with the following command 'ssh -i <ssh_key> opc@public_ip'.
+2. Access the instance using the public ip of the instance with the following command:
 
-3. Install nvidia-container-toolkit
+    ```text
+        <copy>
+        ssh -i <ssh_key> opc@public_ip
+        </copy>
+    ```
+
+5. Install nvidia-container-toolkit
 
     ```text
         <copy>
         curl -s -L https://nvidia.github.io/libnvidia-container/stable/rpm/nvidia-container-toolkit.repo | sudo tee /etc/yum.repos.d/nvidia-container-toolkit.repo
         </copy>
     ```
 
-4. Run the following command
+6. Run the following command
 
     ```text
         <copy>
         sudo yum install -y nvidia-container-toolkit
         </copy>
     ```
 
-5. Generate CDI configuration for podman
+7. Generate CDI configuration for podman
 
     ```text
         <copy>
         sudo nvidia-ctk cdi generate --output=/etc/cdi/nvidia.yaml
         </copy>
     ```
 
-6. Setup nvidia driver to be persistent across reboots
+8. Setup nvidia driver to be persistent across reboots
 
     ```text
         <copy>
         sudo nvidia-persistenced
         </copy>
     ```
 
-7. Run the following command.
+9. Run the following command.
 
     ```text
         <copy>
         sudo systemctl enable nvidia-persistenced
         </copy>
     ```
 
-8. Install podman
+10. Install podman
 
 ```text
     <copy>
@@ -105,92 +111,66 @@ Click **Create**
     </copy>
 ```
 
-## Task 3: Generate NGC API Key
-
-Follow the steps listed in the following link to generate an api key which will be used in next task. [NGC API Key](https://docs.nvidia.com/ai-enterprise/deployment-guide-spark-rapids-accelerator/0.1.0/appendix-ngc.html)
-
-## Task 4: Continue with Steps to run the container
-
-1. Login to nvcr.io. Use the api key generated in previous step.
-
-    ```text
-        <copy>
-        sudo podman login nvcr.io --username '$oauthtoken' --password $api_key
-        </copy>
-    ```
-
-2. Pull cuopt from nvcr.io
-
-    ```text
-        <copy>
-        sudo podman pull nvcr.io/nvidia/cuopt/cuopt:25.08
-        </copy>
-    ```
-
-3. Create systemd service file for cuopt
-
-    ```text
-        <copy>
-        sudo tee /etc/systemd/system/cuopt.service <<EOF
-        [Unit]
-        Description=Podman cuopt Container
-        After=network.target
-        [Service]
-        Type=simple
-        Restart=always
-        ExecStart=/usr/bin/podman run --rm --device nvidia.com/gpu=all -p 5000:5000 nvcr.io/nvidia/cuopt/cuopt:25.08
-        [Install]
-        WantedBy=multi-user.target
-        EOF
-        </copy>
-    ```
+## Task 3: Run NVIDIA cuOpt container
 
-4. Reload systemd and start the service
+1. Run the cuopt image
 
     ```text
         <copy>
-        sudo systemctl daemon-reload
+        sudo podman run --rm --device nvidia.com/gpu=all -p 8000:8000 -e CUOPT_SERVER_PORT=8000 docker.io/nvidia/cuopt:latest-cuda12.8-py3.12
         </copy>
     ```
 
-    ```text
-        <copy>
-        sudo systemctl start cuopt.service
-        </copy>
-    ```
+## Task 4: Test cuOpt with an API call
 
-5. Enable automatic start on boot
+Open a new SSH session with the following command (leave the previous one open so you will be able to see cuOpt logs) :
 
-    ```text
-        <copy>
-        sudo systemctl enable cuopt.service
-        </copy>
-    ```
+```text
+    <copy>
+    ssh -i <ssh_key> opc@public_ip -L 8000:localhost:8000
+    </copy>
+```
 
-## Task 5: Test cuOpt with an API call
+```text
+    <copy>
+    curl --location 'http://localhost:8000/cuopt/request' \
+    --header 'Content-Type: application/json' \
+    --header 'Accept: application/json' \
+    --data '{
+        "cost_matrix_data": { "data": { "0": [[0, 1], [1, 0]] } },
+        "task_data": {
+            "task_locations": [1],
+            "demand": [[1]],
+            "task_time_windows": [[0, 10]],
+            "service_times": [1]
+        },
+        "fleet_data": {
+            "vehicle_locations": [[0, 0]],
+            "capacities": [[2]],
+            "vehicle_time_windows": [[0, 20]]
+        },
+        "solver_config": { "time_limit": 1 }
+    }'
+    </copy>
+```
 
-Run the following command to test the container
+You will receive a reqId. Now run the following command, and you should see that the request has been completed:
 
 ```text
     <copy>
-   curl --location 'http://0.0.0.0:5000/cuopt/routes' \
-   --header 'Content-Type: application/json' \
-   --header "CLIENT-VERSION: custom" \
-   -d '{
-    "cost_matrix_data": {"data": {"0": [[0, 1], [1, 0]]}},
-    "task_data": {"task_locations": [1], "demand": [[1]], "task_time_windows": [[0, 10]], "service_times": [1]},
-    "fleet_data": {"vehicle_locations":[[0, 0]], "capacities": [[2]], "vehicle_time_windows":[[0, 20]] },
-    "solver_config": {"time_limit": 2}
-    }'
+    curl --location 'http://localhost:8000/cuopt/result/YOUR_REQUEST_ID' \
+    --header 'Accept: application/json'
     </copy>
 ```
+## Task 5: Discover the cuOpt documentation
+
+On your local machine, go to http://localhost:8000/cuopt/docs , where you can also run multiple tests.
 
 ## Acknowledgements
 
 **Authors**
 
 * **Guido Alejandro Ferreyra**, Principal Cloud Architect, NACIE
-* **Abhinav Jain**, Senior Cloud Engineer, NACIE
 
 **Last Updated By/Date:**
-* **Abhinav Jain**, Senior Cloud Engineer, NACIE, August 2025
+* **Guido Alejandro Ferreyra**, Principal Cloud Architect, NACIE, December 2015