Using VS Code and Enterprise Guide with SAS Analytics Pro

In this post we will look at using Microsoft Visual Studio Code and SAS Enterprise Guide with SAS Analytics Pro.

With SAS Analytics Pro 2025.08 (August) there was an update to support connections from SAS IOM Clients. To be more precise, the feature was first in preview with 2025.07 (in July). IOM stands for Integrated Object Model, the IOM support is normally provided by SAS 9 based software with the SAS Integrated Technologies product offering.

This means that there is an alternative to using SAS Studio. It is now possible to use Visual Studio Code (VS Code) and SAS Enterprise Guide with SAS Analytics Pro.

This is important as the SAS Studio that is shipped with Analytics Pro is not the latest version that is shipped with the SAS Viya platform. It is an older version SAS Studio (SAS Studio 5.2). I’ll leave it to others to detail any functional gaps, but using VS Code will ensure access to current capabilities using a modern IDE.

Let’s take a quick look at the configuration that is required…

In previous posts I have talked about deploying and configuring SAS Analytics Pro. So here I will just focus on the IOM connectivity.

On the Analytics Pro side, the only real change is that you need to publish the IOM port, port 8591. For example, when running Docker you would do the following:

# Get the Analytics Pro image name
APRO_IMAGE=$(docker image ls | grep -m 1 sas-analytics-pro | awk '{ print $1 ":" $2 }')

docker run -u root \
--name=sas-analytics-pro \
--rm \
--detach \
--hostname sas-analytics-pro \
--env RUN_MODE=developer \
--publish 8080:80 \
--publish 8591:8591 \
--volume ${PWD}/sasinside:/sasinside \
--volume ${PWD}/data:/data \
$APRO_IMAGE

The example above, shows starting Analytics Pro in Developer mode. Which uses internal authentication using the sasdemo user. Analytics Pro can be configured for an enterprise deployment and integrated authentication providers (such as Microsoft Entra ID) using a System Security Services Daemon (SSSD) configuration.

For more information see the SAS Analytics Pro Deployment Guide: Connect SAS Enterprise Guide or Visual Studio Code to SAS Analytics Pro

Using the SAS IOM Clients

From the client perspective, the documentation states that the client needs the following installed:

SAS Integration Technologies Client for Windows
SAS Providers for OLE DB

As part of the client prerequisite setup, installing the SAS Providers for OLE DB will automatically install the SAS Integration Technologies Client. No separate installation is required for the Integration Technologies Client.

For SAS Enterprise Guide, Enterprise Guide 8.6 (or higher) is required.

To enable SAS support in Visual Studio Code, the SAS Extension for Visual Studio Code must be installed. This is a separate installation step that must be completed within the Visual Studio Code environment.

Using VS Code

Once the SAS extension is installed in VS Code you need to create the connection profile. For this you need to create a profile using a connection type of ‘SAS 9.4 (remote – IOM)’. For example:

Select any image to see a larger version.
Mobile users: To view the images, select the "Full" version at the bottom of the page.

When prompted for the port, the default port is 8591. For more information see the references later in this post.

Once connected you will see the following:

The ‘SAS SERVER’ section shows the user’s home folder on the Analytics Pro instance that you are connected to. In the ‘LIBRARIES’ section you see the default libraries, including the SASHELP libraries.

Using SAS Enterprise Guide

With SAS Enterprise Guide you follow the standard steps to create a new server connection. Here you need to select ‘SAS Analytics Pro Server’. For example:

Again, you need to specify port 8591 in the connection profile.

Once connected you can start working with SAS Analytics Pro.

Running Analytics Pro on Kubernetes

One of the deployment options with Analytics Pro is to run it on Kubernetes. While it might not be that common, it does have some advantages. For example, you can use a deployment to run multiple instances of Analytics Pro to implement a multi-user platform.

The key part of this deployment is that you need to use a LoadBalancer service (assuming you are running in one of the cloud platforms), or you could use a NodePort service if running on-premises.

As the SAS IOM connection uses a proprietary protocol over a TCP/IP session, using an ingress for access is not an option, the ingress is used for HTTP/HTTPS traffic. Hence, the need for a LoadBalancer or NodePort service.

Here is an example of the service that I used:

---
apiVersion: v1
kind: Service
metadata:
  name: apro-iom-svc
  labels:
    app.kubernetes.io/name: apro-iom-svc
spec:
  type: LoadBalancer
  selector:
    app.kubernetes.io/name: apro
  ports:
  - protocol: TCP
    port: 8591
    targetPort: 8591
  loadBalancerSourceRanges:
  - xxx.xxx.xxx.xxx/xx

It is important to specify the ‘loadBalancerSourceRanges’ as the LoadBalancer service will create a public IP address, and it needs to be secured. The source ranges are expressed in CIDR notation and are used to control (limit) access to a specific set of IP address ranges.

Using a Load Balancer service, it is also possible to open (expose) a different port externally and map that to port 8591. For example, for my testing, due to the firewall rules only ports 80 and 443 are open to Azure. So, in my service the port definition was set to “port: 443” with the targetPort still set to 8591.

This is another advantage of running on Kubernetes and using a Load Balancer service. It provides the option to map non-standard ports to a different port that maps to (complies with) the organization’s security (firewall) rules.

When deploying Analytics Pro, you also need to open port 8591 on the Analytics Pro container. For example, using a Kubernetes deployment the spec template would contain the following:

---
# Create the apro deployment
apiVersion: apps/v1
kind: Deployment
metadata:
  name: sas-analytics-pro
spec:
  selector:
    matchExpressions: []
    matchLabels:
      app: sas-analytics-pro
  replicas: 1
  template:
    metadata:
      labels:
        app: sas-analytics-pro
        app.kubernetes.io/name: apro
    spec:
      securityContext:
         runAsUser: 0
         runAsGroup: 0
         fsGroup: 0
      containers:
      - name: sas-analytics-pro
        image: {{IMAGE}}
        imagePullPolicy: Always
        ports:
        - containerPort: 80
        - containerPort: 443
        - containerPort: 8591
        env:
        - name: ...

Here you can see the container has ports 80, 443 and 8591 published. If you wanted to lock the environment down to just having IOM client access and remove SAS Studio access, you have a couple of options.

The first step is not to define any ingress and service for the SAS Studio access. You could stop there, but you could also remove the related containerPort lines from the deployment definition.

Finally, coming back to my comment that one of the advantages of running on Kubernetes is that you can use a Deployment with multiple replicas. The code example above has the replicas set to “1”. However, you could change that to a value greater than one. This provides scalability for the Analytics Pro environment.

While I haven’t done extensive testing with using multiple replicas, I found this worked for the clients using VS Code, the sessions were spread across the replicas. However, in my environment SAS Studio did not work well. More testing would be required before I would recommend running that configuration for SAS Studio access.

Have fun using VS Code with SAS Analytics Pro…

Other useful material

For more information on using VS Code with Analytics Pro see this post from Shelby Taylor: Visual Studio Code for SAS Analytics Pro Users (Part 1)

Also see this post by Gemma Robson: SAS Analytics Pro: Choose Your Interface

SAS Help Center: SAS Studio 5.2

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