The Stored Processes are deployed using a SAS Program. This should be executed using an account that has WRITE METADATA (WM) permissions to the necessary root folder (`appLoc`) in metadata.
If you don't have internet access from SAS, download [this file](https://git.4gl.io/dc/deploy/-/raw/main/s9_noweb.sas) and change the `compiled_apploc` on line 2:
2. Unzip and place in the [htdocs folder of your SAS Web Server](https://sasjs.io/frontend-deployment/#sas9-deploy) - typically `!SASCONFIG/LevX/Web/WebServer/htdocs`.
You can now open the app at `https://YOURWEBSERVER/unzippedfoldername` and follow the configuration steps (DC Physical Location and Admin Group) to complete deployment.
When opening Data Controller for the first time, a configuration screen is presented. Be sure to log in with an account that has WRITE METADATA (WM) on the following metadata folders:
*`services/admin` - so the configurator STP can be deleted after being run
*`services/common` - so the `Data_Controller_Settings` STP can be updated
*`Data` - so the library and tables can be registered (using proc metalib)
2. Admin Group. ⚠️ Note that anyone in this group will have unrestricted access to Data Controller! ⚠️ "Unrestricted access" is provided by code logic. Post installation, Data Controller will never update nor modify metadata.
If you do not see any groups, then it is possible your Stored Process is running from a different metadata repository to the location of your SAS users (eg Foundation). To fix this, update the `services/admin/configurator` STP with this code: `%let dc_repo_users=YOUUSERRMETAREPO;`
The streaming approach is optimised for rapid deployment, and works by bundling the frontend into metadata. This is a highly inefficient way to serve web content, and thus should only really be used for demos / evaluation purposes.
Deployment is very easy - just run the SAS code below (after changing the `appLoc`):
filename dc url "https://git.4gl.io/dc/deploy/-/raw/main/s9.sas";
%inc dc;
```
If you don't have internet access from your SAS environment, you can also [download the file directly](https://git.4gl.io/dc/deploy/-/raw/main/s9.sas) and modify the `appLoc` on line 2, as follows:
![](img/sas9_apploc.png)
After that, continue to the configuration as described above.
Nothing needs to be deployed or modified on the client device. We support a wide range of browsers (the same as SAS). Browsers make requests to the SAS Web Server, and will cache assets such as JS, CSS and images. Some items (such as dropdowns) are kept in local storage to improve responsiveness.
All deployments of Data Controller also make use of a physical staging directory. This is used to store staged data, logs, plus CSV and Excel files as uploaded by end users. This directory should NOT be accessible by end users - only the SAS system account (eg `sassrv`) requires access to this directory.
A typical small deployment will grow by a 10-20 mb each month. A very large enterprise customer, with 100 or more editors, might generate up to 1 GB or so per month, depending on the size and frequency of the Excel EUCs and CSVs being uploaded. Web modifications are restricted only to modified rows, so are typically just a few kb in size.
All SAS code is embedded in Stored Processes (so there is no need to deploy programs to the file system, no SASAUTOs). There is no use of X commands, no use of external internet access, full LOCKDOWN is supported.
After the installation process (which updates `public/settings` and removes the `admin/makedata` STP), there are no write actions performed against metadata.
We have customers in production using Oracle, Postgres, Netezza, SQL Server to name a few. Contact us for support with DDL and migration steps for your chosen vendor.
Data Controller does NOT modify schemas! It will not create or drop tables, or add/modify columns or attributes. Only data _values_ (not the model) can be modified using this tool.
To caveat the above - it is also quite common for customers to use a BASE engine library. Data Controller ships with mechananisms to handle locking (internally) but it cannot handle external contentions, such as those caused when end users open datasets directly, eg with Enterprise Guide or Base SAS.