Installing RapidMiner Server (now RapidMiner AI Hub) on AWS
In my first post, I wrote about getting your AWS instance started and ready to go. Now I explain how to connect with a Remote Desktop and finish the installation of RapidMiner Server (now RapidMiner AI Hub).
Once you have created this instance, the first order of business is to connect to it. Since this is in Windows, the connection will be through the Windows Remote Desktop application. Select the instance you want (your table may only have your single instance listed) and press the “Connect” button at the top, which will bring up the following dialog box:
You should download the Remote Desktop file (top button) and also “Get Password” (middle button) as you will need both of these for your connection. To get the Remote Desktop file just hit the top button and your browser will prompt you with where to save the file. To get the password, hit the middle button and it will bring up the next window:
Now you’ll need that key file that you created earlier in the process. You select the file using the “Browse” button in the middle of the page, and then the “Decrypt Password” button under the window. That will reveal your instance name, username, and password, which you will need to save in another text file for use later in the sign on process.
Now you simply run the remote desktop connection executable file that you just downloaded. You’ll first be presented with a screen similar to this one:
It’s an extra security measure and you probably want to check the box about not asking again so you don’t get it every time you start your connection.
Hit the “Connect” button and you’ll get a login authentication screen where you’ll need to enter the password that was generated in the prior step. Once you do that, you should get another security popup that warns you that the certificate is not from a trusted authority. That’s because AWS free certificates are self-issued, which is fine.
Again you probably want to select the “don’t ask me again” option, and press “Yes”. Once you do that, you will be managing your AWS remote server through the Windows Remote Desktop application! Also, don’t be concerned if you have a blank screen for a few minutes, it can take a while for all the services to start the very first time that you log in. Eventually you should see your remote desktop.
Installing RapidMiner AI Hub
Now that you have a remote server running, you will need to take care of a few basic things before you can actually install RapidMiner AI Hub there. The first order of business is to take care of some additional security settings that are managed at the OS level (as opposed to through AWS). Open the Server Manager on the remote machine and you will get a dashboard like this:
Select “Local Server” from the menu on the left, and you will get the next screen:
Now you want to turn off “IE Enhanced Security Configuration” (midway down on the right hand column), or else you won’t be able to navigate to any external web pages from this server.
After that, you should go to the Windows Firewall through the Control Panel. You’ll get the following screen:
You need to click on “Windows Firewall Properties” about halfway down the page. Doing so will bring up the following dialog box:
You can either disable the server firewall entirely (first option) and rely only on the AWS security policy, or you could choose to keep the firewall on but allow all connections. You could also add a custom rule to allow all connections via http (which is how you will communicate with your server from other machines on the internet).
Once you have done all of that, you are ready to start configuring the server for RapidMiner AI Hub. RapidMiner already offers an excellent RapidMiner AI Hub Installation Guide, so I am not going to repeat all of that material here, although I will make a few comments. The complete guide is available here.
First you will need to install Java 8, as the AMI you select doesn’t necessarily come with the latest version of Java. The easiest way to do this is to open a web browser on the remote server and navigate to the Java download page and select the correct version for your server (I recommend using the offline version as well so you don’t have any issues with the internet connection).
Note that you will have to add the JAVA_HOME variable and add the new Java installation to the PATH statement manually, which can be done by going to the Control Panel/System and then selecting “Advanced system settings” from the left hand navigation as shown here, which will bring up the System Properties:
Click the button for “Environment Variables” which brings up the dialog box at the far right, and then click “New” in the lower window. Enter “JAVA_HOME” as the variable name and then the path to the Java installation directory (usually like “C:\Program Files\Java\jre1.8.0_101”) in the variable value. Also find the find the “Path” variable in the lower window. Click the “edit” button and then add the same path to the Java 8 directory to the end of the path statement.
To run RapidMiner AI Hub you will also need to download and install your preferred open-source database program, such as MySQL or PostgreSQL . Configure that database according to the instructions in the RapidMiner AI Hub installation guide (and note that you will need to download the extra jdbc database driver if you are going to use MySQL, which is also explained in the Installation Guide).
Finally, you are ready to download and run the RapidMiner AI Hub installation files according to the steps described in the instructions referenced above. When you are complete, you should be able to log into your RapidMiner AI Hub’s administrative interface from any web browser by entering its public IP address followed by :8080 (e.g., http://184.108.40.206:8080).
Hurray! You now have a fully functional RapidMiner AI Hub instance running on AWS. You can connect it to your RapidMiner Studio installation as a Repository (the instructions for doing so are in the same RapidMiner AI Hub Installation Guide) and start running your processes in the cloud. Happy data mining!