Last Updated on 2nd September 2023 by peppe8o
In this tutorial I’m going to show you how to setup and use hercules, which bring a lite version of MVS (Mainframe) on Raspberry PI.
Mainframes mainly belong to a remote computer era, when window on PC where quite not used on companies main servers. Anyway, they are still installed and running in many server farms and run a number of services we use everyday (like, for example, banking back-end). Hercules brings a lite (and old) version of MVS emulation to get Mainframe on Raspberry PI
Wikipedia Mainframe Computer page defines Mainframe as following:
Mainframe computers or mainframes (colloquially referred to as “big iron”) are computers used primarily by large organizations for critical applications; bulk data processing, such as census, industry and consumer statistics, enterprise resource planning; and transaction processing. They are larger and have more processing power than some other classes of computers: minicomputers, servers, workstations, and personal computers.
Mainframes are focused on some key factors, vital for critical businesses:
- high availability
- high I/O volumes
- reliability for transaction processing
Even if they are currently considered as an outdated technology (compared to modern virtual machines / container technology), they are still deep-rooted in modern datacenters, expecially for banks, stock exchange, etc
In this article I’m going to show you how to run a Mainframe MVS (Multiple Virtual Storage) inside … a Raspberry PI!
What We Need
As usual, I suggest adding from now to your favourite e-commerce shopping cart all the needed hardware, so that at the end you will be able to evaluate overall costs and decide if continue with the project or remove them from the shopping cart. So, hardware will be only:
- Raspberry PI (including proper power supply or using a smartphone micro usb charger with at least 3A)
- high speed micro SD card (at least 16 GB, at least class 10)
Check hardware prices with following links:
This guide will use an amazing MVS package available from wotho.ethz.ch, which includes also a User Manual explaining how to use this MVS emulation.
Start setting up the operating system. You can install Raspberry PI OS Lite (for a headless, fast OS) or install Raspberry PI OS Desktop (in this case, using its internal terminal). This tutorial uses the Lite distribution with a remote ssh connection.
Also note that you have to install the 32-bit OS version, in order to get the MVS emulator running.
Install TK4 MVS Emulation
We’ll download and unzip tk4 package inside a new folder from where our system will load. From Raspberry PI type the following commands:
mkdir mvs cd mvs wget https://wotho.ethz.ch/tk4-/tk4-_v1.00_current.zip unzip tk4-_v1.00_current.zip
Now your MVS emulation is ready to be started.
The basic configuration doesn’t need any change and runs in unattended mode with the simple command:
This launches an unattended startup. At the end of the load procedure, you will see the following screen:
Connect To MVS
To login into your MVS, you will need a terminal capable to start an x3270 session.
For Windows PC, a free terminal can be downloaded from https://sourceforge.net/projects/x3270/. Another alternative is the good Mocha TN3270 available with 30 days trial as Chrome Extension from Mocha Chrome store.
In both cases, set your connection parameters with:
- Host: IP address of your Raspberry PI
- port: 3270
Once connected, a logon is required:
Use one of the default users. For example:
- user: HERC01
- password: CUL8TR
Once connected, with 2 RETURN pressing you will go to TSO home page:
Very First Exercise With TK4 TSO: Create a Simple Dataset
Terminal Emulator Screen
Before all, a few descriptions of the main parts of the Terminal Emulator. It is composed of 3 main parts:
The emulation screen usually gives in the top section an Options field where you can select the desired option to execute (Return to execute in some terminal emulators, or CTRL in some other terminal emulators). Options are listed in the following section, each line reporting the option number and related action.
Function keys (F1 to F12) have an important role in terminal because each one is a shortcut to a specific function. For example, the most common and most used is F3, to go back to the previous screen.
What Is a Dataset
A data set or dataset (refer to Wikipedia for Data set description) is a file with a record organization. It can be associated with a mix of more common Windows directories and files or Linux folders and files.
To create the first dataset (which will be a simple text dataset), from TSO home page with option 2 select the RPF productivity tool. With the word “select”, in this paragraph, I will intend to write the option number and press Return (or CTRL where it is configured as option confirmation):
Select 3 to use RPF utility:
Select option 2 to Create a new dataset:
Here we’ll configure dataset naming (and logical position) modifying parameters circled in the following picture. All other parameters can be left with default values:
Now select option 1 to allocate (the space) the dataset. The terminal confirms that the dataset has been allocated:
Press F3 to go back to RPF Utility Menu and select option 4 to search available datasets:
Edit in the search window (ops… sorry mainframers, I intended label 🙂 ) with the prefix setup in the previous step. In my case, “PEPPE”:
And press Return (or CTRL) to list available datasets with the same prefix. In a new environment, it will show the only one dataset allocated:
Now, the most common actions with a dataset are browse (to view their content), edit (to modify their content) or delete (to delete the entire dataset). These actions can be performed by adding the related command letter (b=browse, e=edit, d=delete) on the left of the dataset. We’ll perform and edit to add content to our dataset. So, add the “e” at the left of the dataset:
And press Return (or CTRL). An empty editor screen will appear. Fill in with text of your choice and press return to have the prompt back in the “Cmd” area:
type save near the Cmd area and press return.
Select option 1 and press Return. The terminal will go back in the dataset list, also confirming that your dataset has been edited:
Congratulations, you have created your very first dataset!
Now press F3 as many times as to go back to TSO home screen.
To shut down, simply exit from TSO (from TSO home screen press F3):
and simply type “shutdown” and press Return (or CTRL). This will start the shutdown procedure.
Interested in more projects with your RPI? Take a look at peppe8o Raspberry PI computers tutorials pages.
We are sorry that this post was not useful for you!
Let us improve this post!
Tell us how we can improve this post?