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Even if they are currently considered as an outdated technology (compared to modern virtual machines / container technology), they are still deep-rooted in modern datacenters, expecially for banks, stock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 ecommerce shopping chart all needed hardware, so that at the end you will be able to evaluate overall costs and decide if continuing with the project or removing them from shopping chart. So, hardware will be only:
- Raspberry PI (including proper power supply or using a smartphone micro usb charger with at least 3A)
- micro SD card (at least 16 GB, at least class 10)
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.
Install Raspberry PI OS using Install Raspbian Buster Lite in your Raspberry PI guide.
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 http://wotho.ethz.ch/tk4-/tk4-_v1.00_current.zip unzip tk4-_v1.00_current.zip
Now your MVS emulation is ready to be started.
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 load procedure, you will see the following screen:
Connect To MVS
To login in 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 case, set your connection parameters with:
- Host: IP address of your Raspberry PI
- port: 3270
Once connected, a logon is required:
Use one of 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 description of main parts in Terminal Emulator. It is composed by 3 main parts:
Emulation screen usually gives in top section an Option filed where to select desired option to execute (Return to execute in some terminal emulators, or CTRL in some other terminal emulator). Options are listed in following section, each line reporting 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 in 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 to 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 option number and press Return (or CTRL where it is configured as option confirmation):
Select 3 to use RPF utility:
Select otion 2 to Create a new dataset:
Here we’ll configure dataset naming (and logical position) modifying parameters circled in 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 dataset have been allocated:
Press F3 to go back in RPF Utility Menu and select option 4 to search available datasets:
Edit in search window (ops… sorry mainframers, I intended label 🙂 ) with the prefix setup in 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 datased 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 dataset. We’ll perform and edit to add content inside our dataset. So, add the “e” at the left of dataset:
And press Return (or CTRL). An empty editor screen will appear. Fill with text at your choice and press return to have prompt back in “Cmd” area:
type save near Cmd area and press return.
Select option 1 and press Return. Terminal will go back in dataset list, also confirming that your dataset have been edited:
Congratulations, you have created your very first dataset!
Now press F3 as many times to go back in TSO home screen.
To shutdown, simply exit from TSO (from TSO home screen press F3):
and simply type “shutdown” and press Return (or CTRL). This will start shutdown procedure.
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