Bringing Agility to Mainframe Data Access Using Bluemix
This is part 5 of a five-part series on accessing mainframe data from your Bluemix applications.
- Part 1: Bluemix Meets Mainframe Data
- Part 2: Installing Rocket Mainframe Data Service on Your Mainframe
- Part 3: Mapping Your Mainframe Data for Access From Bluemix
- Part 4: Building an Application in Bluemix That Accesses Mainframe Data
- Part 5: Bringing Agility to Mainframe Data Access Using Bluemix (this entry)
In this last post of the series, I want to share a story that really demonstrates the power of this service on the mainframe.
This summer two interns were assigned to a project under me. We were tasked with building an IT operational analytics dashboard using SMF data from the various mainframe systems that we have at Rocket. Our goal was to provide it to our system programmers for their day-to-day use and planning.
Eli and Nick, our interns, had no previous mainframe experience and had never interacted with a mainframe. Eli had a computer science background and could pick up new technologies very easily. Nick, on the other hand, an avid builder, loved tinkering with hardware, had a robotics background and was looking forward to adding software experience to his belt.
We decided on the technology stack early on: Angular.js single page app, angularjs-charts for charting using D3, Java for the back-end, and Rocket Mainframe Data service for accessing mainframe data. Eli and Nick spent a couple of weeks understanding and learning Angular.js and identifying which D3 charts would be the most useful for displaying IT operational data.
When it came time to access SMF data, we had the Rocket Mainframe Data Service installed and configured on one of our mainframes. The service comes with pre-mapped SMF data so we didn’t have to go through the mapping step and were able to start looking at data immediately. Eli and Nick spent a few days using the Studio to explore the data available to them in various SMF virtual tables (it was a matter of issuing queries and exploring the data returned to them).
After they were comfortable with the data, we started on the task of building the dashboard. Within about ten days, they built the dashboard that ran in Bluemix and showed the charts built from SMF data on our mainframe. They didn’t have to parse that data. They didn’t have to move it anywhere, nor did they have to worry about real-time access to the data. They were able to access it as if it was pre-populated in a MySQL database and build an IT operational analytics dashboard for the mainframe in a matter of two weeks. No exaggeration!
The dashboard uses data from SMF 30 and 80 records, and shows various times and events that will be of interest to a system programmer. As Eli and Nick were presenting these charts to me, it dawned on me on how much harder it would have been for us to develop this dashboard without the Rocket Mainframe Data Service. Imagine having to learn the SMF record formats and layouts. Imagine having to explore data in the SMF records on the mainframe. They didn’t have to do any of that. They were able to issue queries against (virtual) tables and use their favorite data exploration tool to look at the various SMF records.
The most interaction that Eli and Nick had with a mainframe was that they had to reset their passwords when they were originally setup. What excites me is that now it’s possible for you to do the same. You can use the virtual tables to access mainframe resident data as if it was in MySQL or MongoDB.
We’re excited to see what you build with your mainframe data in Bluemix. Please reach out to us and tell us what you have done with your mainframe data.