MQ

Hello friends, 

Leadership is putting together a roadmap for the next 5 years and this will include A.I.
I was tasked to research and put together any plans that we could leverage A.I. for MQ
I couldn't find any information out there and thought I'd ask the experts  ;)
We are currently at zOS MQ 9.3 LTS. 
I appreciate any feedback. 

Thanks,
Michael

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Michael Pearson
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Hi Michael,

This topic has come up a number of times with MQ on z/OS over recent years. Other customers have tended to focus on applying AI to the SMF data that the queue manager produces. The idea being that they can learn what is normal for their MQ on z/OS systems and then react quickly if anomalies occur. 

Those discussions lead us to make a number of improvements to the queue manager. Including the ability to collect SMF data every second if needed: high fidelity data allows better modelling and decision making. The other big change was per queue SMF statistics, allowing customers to focus on what really matters, the queues. Both of those are in 9.3.0, and the queue statistics has been enhanced in the 9.3.* CD releases too.

IBM Z Anomaly Analytics - IBM Z Anomaly Analytics

Ibm		remove preview
IBM Z Anomaly Analytics - IBM Z Anomaly Analytics IBM Z Anomaly Analytics delivers intelligent anomaly detection to avoid costly incidents. View this on Ibm >

We have also been working with our z/OS colleagues to add support for MQ to IZAA: https://www.ibm.com/products/z-anomaly-analytics. IZAA will take MQ's SMF data and build a model from it using AI, and then alert you when anomalies are detected.

Happy to have a chat if you want to discuss further.

Regards, Matt.

Hello friends, 

Leadership is putting together a roadmap for the next 5 years and this will include A.I.
I was tasked to research and put together any plans that we could leverage A.I. for MQ
I couldn't find any information out there and thought I'd ask the experts  ;)
We are currently at zOS MQ 9.3 LTS. 
I appreciate any feedback. 

Thanks,
Michael

------------------------------
Michael Pearson
------------------------------

Hi Michael,

This topic has come up a number of times with MQ on z/OS over recent years. Other customers have tended to focus on applying AI to the SMF data that the queue manager produces. The idea being that they can learn what is normal for their MQ on z/OS systems and then react quickly if anomalies occur. 

Those discussions lead us to make a number of improvements to the queue manager. Including the ability to collect SMF data every second if needed: high fidelity data allows better modelling and decision making. The other big change was per queue SMF statistics, allowing customers to focus on what really matters, the queues. Both of those are in 9.3.0, and the queue statistics has been enhanced in the 9.3.* CD releases too.

IBM Z Anomaly Analytics - IBM Z Anomaly Analytics

Ibm		remove preview
IBM Z Anomaly Analytics - IBM Z Anomaly Analytics IBM Z Anomaly Analytics delivers intelligent anomaly detection to avoid costly incidents. View this on Ibm >

We have also been working with our z/OS colleagues to add support for MQ to IZAA: https://www.ibm.com/products/z-anomaly-analytics. IZAA will take MQ's SMF data and build a model from it using AI, and then alert you when anomalies are detected.

Happy to have a chat if you want to discuss further.

Regards, Matt.

Hello friends, 

Leadership is putting together a roadmap for the next 5 years and this will include A.I.
I was tasked to research and put together any plans that we could leverage A.I. for MQ
I couldn't find any information out there and thought I'd ask the experts  ;)
We are currently at zOS MQ 9.3 LTS. 
I appreciate any feedback. 

Thanks,
Michael

------------------------------
Michael Pearson
------------------------------