Messaging, Music and Moving Around
This started out as a pleasant-enough chord/bass improvisation. Nothing special but I hoped it might inspire something.
Unfortunately, when I began to put a melody on top, it was sounding a little familiar. It’s a bit jerky because once I got to this point I didn’t bother cleaning up the performances.
Going through the TSA checkpoint in Chicago O’Hare yesterday, the agent said she’d just had someone present her docs and ask “which concourse for Southwest flights”. And replied: “That’s the other side of the city – you need Midway, not O’Hare”
This post shows how you can use Grafana to selectively view information about your MQ configuration. Which may sound a little odd. Grafana’s strength is primarily to show statistics and metrics in pretty graphs. So why would we want to use it to look at queue definitions? The answer is that you usually would not! There are many more appropriate tools for displaying and updating the queue manager configuration – even the MQ Explorer or MQ Console are better. But there may be times when a limited set of information may be desirable, so you can link from a graph to a different view, within the same tool.
But another important aspect that I hope this shows is the power of a common data format. The techniques I’ll show here could be used to combine a variety of different tools, and perhaps this will give you some ideas.
In the departure gate area at Heathrow, waiting for my plane to board. There are delays, and I can overhear conversations between crew, maintenance staff and agents. Eventually there’s an announcement – “the flight will be boarding soon, but can everyone who is seated in rows 32-40 please come to the side.”
The explanation given is that one of the exit doors at the back is broken. It is shut OK but will not open safely and cannot be repaired right away. So the decision is that noone will be allowed to sit in the rear section of the aircraft; they will have to be rebooked. If an emergency happens, they can get the remaining passengers out of the rest of the doors.
Once on board, I can see that the affected rows are taped off. They are not letting anyone spread out into those seats. There are many checks to ensure all the available seats are taken – the small gaps that often exist get filled in. There’s even an announcement that they will do a walkthrough of the cabin and you MUST be in the seat, not even using one of the lavs. Otherwise your seat WILL BE reassigned. While all that is going on, I can see from the window that there’s activity to remove the non-travelling passengers’ luggage. They claim they got all the right stuff off and left the correct stuff on.
What surprised me somewhat was that even after takeoff, when the emergency doors were not useful, they still didn’t allow people to spread out. But the light load did mean we got to Chicago on time, even after the long departure delay!
Recently, we have been creating and publishing a lot of material to help educate people about MQ. You can find that here.
But how might you have learned about MQ in its early days? While hunting through archives for something that I was, in the end, unable to find, I did come across one piece of education that was created over 20 years ago.
You can now see what it was like in this video.
Just a few thoughts that I had:
I hope you enjoy it.
In 2016 I wrote about how MQ’s resource statistics can work with a number of time-series databases, including Prometheus. This permits monitoring using the same tools that many customers use for monitoring other products. It allows easy creation of dashboards using tools such as Grafana.
Since that original version, we’ve made a number of enhancements to the packages that underpin that monitoring capability. For example, more database options were added; a JSON formatter appeared. One notable change was when we split the monitoring agent programs into a separate GitHub repository, making it easier to work with just the pieces you needed.
And now, I’ve released some changes that allow Prometheus and generic JSON processors to see some key channel status information. In particular, a Grafana dashboard can easily highlight channels that are not running.
Continue reading “Using Prometheus to monitor MQ channel status”
MQ Application Activity reports have a lot of detail. This post shows a simple way to extract key fields for simpler processing.
Application Activity Trace is a mechanism on the MQ Distributed platforms that give a report of all the MQI calls made by a program. Originally configured via a text file, MQ V9 enhanced them by allowing a monitoring application to subscribe to topics that describe the application or channel of interest.
See how to extract key fields from events
In November, I wrote about a new language binding to MQ, making it possible to use Javascript in a Node.JS environment to access the MQ API. I published the first release of that code only through GitHub which required that you clone it locally before you could use it. Once the initial public exposure proved some stability to the interface, I added the ibmmq package to the npm repository meaning that you could simply refer to it in the descriptors (package.json) for your programs and npm would automatically download and install it.
But there was still one drawback. The package builds on, and requires, the MQ C client runtime libraries. That needed a separate operation to complete the installation, as those libraries came from product installation media or required you to login to an authorised location before they could be accessed.
No longer though.
Recent updates to the MQ Redistributable Client package and then to the MQ Node.js component have made it much simpler to get an MQ application running, and to create standalone containers for those applications.
Continue reading “Easier use of the Node.js interface for MQ”
Turn MQ SMF data into JSON for simple consumption and analytics. Use a free open source tool for Windows and Linux to process your mainframe statistics.
On z/OS, MQ produces a lot of information about its usage through SMF records. One tool I published on GitHub a couple of years ago was designed to take collected SMF data and process it into a more consumable format. The goal was to create something that did nothing more than format the data, rather than try to analyse it in the manner of SupportPac MP1B. The analysis would be done using independent tools.
The comma-separated-value format is ideal for importing into spreadsheets and databases. Many of our z/OS customers have been helped by reports created from their data, and analysed through SQL queries.
While I didn’t write about it in a blog post then, I did publish a short video showing it in action. And since the original release, I’ve made regular updates to the code. Mostly these have been to simplify the SQL processing.
I’ve now updated the program to give a further output format option. It is intended to make it easy to feed SMF information to other analytics tools, many of which work with JSON structures. Other aspects of MQ administration can now be done with JSON-format data – the error logs on Distributed platforms, an event formatter (which is also available in MQ V9.0.5), the REST APIs for administration and messaging – and this is one further piece of a consistent story.
Application developers who are working in Java, using the JMS interface, often choose to work with the Spring Framework. Spring can simplify the coding of new applications by providing templates for common patterns, and has been successfully used for many
years with the MQ JMS classes. The JmsTemplate class in Spring is the key interface here, but it still relies on having dependencies and configurations defined or coded.
The Spring Framework includes several modules for different capabilities. One of these components is Spring Boot. Spring
Boot starters conveniently pull in all the dependencies and auto-configuration libraries required to use a particular technology. This makes it very easy to get going with a new application and technology, faster than working directly with classes like JmsTemplate. So how can we enable this easy access for MQ applications?
In this post I described how MQ’s Java classes are available for direct download from Maven Central Repository. And we have now exploited that to create a Spring Boot Starter for MQ. You can download full source code for the module from GitHub.
