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Butler SOS goes main stage at Qonnections 2017

Edit:

Qlik has made available a video from Anthony Deighton’s (Qlik’s CTO) keynote session.

Very much worth looking through the entire video – it was very interesting indeed. 
His highlight of customer and partner project’s is found 12 min 36 sec into the video.

 

 

A few weeks back something cool happened.

During the big, main stage keynote session at Qlik‘s annual Qonnections conference, my Butler SOS project was highlighted as an example of a great application built on top of the Sense APIs.

I have to admit that it is pretty neat to get that kind of recognition from industry peers… a bit of ego boost :).

And it makes it easier and even more fun to work out coming, similar concepts and services. Lots more to be done around DevOps and Qlik Sense.

Speaking of which:
I started playing around with Qlik’s new Enigma.js library a week or so ago, to see if it could be used in coming projects.

Very nice indeed. Nothing wrong with good old Qsocks, but Enigma is a step in the right direction. Just like qsocks, Enigma is open source – but also fully supported by Qlik. That is a huge advantage!

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Butler SOS: real-time server stats for Qlik Sense

I got somewhat distracted from the idea of breaking up the existing Butler software into smaller, stand-alone micro services.
Or rather, an idea came to mind. An idea too good not to explore…

The healthcheck API of Qlik Sense provides basic metrics for both the Qlik Sense engine itself, and the server it is running on. Things like CPU load, available RAM, number of connected users and what apps are loaded into the Sense engine.

The idea behind Butler SOS ( SOS = SenseOps Stats) is very simple:
Get the healthcheck metrics for all servers in a Sense cluster. Then send the information to MQTT for immediate, real-time use cases.
It is directly aimed at bringing better features to the monitoring step of SenseOps – please visit SenseOps.rocks for more info on SenseOps.

Butler SOS is nice and sending data via MQTT make the health metrics available in for example Node-RED. Node-RED has some basic graph options, but not anywhere near those offered by Grafana. Grafana is very, very cool… A live demo is available here – do check it out – it is very nice indeed.

Creating real-time dashboards in Grafana is greatly simplified if the data is stored in some kind of time series database. Influxdb is an obvious choice. It is open source, installation is very easy, and there are good Node.js libraries that make it trivial to insert data into a Influxdb database.
Thus – Butler SOS also sends the Sense health metrics to an Influx db of choice.

Only need Influxdb and not MQTT? Or the other way around?
No problem, the Butler SOS config file include options for independently turning on/off sending of data to MQTT and Influxdb.

Butler SOS, including a sample Grafana dashboard, is available on GitHub.

Using Grafana we get dashboards and charts like these:

Showing CPU load, available RAM, active users, cache hit ratio and more.
A 100% cache hit ratio (left y axis) means that no additional calculations were needed to serve the requested data to the client. The yellow dots are associated with the right y axis, which tells us how big the request in question was.

 

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