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If you don’t measure it, you can’t improve it: DevOps concepts meets Qlik Sense

Real-time monitoring of user sessions using Butler SOS

Butler SOS 4.0 is out, adding features that make it easier than ever to monitor large Qlik Sense environments. We’ll return to this topic of course, but let’s first take a few steps back.

There are many variants of that quote: “If you can’t measure it, you can’t improve it”, “Measure what matters”, “Measure what is measurable, and make measurable what is not so.” and others. The last one supposedly originates with Galileo Galilei. Smart guy.

The development of Butler SOS continues in that spirit. Qlik Sense provides an awesome platform on top of which all kinds of data analysis, visualisation and presentation solutions can be built. A key word there is platform. Sense does not offer solutions to all software development challenges, nor should it. Instead, use the tools and best practices that millions of developers around the world have refined over the years.

Qlik Sense does on the other hand offer a very comprehensive set of APIs that give developers access to its internals – and this is part of why it’s such a powerful platform. Butler SOS taps into some of these APIs, exposing their data in the form of real-time dashboards, charts and alerts. Suddenly sysadmins know can get both an overview of how all servers are doing, as well as look at detailed server metrics when so needed.
All made possible using the Sense APIs, but in general powered by various open source tools.

We’re basically back to Galileo – let’s make sure the important parts of Qlik Sense are measurable. It is then possible to improve the parts that don’t work well.

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Monitoring for Qlik Sense: Butler SOS v3 is out

The latest version fo Butler SOS is out, taking the version number to 3.0.
A lot of the code has been fine tuned to better meet the needs of enterprise grade Qlik Sense deployments.

Docker (or some compatible container platform) is now the preferred and recommended way of running Butler SOS. Butler SOS has been developed and tested on Linux and Mac OS, but should in theory run also other Docker enabled platforms.

New features

Version 3 adds a few – but useful – features:

  • Per-server config option “serverGroup”. Use this to group or categorize servers, for example as being part of a production vs development Qlik Sense cluster. This enables the creation of Grafana dashboards that use Grafana variables to automatically show metrics for all PRODUCTION servers. This greatly simplifies using Butler SOS in large Qlik Sense environments, where servers are frequently added/removed. No need to manually update the Grafana dashboards any more.
  • Config option “queryPeriod” for controlling how far back querying for Sense log entries should be done. Used together with the logdb.pollingInterval setting, it is now possible to fine tune how often the Qlik Sense log database is queried for errors and warnings.
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Docker everywhere – Qlik Sense operations monitor using Butler SOS

Following up on previous posts (here and here) about the Butler family of tools being Dockerized, here is another one on the same topic:

Butler SOS can now be run in a Docker container. 

This is good news as it makes it a lot easier to set up real-time monitoring of a Qlik Sense enterprise environment, compared to the previous (still working, btw) method of installing Node.js and then running Butler SOS on top of Node.

The Github repository has all the details – head over there to get the latest release of the code as well as instructions how to run Butler SOS using Docker.

The Docker image is available on Docker Hub, if you want to get started right away.

 

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Reading sensor data from a Verisure home alarm system

I recently upgraded our house alarm system to the latest model from Verisure.

Pretty nice actually, the new system comes with a good mobile app, remote querying of both alarm status and status of the various sensors (smoke, movement etc) that are included in the system. Oh, the new system actually cost less per month too, compared to the old one. Go figure.

Being the geek that I am, I immediately wondered if it was possible to get hold of the sensor readings (temperature and humidity) that were shown in the mobile app.

Turns out it is pretty simple. There is a REST API which can be queried, and from there you get back all kinds of status for the system. With that data nicely structured in a JSON it’s then a breeze to send the data to a MQTT pub-sub broker for later use by whatever system that might need it. Easy in theory.

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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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