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.
Before the summer the Butler tool turned two years old – time flies!
Over those years I have installed, tweaked and upgraded a fair number of Butler instances… Not a problem per se, but maintaining a production grade Butler instance does assume a certain level of experience around Node.js, Linux, networking etc.
The most recent Butler version (v2.2) attempts to make it easier to deploy and operate Butler. This is achieved by deploying Butler as a Docker container instead of a regular Node.js app.
The Docker image (from which a container is created) contains exactly the same Node.js app that you can run right on your server or laptop – i.e. there is no functional difference what so ever between running the Node app natively, and running it as a Docker container.
There are some significant benefits of running Butler under Docker:
This one is long overdue, but finally here: Butler SOS v2.0
The new version is an almost complete re-write of v1.0. Changes are plentiful and include
All warnings and errors stored by Sense in its log database are now pulled into Butler SOS, from where it can be graphed and acted upon. This is a big deal, as it was previously not possible to get notifications or alerts when errors or warnings started to pile up in the logs.
Operational health metrics are still pulled from Qlik Sense, but this is now done directly from the QIX engine rather than via a hard-to-secure virtual proxy.
Using certificates for authentication with Sense removes potential security issues with v1.0.
Config file is now YAML instead of JSON. More human readable and with inline comments.
Config file now allows for more fine-grained control of Butler SOS.
Several bugs fixed, especially around sending metrics to MQTT.
The readme file on GitHub has all the details, here are some screen shots to get you started though:
When relying on various Node.js services (e.g. Butler SOS, Butler, App Duplicator etc), you quickly run into the challenge to ensure all services are always up and running.
A failing service might be fine, as long as it is quickly restarted in a predictable way.
A concrete example could be Qlik Sense or QlikView apps that send status messages to Slack during the execution of their reload scripts. Those messages will fail if Butler is for some reason not running.
This leads us to the conclusion that the services must automatically be
a) started when a server is rebooted, and
b) restarted if they for some reason terminate/die.
Enter process monitors.
At their core, process monitors ensure that the desired processes are always running, i.e. bullet b) above. Some process monitors also offer additional features such as zero-downtime restart of services, memory and performance profiling of the monitored services, being able to monitor different kinds of processes (not only Node.js ditto).
Adding to the pain is the fact that Sense and QlikView runs on Windows servers, meaning that all those great tools available on Linux cannot be used.
Looking at Node.js specifially, I have found two process monitors to work well on Windows: Forever and PM2.
I was recently in Helsinki, giving a talk at a QlikDevGroup event. Great event, great crowd. The topic was SenseOps and Butler SOS, and I showcased the lamp above as an example of a funky, but still relevant way to monitor user activity in a Qlik Sense Enterprise environment.
A person in the audience asked how the map works. I claimed it was super simple, costing less than USD 10 to build (assuming you already have a suitable enclosure) and uses just four wires hooked up between some pre-made modules. Time to prove it.
The four wires part might have been a slight exaggeration… but it depends on which wires you count – right?
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.