Qlik Sense is very much my go-to tool for many data related questions. It’s very powerful to be able to throw together a proof of concept or test a hypothesis in half an hour. Seeing is however believing, so those prototypes does need some polishing before they can be seen as production grade.
I have always pushed my peers in the Qlikosphere to become better at using icons for their Qlik Sense apps in general, and also for the sheets within those apps. Having an icon for a sheet within an app makes it way easier for the user to find a particular sheet – humans are visual by nature.
Butler SOS has matured quite a bit during past couple of years, with latest additions being fine-grained monitoring of what users are connected to what servers. Opens up for various interesting use cases, including notification to users before server restarts etc.
A brand new doc site (butler-sos.ptarmiganlabs.com) also goes live today (built with Hugo and Docsy, vastly better than the previous one-pager at GitHub.
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.
The basics are the same, i.e. one-click creation of Qlik Sense apps, using regular Sense apps as templates. Several new features however take the tool to a new level, making it easier to set up, manage and more enterprise grade. Good news thus!
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.
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.
Docker is one of those tools that have the potential to fundamentally transform how you develop and run software – once you have tried Docker it is hard to imagine going back to something else.
In previous posts we have seen how Butler, Butler SOS and Butler CW can be run as Docker containers.
But we can do even better – why not control all the Butler tools from a single docker-compose file? Maybe even specifying the dependencies on influxdb and mqtt in there too?
Setting this up is incredibly easy – a single docker-compose file tells Docker what containers to use, and some config files tells the Butler tools where to find things.
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.
I worked out the issue preventing me to add additional nodes to a Qlik Sense Enterprise suystem whose central node had been updated to June 2018.
The June 2018 version of Qlik Sense Enterprise relies on a database called “SenseServices” to be available in the Postgres db (as in earlier versions, Postgres can run on the central node or on some other server).
When running the June 2018 installer on a new server (which is to be added as a new node in a Sense Enterprise cluster), the installer verifies that the SenseServices database exists. If it does not, you get an error half-way through the installer:
Maybe there is info somewhere that you need to create a new “SenseServices” db in Postgress before installing additional Sense nodes… but I looked (a lot) without finding anything.