This release both adds some nice new features as well as enhancing existing ones and fixing some bugs. Let’s take a look at the highlights.
Track in detail whatapps are loaded into each Sense server.
Regular apps and session apps are handled separately, making app metrics easier to understand and more relevant
Sample dashboards are now built using the brand new, shiny and all together awesome Grafana 7. Did I mention that Grafana 7 is awesome? Awesome.
Ever wondered how long Butler SOS has been running or how much memory it uses? The new uptime messages have you covered.
You are properly impressed with the uptime messages – good. Why not store them to Influxdb, so you can also visualize Butler SOS’ own memory use? It’s just a couple of changes in the config file away.
Better control over what features are enabled. Don’t need Docker health checks? Now you can turn that (and other) feature off.
Ah, you are a serious Sense user and have separate DEV and PROD environments? Good – now Butler SOS supports multiple instances running on a single server.
Who will monitor the monitor? Butler SOS can now send heartbeats to customisable URLs at desired intervals. Perfect if you want to monitor Butler SOS using for example healthchecks.io. Very, very cool actually.
Bugs, bugs and bugs. The known ones have been fixed. Keep reporting new ones!
Update all dependencies to latest versions, to ensure security concerns are adressed.
Curious what it looks like in practice? Seeing is believing:
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 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!
For years I have thought about ways to get data lineage info for all apps in a Qlik Sense Enterprise environment.
It would be super useful to know exactly what apps use a particular data source, as well as vice versa (what data sources are used by a specific app). I know there are commercial tools doing this and much more, but I wanted something easy to use, yet still effective and free.
Same thing for app load scripts: Extracting and storing them to disk in human readable format has more than once save days of work, when something has gone badly wrong in an app. Dumping load scripts to disk was possible in my original Butler tool, but then only one app at a time. So not quite what was needed in an enterprise context.
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.
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: