The desire to see it all in one place is understandable, but it makes no sense to crowd up a perfectly constructed visualization with a sub aggregation of an irrelevant field. Try and avoid overcomplicating your visualizations. If it’s a pie chart visualization for example, use the basic default settings to see a breakdown of the top five results for a specific field. You don’t have to start with a fancy Timelion visualization. Start by defining a goal by asking yourself a simple question - what are you trying to analyze or monitor?Īre you looking for a historical trend over time for a specific field? Do you want to see a simple breakdown of the top ten values for a specific field? If you are monitoring traffic to your website, do you want to see a geographical depiction of where the originating request is coming from?Īnswering this question provides you with pieces of information required for the next step - what fields you are going to use, what visualization type is best suited, and of course what log type is going to be used (in case you’re shipping multiple types). Once you have a clearer understanding of your data, you can begin to strategize your visualizations. Play around with queries and searches, do some research on the fields, take a look at their type and value. This understanding is often gained by setting up parsing but if this was performed by a colleague or automatically (if you’re a Logz.io user), exploring the data is up to you. If you know, for example, that the field response_code is mapped as a string and not an integer, you will know that you cannot use metric aggregations with it in visualizations. Understanding your data is key to an easier visualization. Application logs, for example, will require more discipline and thinking from the developers (read more about application logging ). If you’re shipping a common log type, your data will most likely be structured and formatted in a standardized way. The more structured and consistent your data is, the easier it is to parse them and later on build visualizations. Kibana visualizations are based on the fields constructing your logs. Still, there are some general best practices that can be outlined that will help make the work easier. This makes it quite challenging to provide rules of thumb when it comes to creating visualization in Kibana. Logs come in all sorts and shapes, and each environment is different.
#Wms url for kibana how to
This tutorial will hopefully help those of you stuck on your first or second visualization understand a bit more on how to visualize data in Kibana. Experience is important as well as intimate knowledge of your log data. Kibana super-users might be able to glide through these steps with ease, but most users can and will find it challenging. Truth is, though, before you reach the stage where you’re gazing upon a beautiful Kibana dashboard there are some necessary steps that you need to go through. Whether a simple pie chart or a more complex Timelion visualization, being able to slice and dice your data is one of the reasons I love using Kibana.
There’s something visually appealing about different charts and graphs depicting your data in real time.
Who doesn’t like a beautiful Kibana dashboard? In this part, we will outline the next natural step in using Kibana - visualizing your log data.
#Wms url for kibana software
In part 1 of this series, we described how to get started with Kibana - installing the software and using various searches to analyze data.
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