radoondas.io

Visualise Historical Tornadoes Tracks

Wed, 31 Mar 2021 08:00:00 +0100

Welcome to another blog post where we explore another exciting dataset with Elastic Stack. Today, you will learn how to ingest and analyze Historical Tornadoes tracks covering 69 years’ worth of data. We will explore the dataset, create the ingest pipeline, consume the CSV file with Filebeat, store tornadoes in Elasticsearch, and visualize them in Kibana.

Track Docker Container Pulls with Elastic Stack

Sat, 06 Feb 2021 08:00:00 +0100

In this, yet another, practical post, I will guide you through the simple setup, which will allow you to track the number of pulls of the Docker images uploaded to the Docker hub. By reading the post, you will learn about Metricbeat’s HTTP module, Ingest pipeline, and use Kibana to explore a few simple visualizations. I hope you will find some inspiration for your tasks, which you are at right now.

Elasticsearch Snapshots With Linode Storage Object

Tue, 13 Oct 2020 00:00:00 +0200

Elasticsearch supports several object storage solutions or vendors out of the box for taking snapshots of your data, or for backups. It is as easy as installing the correct plugin, followed by a proper configuration. Using the supported vendor’s storage option is easy and convenient. But, can you take a snapshot into Linode object storage as an S3 compatible solution with Elasticsearch? Let’s find out in this post.

Visualise Covid-19 data Using Elastic Stack (Slovakia)

Fri, 31 Jul 2020 08:00:00 +0100

Covid-19 and its implications are the topic number one for quite some time. The situation naturally provides us a new dataset which any data analyst can process with different tools.

Despite this is not a happy dataset and one I would rather not be part of, it is also an opportunity to use tools, learn new applications, and hope that anything we do will help in some way to other people around us. Whether it is a scientist looking for a different approach to solve the problem or a student learning new tools using interesting data right now, everyone can benefit. Because I believe that we learn by doing ’things’, I am presenting a complete hands-on example based on Slovakia’s data. The same methodology can be applied for similar use cases or just as a proof of concept when needed.

Import Slovakia Regional GIS Data into Elastic Stack

Thu, 23 Jul 2020 08:00:00 +0100

Elastic Map Service nowadays comes with Slovakia regions , which you can happily use with your geospatial data. If you want to have higher precision of Region’s shapes, or you do need to implement the level of ‘districts’ (okresy) or go to the detail of a single city/town, you must use custom map layers. Using different layers is considered a basic task for any GIS application. Possibility to add custom layers in Kibana Maps is available since the introduction and is improving with every release.

Simple GDAL Setup Using Docker

Mon, 20 Jul 2020 08:00:00 +0100

I often work with different geospatial data sets, including geolocation information, and I want to present documents in the context of the Map’s position. To get the job done, I use Elastic Kibana Maps for my visualizations. Elastic provides Elastic map service (ESMS), which anyone can use for geospatial visualizations. The service includes different vector layers out of the box and is kept up to date and improved continuously. Only recently, all the Europe regions were completed on ESMS and released to the public.

You know, for sharing

Mon, 23 Mar 2020 08:08:00 +0100

For years, actually many years, I was reading, learning, and using someone’s else posts, sites, knowledge, and more. Using all of this for free, it is now my turn to share some knowledge and experiences. Any feedback is appreciated. Thanks!