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.

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 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.