In my last articles, I have introduced the foundations for storing geospatial information in Elasticsearch. For various use cases, Kibana and the Elasticsearch Query DSL offer powerful features to solve specific problems.
The Elastic Stack is an open source foundation that offers data solutions from any source and any format. Digitalisation is just the start of exciting data exploration. We start our journey with geospatial information.
By the end of September 2018, my last day of work for a payment service processor ended. It was a tough decision to leave behind a great team and safe environment to face a new challenge. The chance to work with cutting-edge technologies and products convince me to take the opportunity. I leave with love and respect for the past years. I think the best occasion to part ways if there is nothing left to remove for a working solution.
Docker has its strength by isolating applications through containers. Each container has its namespace and a network subsystem. Starting with Docker containers there is a different approach to check connections for your running application.
Just bought terrific music from Bandcamp and downloaded the FLAC archives. Now I needed to extract them in the terminal console and run into little problems.
Tuning Elasticsearch is an advanced topic, that attending in an Elasticsearch Engineer Training by elastic is pretty simple to understand. The usual answer is always:
It depends. I summarise my notes and findings on this. Consider there is always a lot more to it. The training covers it all. It is undoubtedly worth to attend. Education is important ;-). Roughly it is about Elasticsearch Internals (Apache Lucene under the hood), Capacity Planning and smart choices/anticipation.