Elasticsearch is a powerful search engine developed in Java with clients available for many of the major languages. Data is stored as JSON documents and are easily and quickly searched via an HTTP interface. Elasticsearch is popular to run together with Logstash for data-collecting and processing logs, and Kibana for visualizing the data. This is referred to as the Elastic Stack, and Elasticsearch functionality in the stack is to store the data and make it searchable.
When dealing with multiple servers, and especially in a high availability environment handling logs can get quite complex. It can become difficult to debug with logs spread out over multiple servers and this is one of the problems that Logstash attempts to address. Logstash is also part of the ELK (ElasticSearch, Logstash, and Kibana) Stack, lately referred to as the Elastic Stack, which together form a very powerful tool for managing, reading and visualizing logs and data. In the Elastic Stack series, we are going to have a look at each of the tools and go through some best practices.
Docker Swarm enables us to easily scale up and down our servers with containers, but how do we take advantage of all of our containers? Preferably we would want to spread out the load across the multiple containers. With a HAProxy this becomes possible.
Welcome to the promised NoSQL with Couchbase series, in these articles we are going to learn how to use a NoSQL database called Couchbase. We are going to investigate and learn what it is extremely good at and what it is not the best at. There is quite a lot of stuff to go through, I am imagining it being enough content for around 5-6 articles and therefore I feel like we have to split it up. This first episode we will focus on installation, and as a bonus, we will also get a quick introduction to another powerful tool called Docker.