Running Elasticsearch as docker container is straightforward. If you don’t have a cluster manager like Kubernetes, monit can help you to keep track of the container lifecycle.
Running Elasticsearch as docker container is straightforward. If you don’t have a cluster manager like Kubernetes, monit can help you to keep track of the container lifecycle.
Do you ever run into the situation that a open source library uses a logging framework and you don’t know which one? If you use Apache Maven as build tool, the easiest solution is just to invoke mvn dependency:tree.
The aggregations framework helps provide aggregated data based on a search query. It is based on simple building blocks called aggregations, that can be composed in order to build complex summaries of the data. There are several types of aggregations. The cardinality aggregation is the exact match for distinct field values.
If you have the need to comment a whole file sed is very handy to comment and uncomment files.
If you have an application which does distributed computing, i.e. means connects to other servers and send data, it is interesting to monitor the connection handling. Therefore collectd provides the plugin tcpconns, that allows to monitor dedicated ports. This data can be send to logstash, where it can have graphite or elasticsearch as output. Having the data in a metrics storage, visualization with Kibana or Grafana is a piece of cake.
Marvel is the monitoring plugin for Elasticsearch and Kibana. If you do maintenance in Elasticsearch, and therefore close indices, you might stumble over some ERROR messages in the elasticsearch log. (Update: elastic rebranded it as x-pack monitoring)
Monit has the capability to check for a process name. The process itself can also provided a service on a dedicated port, in this Kibana in Production, which uses SSL and expose its service on port 5601.
Using Windows command line is sometimes challenging. Especially if you want to check if a special port is up and running (listening). This post demonstrates how.
A long time ago (seems like ages to me) I have programming in Java and let my projects analyze with Sonarqube. I always remembered that every Sonarqube upgrade wasn’t quick to made. Since Docker I now have the possibility to run the latest stable Sonarqube version. No manual upgrades anymore. Sounds wonderful. Following installation was made on my Linux Box running Ubuntu 16.04.01 LTS with Docker 1.11.2 and PostgreSQL 9.5.