The Dockerfile below is used to add Filebeat configuration files to the base Filebeat image and nothing more. Filebeat ships with a sample Kibana dashboard that looks like this:Īs well as shipping Docker logs, I write the logs from my ASP.NET Core applications to disk (The best way to make sure you never lose log information) and then use Filebeat to ship these log files to ElasticSearch. You can then view these logs in a fully customizable Kibana dashboard. The latest version 6.0 queries Docker APIs and enriches these logs with the container name, image, labels, and so on which is a great feature, because you can then filter and search your logs by these properties. cat /dev/null > /var/lib/docker/containers/CONTAINERID/CONTAINERID-json.log. EDIT: based on the new information, note that you need to tell filebeat what indexes it should use. Running docker info shows plenty of data space available but my root file. You can also crank up debugging in filebeat, which will show you when information is being sent to logstash. Check /.filebeat (for the user who runs filebeat). Performance and Root Cause Analysis, Combines APM and Low Level Developer Style Tooling. Filebeat keeps information on what it has sent to logstash. In terms of Beats, I use three of them which I'll talk about below: Filebeatįilebeat is a tool used to ship Docker log files to ElasticSearch. 3) Explore/query old performance data in a simple manner. There is a cost versus effort trade-off in this decision and it's up to you where you decide to go. I had a look at the ElasticSearch Docker container and if you really want to go down the Docker route and create an ElasticSearch cluster, it looks fairly straightforward but a bit unorthodox. Using a hosted version takes some of the pain out of maintaining ElasticSearch. While you could use Docker to host ElasticSearch and Kibana, I use the ElasticCloud at work, you could also use instances hosted by AWS and Azure. There are several Beats which are used to ship data into ElasticSearch from various sources. Kibana is a visualization took that gives you a nice UI to view all of your data and produce nice visualizations and dashboards. To collect logs from my Swarm and monitor the health of it, I use the ELK-B stack which is made up of four pieces of software called ElasticSearch, LogStash (I recommend that you use Beats instead of LogStash), Kibana and various Beats.ĮlasticSearch is basically a No-SQL database that is geared towards storing JSON documents and searching across them. Knowing what is happening in Docker and in your applications running on Docker is critical. Useful Docker Images - Administering Docker.
0 Comments
Leave a Reply. |