First off, we will use the ELK stack, which has become in a few years a credible alternative to other monitoring solutions (Splunk, SAAS …).
It is based on the following software:
E as Elasticsearch, search engine which provide full text search & analytics
L as Logstash, an ETL for retrieving data from heterogeneous sources, transforming them and sending them to Elasticsearch
K as Kibana, which provide an UI for exploring data, and create interactive dashboards
But also :
R as Redis, an upstream broker which will serve as buffer in case of latency of the system, while avoiding excessive congestion in case of a peak,
C as Curator, a tool to manage our index
B as Beats, client-side agent to send the logs/metrics to our stack
We will use Docker containers for each stack component.
Services and interactions are described in a docker-compose.yml file:
version: "2" services: # brocker redis: image: redis:3.2.6 container_name: redis ports: - 6379:6379 volumes: - redis-data:/data networks: - logging # index, search & agregation elasticsearch: image: elasticsearch:5.1.2 container_name: elastic environment: - ES_JAVA_OPTS=-Xms1g -Xmx1g ports: - 9200:9200 - 9300:9300 volumes: - $PWD/elasticsearch/config/elasticsearch.yml:/usr/share/elasticsearch/config/elasticsearch.yml - "es-data:/usr/share/elasticsearch/data" networks: - logging # UI kibana: image: kibana:5.1.2 container_name: kibana ports: - 5601:5601 volumes: - $PWD/kibana/config/kibana.yml:/etc/kibana/kibana.yml networks: - logging depends_on: - elasticsearch # indexer logstash: image: logstash:5.1.2 container_name: logstash command: logstash -f /config/ environment: - JAVA_OPTS=-Xms1g -Xmx1g volumes: - $PWD/logstash/config:/config networks: - logging depends_on: - elasticsearch - redis volumes: es-data: driver: local redis-data: driver: local networks: logging: driver: bridge
Based on this repository, we will deploy a functional stack:
# clone repo & build images git clone https://gitlab.com/flightstar/docker_elk_stack.git cd docker_elk_stack docker-compose build # run (daemon) docker-compose up -d # show logs docker-compose logs
After startup, you should be able to access Kibana (port 5601).
Then, we will deploy a basic example web app (NGinx serving HTML + Filebeat agent to send log in our stack)
# build image docker build ./webapp -t dockerelkstack_webapp # run (daemon) docker run --network dockerelkstack_logging --link redis:redis -p 80:80 -d --name webapp dockerelkstack_webapp # show logs docker logs webapp
After startup, you should be able to access the web app (port 80).
After few minutes browsing, returning to Kibana. An index (logstash-*) is now available.
After creating index, we can now exploring our web app logs (Discover tab), create visualizations (Visualize tab) and dashboards (Dashboard tab).
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