How to implement log management with the ELK stack

Short answer

Deploy Elasticsearch, Logstash, and Kibana as Docker services, configure the Docker logging driver or Filebeat to forward logs, and visualize them in Kibana dashboards.

Details

A common setup uses Docker Compose to run the ELK stack on a dedicated logging host. Configure the json-file logging driver on your application containers, then mount the Docker logs directory into Filebeat. Filebeat ships logs to Logstash for parsing (e.g., extracting timestamps and levels), and Logstash forwards structured data to Elasticsearch. Use Docker volumes to persist Elasticsearch data outside the container so indexed logs survive restarts. If you need to transform logs with custom scripts, writing bash scripts to preprocess files before ingestion can reduce Logstash complexity.

Tips

• Set index lifecycle policies in Elasticsearch to roll over and delete old logs automatically.
• Avoid logging sensitive data in plain text; redact tokens before they reach the log pipeline.
• Monitor Elasticsearch disk usage; unbounded log growth can crash the cluster.