Unlocking System Insights with the ELK Stack
In a complex IT environment, logs are generated everywhere. A centralized system turns this chaos into clarity, enabling real-time monitoring, rapid troubleshooting, and proactive security.
100%
System Visibility
90%
Faster Troubleshooting
75%
Improved Anomaly Detection
A powerful, four-part system for managing log data from end to end.
A lightweight shipper that tails log files and forwards the data efficiently.
A server-side pipeline that processes, transforms, and enriches the log data on the fly.
A distributed search engine that stores and indexes logs for lightning-fast retrieval.
A web interface for creating dashboards, exploring log data, and setting up alerts.
A simplified path to getting your ELK stack running on Ubuntu.
Start by installing Java, the runtime for Elasticsearch, and adding the official Elastic APT repository to your system to access the necessary packages.
Install and enable the core components: Elasticsearch for data storage and Kibana for visualization. Configure Kibana to be accessible over your network.
Deploy the data shippers. Install Filebeat on source servers and configure Logstash to receive, process, and forward the logs to Elasticsearch.
With all components running, create an index pattern in Kibana. Your logs are now centralized, searchable, and ready for analysis.
Visualize trends and set up proactive alerts to monitor system health.
Visualizing the volume of logs over time helps identify unusual spikes that could indicate an application error, a security event, or a sudden increase in traffic. A line chart provides a clear, at-a-glance view of system activity.
Each part of the stack plays a distinct role. This donut chart shows the conceptual breakdown of the workflow into four key stages.
Set up rules to get notified of critical events automatically. This example shows an alert for multiple failed SSH logins.
IF `system.auth.ssh.event` is `Failed`
AND Count is > 5
WITHIN `last 5 minutes`
THEN TRIGGER ALERT