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deviantony/docker-elk

0
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18,375 stars·6,921 forks·Shell·MIT·18 views

Docker Elk

This project is a containerized orchestration layer for the Elastic Stack, providing a pre-configured set of Docker Compose files to deploy Elasticsearch, Logstash, and Kibana as a unified data analysis stack. It functions as a centralized log management system for ingesting, indexing, and searching log data using a cluster of interconnected services.

The deployment pattern includes an Elasticsearch cluster manager that enables scaling data nodes through replica scaling and internal discovery. It provides a web-based administration interface for monitoring cluster health and status.

The system covers a broad range of operational capabilities, including log data ingestion, distributed data clustering for high availability, and infrastructure monitoring. It manages networking isolation for internal service communication while supporting external container networking to capture logs from other applications.

Configuration and maintenance are handled through environment-driven settings for resource allocation tuning and command-line utilities for user credential management.

Features

  • Observability Stack Deployments - Orchestrates the deployment of a complete observability suite comprising Elasticsearch, Logstash, and Kibana.
  • Compose Orchestrators - Uses Docker Compose to orchestrate the interdependencies and networking of the full Elastic Stack.
  • Full-Stack Orchestration - Packages the full search and visualization suite into a coordinated set of containers.
  • Centralized Logging Systems - Implements a system for aggregating and searching logs from distributed components in one store.
  • Log Ingestion - Provides the pipeline to receive and import log data from diverse network sources.
  • Elastic Stack - Deploys the integrated suite of Elasticsearch, Logstash, and Kibana for log analysis.
  • Persistent Volume Mapping - Maps host directories to containers to ensure log data persists across restarts.
  • Database Cluster Scaling - Enables scaling of data nodes through replica management and internal discovery.
  • Docker Compose Deployments - Uses Docker Compose templates to deploy the full analysis stack as coordinated services.
  • Cluster State Synchronization - Implements synchronization of cluster state and discovery mechanisms across multiple data nodes.
  • Container Networking Configurations - Configures shared networks to link external application containers for log capture.
  • Network Isolation - Provides dedicated virtual networks to isolate analysis tools from the host system.
  • Distributed Storage Clusters - Aggregates multiple nodes into a unified storage system to increase capacity and availability.
  • Cluster Administration - Provides a web-based administration interface for monitoring and managing the health and status of the Elasticsearch cluster.
  • Elasticsearch Health Monitors - Includes a web-based interface for monitoring the health and status of the Elasticsearch cluster.
  • Infrastructure Monitoring - Captures and visualizes system performance and error logs from connected containers.
  • Observability and Monitoring - ELK stack deployment via Docker Compose.

Star history

Star history chart for deviantony/docker-elkStar history chart for deviantony/docker-elk

How this analysis was created: This summary and feature list were written by an AI model that read the project's README and public documentation pages. Each feature links to the documentation it came from; stars, license and language come straight from the GitHub API. The model does not read the source code, and the analysis is refreshed when the project is re-analysed. Learn more on our About page.

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Frequently asked questions

What does deviantony/docker-elk do?

This project is a containerized orchestration layer for the Elastic Stack, providing a pre-configured set of Docker Compose files to deploy Elasticsearch, Logstash, and Kibana as a unified data analysis stack. It functions as a centralized log management system for ingesting, indexing, and searching log data using a cluster of interconnected services.

What are the main features of deviantony/docker-elk?

The main features of deviantony/docker-elk are: Observability Stack Deployments, Compose Orchestrators, Full-Stack Orchestration, Centralized Logging Systems, Log Ingestion, Elastic Stack, Persistent Volume Mapping, Database Cluster Scaling.

What are some open-source alternatives to deviantony/docker-elk?

Open-source alternatives to deviantony/docker-elk include: collabnix/dockerlabs — dockerlabs is a collection of educational labs and technical tutorials designed to teach the fundamentals of… victoriametrics/victoriametrics — VictoriaMetrics is a high-performance, scalable time series database and observability platform designed for long-term… uptrace/uptrace — Uptrace is an OpenTelemetry-based observability platform designed to collect, store, and analyze distributed traces,… highlight/highlight — Highlight is a full-stack observability platform and monitoring system that aggregates logs, errors, and distributed… graylog2/graylog2-server — Graylog2-server is an open-source centralized log management system and aggregator. It functions as a log analysis… elastichq/elasticsearch-hq — Elasticsearch-HQ is a web-based management interface used to monitor and administer Elasticsearch clusters, indices,…