Introduction
Fess is utilized by organizations across various industries and scales. This page introduces representative use cases and practical examples of Fess deployment.
Note
The following examples illustrate common deployment patterns for Fess. For actual case studies, please contact Commercial Support.
Industry-Specific Use Cases
Manufacturing
Challenge: Design drawings, technical documents, and quality management documents are scattered across multiple file servers, making it time-consuming to find needed information.
Fess Solution:
Unified search across CAD drawings, PDF technical documents, and Office documents on file servers
Cross-search by product model numbers, drawing numbers, and project names
Display search results based on access permissions (role-based search)
Architecture Example:
[File Servers] → [Fess] → [Internal Portal]
│ │
├─ Drawings ├─ OpenSearch Cluster
├─ Tech Docs └─ Active Directory Integration
└─ QC Records
Related Features:
Financial Services & Insurance
Challenge: Compliance documents, contracts, and internal regulations are extensive, making audit responses and inquiry handling time-consuming.
Fess Solution:
Cross-search of internal regulations, manuals, and FAQs
Text search of contracts and application documents
Knowledge search from past inquiry history
Security Features:
Authentication via LDAP/Active Directory integration
Single Sign-On via SAML
API authentication via access tokens
Related Features:
Education
Challenge: Research papers, lecture materials, and campus documents are distributed across departmental servers, making information sharing difficult.
Fess Solution:
Unified search from campus portal
Research paper repository search
Lecture materials and syllabus search
Architecture Examples:
Campus website crawling
Integration with paper repositories (DSpace, etc.)
Search of materials on Google Drive / SharePoint
Related Features:
IT & Software
Challenge: Source code, documentation, wikis, and ticket management system information are scattered, reducing development efficiency.
Fess Solution:
Code search in GitHub/GitLab repositories
Search of Confluence/Wiki pages
Search of Slack/Teams messages
Developer Features:
Integration with existing systems via Search API
Code highlighting
Filtering by file type
Related Features:
Scale-Based Use Cases
Small Business (up to 100 employees)
Characteristics: Want easy deployment and operation with limited IT resources.
Recommended Configuration:
Easy deployment via Docker Compose
Single server configuration (Fess + OpenSearch)
Required memory: 8GB or more
Deployment Steps:
# Deploy in 5 minutes
mkdir fess && cd fess
curl -OL https://raw.githubusercontent.com/codelibs/docker-fess/master/compose/compose.yaml
curl -OL https://raw.githubusercontent.com/codelibs/docker-fess/master/compose/compose-opensearch3.yaml
docker compose -f compose.yaml -f compose-opensearch3.yaml up -d
Cost:
Software: Free (Open Source)
Server costs only (Cloud or On-premise)
Mid-size Enterprise (100-1000 employees)
Characteristics: Multi-department usage, requires reasonable availability.
Recommended Configuration:
2 Fess servers (redundancy)
3-node OpenSearch cluster
Load balancer for traffic distribution
Active Directory integration
Capacity Guidelines:
Documents: up to 5 million
Concurrent search users: up to 100
Related Features:
Large Enterprise (1000+ employees)
Characteristics: Large-scale data, high availability, strict security requirements.
Recommended Configuration:
Multiple Fess servers (running on Kubernetes)
OpenSearch cluster (dedicated node configuration)
Dedicated crawl servers
Integration with monitoring and log collection infrastructure
Scalability:
Documents: hundreds of millions possible
Horizontal scaling via OpenSearch shard splitting
Enterprise Features:
Department-specific label management
Detailed access logging
Integration with other systems via API
Note
For large-scale deployments, we recommend using Commercial Support.
Technical Use Cases
Internal Wiki / Knowledge Base Search
Overview: Enable cross-search across Confluence, MediaWiki, and internal wikis.
Benefits:
Unified search across multiple wiki systems
Automatic crawling based on update frequency
Wiki page attachments included in search scope
Implementation:
Install Confluence Data Store plugin
Configure connection settings from admin panel
Set crawl schedule (e.g., daily)
File Server Unified Search
Overview: Search documents on Windows file servers and NAS.
Supported Protocols:
SMB/CIFS (Windows shared folders)
NFS
Local file system
Security:
NTLM authentication-based access control
File ACLs reflected in search results
Configuration Points:
Create dedicated crawl account
Phased crawling for large file volumes
Consider network bandwidth
Website Search (Site Search)
Overview: Add search functionality to public websites.
Deployment Methods:
JavaScript Embed
Use Fess Site Search (FSS) to add a search box with just a few lines of JavaScript
API Integration
Build custom search UI using the Search API
FSS Example:
<script>
(function() {
var fess = document.createElement('script');
fess.type = 'text/javascript';
fess.async = true;
fess.src = 'https://your-fess-server/js/fess-ss.min.js';
fess.charset = 'utf-8';
fess.setAttribute('id', 'fess-ss');
fess.setAttribute('fess-url', 'https://your-fess-server/json');
document.body.appendChild(fess);
})();
</script>
<fess:search></fess:search>
Database Search
Overview: Make data in RDBs searchable.
Supported Databases:
MySQL / MariaDB
PostgreSQL
Oracle
SQL Server
Use Cases:
Customer master search
Product catalog search
FAQ database search
Implementation:
Configure Database Data Store plugin
Specify crawl target with SQL query
Configure field mapping
Summary
Fess, with its flexible design, can accommodate various industries, scales, and use cases.
For Those Considering Deployment:
First, try Fess with the Quick Start
Check required features in the Documentation
For production deployment, consult Commercial Support
Related Resources:
Article List - Detailed technical articles
Discussion Forum - Community support
GitHub - Source code and issue tracking