Label Studio + PostgreSQL + Redis

intermediate

Data labeling platform with enterprise features for ML training data.

Overview

Label Studio is an open-source data labeling platform developed by Heartex that enables teams to create high-quality training datasets for machine learning projects. Originally launched in 2019, Label Studio has become a leading solution for annotating text, images, audio, video, and time series data, supporting over 20 different ML tasks from text classification to object detection. The platform provides a web-based interface where teams can configure custom labeling templates, manage annotator workflows, and export labeled data in formats compatible with popular ML frameworks like TensorFlow, PyTorch, and scikit-learn. This enterprise-grade stack combines Label Studio with PostgreSQL for robust data persistence and Redis for high-performance caching and session management. PostgreSQL stores all project configurations, user data, annotations, and metadata with ACID compliance, ensuring data integrity even during concurrent labeling sessions. Redis accelerates the platform by caching frequently accessed data, managing real-time collaboration features, and handling background task queues for data import/export operations. NGINX serves as the reverse proxy, efficiently delivering static assets like images and documents while load balancing requests to the Label Studio application server. Data science teams, ML engineers, and organizations building custom AI models should deploy this stack when they need a scalable, production-ready annotation platform. Unlike basic labeling tools, this configuration supports enterprise features like user authentication, project-based access control, annotation quality metrics, and API integrations. The PostgreSQL backend enables complex queries for annotation analytics and audit trails, while Redis ensures responsive performance even with large datasets and multiple concurrent annotators working on the same projects.

Key Features

Multi-format data support with configurable labeling interfaces for text, images, audio, video, HTML, and time series data
PostgreSQL-backed project management with user roles, annotation versioning, and detailed audit trails
Redis-powered real-time collaboration enabling multiple annotators to work simultaneously without conflicts
NGINX-optimized file serving for large media assets with efficient caching and compression
Advanced annotation quality controls including inter-annotator agreement scoring and review workflows
API-first architecture with RESTful endpoints for automated data import, export, and integration with ML pipelines
Flexible labeling templates supporting custom taxonomies, multi-class classification, named entity recognition, and bounding box annotations
Enterprise authentication integration with LDAP, SSO, and role-based access control for secure multi-team environments

Common Use Cases

1Computer vision teams annotating large image datasets for object detection, semantic segmentation, and facial recognition models
2NLP projects requiring text classification, named entity recognition, sentiment analysis, and document categorization
3Healthcare organizations labeling medical images, patient records, and clinical trial data with strict compliance requirements
4Autonomous vehicle companies creating training datasets for road sign detection, lane marking, and obstacle identification
5Content moderation teams at social media platforms labeling text posts, images, and videos for harmful content detection
6Research institutions conducting longitudinal studies requiring consistent data annotation across multiple researchers
7E-commerce companies building recommendation systems by labeling product images, descriptions, and customer review sentiment

Prerequisites

Minimum 2GB RAM (4GB+ recommended) to support PostgreSQL database operations and Label Studio's web interface
Docker Engine 20.10+ and Docker Compose 2.0+ for container orchestration and volume management
Available ports 80, 8080, 5432, and 6379 for NGINX, Label Studio, PostgreSQL, and Redis respectively
Understanding of data annotation workflows and familiarity with ML training data requirements
Basic knowledge of PostgreSQL administration for database maintenance and backup procedures
Storage capacity planning based on dataset size - PostgreSQL data, Redis memory, and Label Studio file storage requirements

For development & testing. Review security settings, change default credentials, and test thoroughly before production use. See Terms

docker-compose.yml

1services: 
2  label-studio: 
3    image: heartexlabs/label-studio:latest
4    environment: 
5      - DJANGO_DB=default
6      - POSTGRE_HOST=postgres
7      - POSTGRE_PORT=5432
8      - POSTGRE_NAME=labelstudio
9      - POSTGRE_USER=${POSTGRES_USER}
10      - POSTGRE_PASSWORD=${POSTGRES_PASSWORD}
11      - REDIS_HOST=redis
12      - REDIS_PORT=6379
13      - LABEL_STUDIO_LOCAL_FILES_SERVING_ENABLED=true
14      - LABEL_STUDIO_LOCAL_FILES_DOCUMENT_ROOT=/label-studio/files
15    volumes: 
16      - ls-data:/label-studio/data
17      - ls-files:/label-studio/files
18    ports: 
19      - "8080:8080"
20    depends_on: 
21      - postgres
22      - redis
23    networks: 
24      - labelstudio-network
25    restart: unless-stopped
26
27  postgres: 
28    image: postgres:15
29    environment: 
30      - POSTGRES_USER=${POSTGRES_USER}
31      - POSTGRES_PASSWORD=${POSTGRES_PASSWORD}
32      - POSTGRES_DB=labelstudio
33    volumes: 
34      - postgres-data:/var/lib/postgresql/data
35    networks: 
36      - labelstudio-network
37    restart: unless-stopped
38
39  redis: 
40    image: redis:alpine
41    volumes: 
42      - redis-data:/data
43    networks: 
44      - labelstudio-network
45    restart: unless-stopped
46
47  nginx: 
48    image: nginx:alpine
49    volumes: 
50      - ./nginx.conf:/etc/nginx/nginx.conf:ro
51      - ls-files:/files:ro
52    ports: 
53      - "80:80"
54    depends_on: 
55      - label-studio
56    networks: 
57      - labelstudio-network
58    restart: unless-stopped
59
60volumes: 
61  ls-data: 
62  ls-files: 
63  postgres-data: 
64  redis-data: 
65
66networks: 
67  labelstudio-network: 
68    driver: bridge

.env Template

.env

1# Label Studio
2POSTGRES_USER=labelstudio
3POSTGRES_PASSWORD=secure_postgres_password
4
5# Create superuser on first run:
6# docker exec -it label-studio label-studio user create

Usage Notes

1Label Studio at http://localhost:8080
2Create first user via signup
3Import data from local files or cloud
4Support for text, image, audio, video
5Export in multiple formats

Individual Services(4 services)

Copy individual services to mix and match with your existing compose files.

label-studio

label-studio:
  image: heartexlabs/label-studio:latest
  environment:
    - DJANGO_DB=default
    - POSTGRE_HOST=postgres
    - POSTGRE_PORT=5432
    - POSTGRE_NAME=labelstudio
    - POSTGRE_USER=${POSTGRES_USER}
    - POSTGRE_PASSWORD=${POSTGRES_PASSWORD}
    - REDIS_HOST=redis
    - REDIS_PORT=6379
    - LABEL_STUDIO_LOCAL_FILES_SERVING_ENABLED=true
    - LABEL_STUDIO_LOCAL_FILES_DOCUMENT_ROOT=/label-studio/files
  volumes:
    - ls-data:/label-studio/data
    - ls-files:/label-studio/files
  ports:
    - "8080:8080"
  depends_on:
    - postgres
    - redis
  networks:
    - labelstudio-network
  restart: unless-stopped

postgres

postgres:
  image: postgres:15
  environment:
    - POSTGRES_USER=${POSTGRES_USER}
    - POSTGRES_PASSWORD=${POSTGRES_PASSWORD}
    - POSTGRES_DB=labelstudio
  volumes:
    - postgres-data:/var/lib/postgresql/data
  networks:
    - labelstudio-network
  restart: unless-stopped

redis

redis:
  image: redis:alpine
  volumes:
    - redis-data:/data
  networks:
    - labelstudio-network
  restart: unless-stopped

nginx

nginx:
  image: nginx:alpine
  volumes:
    - ./nginx.conf:/etc/nginx/nginx.conf:ro
    - ls-files:/files:ro
  ports:
    - "80:80"
  depends_on:
    - label-studio
  networks:
    - labelstudio-network
  restart: unless-stopped

Quick Start

terminal

1# 1. Create the compose file
2cat > docker-compose.yml << 'EOF'
3services:
4  label-studio:
5    image: heartexlabs/label-studio:latest
6    environment:
7      - DJANGO_DB=default
8      - POSTGRE_HOST=postgres
9      - POSTGRE_PORT=5432
10      - POSTGRE_NAME=labelstudio
11      - POSTGRE_USER=${POSTGRES_USER}
12      - POSTGRE_PASSWORD=${POSTGRES_PASSWORD}
13      - REDIS_HOST=redis
14      - REDIS_PORT=6379
15      - LABEL_STUDIO_LOCAL_FILES_SERVING_ENABLED=true
16      - LABEL_STUDIO_LOCAL_FILES_DOCUMENT_ROOT=/label-studio/files
17    volumes:
18      - ls-data:/label-studio/data
19      - ls-files:/label-studio/files
20    ports:
21      - "8080:8080"
22    depends_on:
23      - postgres
24      - redis
25    networks:
26      - labelstudio-network
27    restart: unless-stopped
28
29  postgres:
30    image: postgres:15
31    environment:
32      - POSTGRES_USER=${POSTGRES_USER}
33      - POSTGRES_PASSWORD=${POSTGRES_PASSWORD}
34      - POSTGRES_DB=labelstudio
35    volumes:
36      - postgres-data:/var/lib/postgresql/data
37    networks:
38      - labelstudio-network
39    restart: unless-stopped
40
41  redis:
42    image: redis:alpine
43    volumes:
44      - redis-data:/data
45    networks:
46      - labelstudio-network
47    restart: unless-stopped
48
49  nginx:
50    image: nginx:alpine
51    volumes:
52      - ./nginx.conf:/etc/nginx/nginx.conf:ro
53      - ls-files:/files:ro
54    ports:
55      - "80:80"
56    depends_on:
57      - label-studio
58    networks:
59      - labelstudio-network
60    restart: unless-stopped
61
62volumes:
63  ls-data:
64  ls-files:
65  postgres-data:
66  redis-data:
67
68networks:
69  labelstudio-network:
70    driver: bridge
71EOF
72
73# 2. Create the .env file
74cat > .env << 'EOF'
75# Label Studio
76POSTGRES_USER=labelstudio
77POSTGRES_PASSWORD=secure_postgres_password
78
79# Create superuser on first run:
80# docker exec -it label-studio label-studio user create
81EOF
82
83# 3. Start the services
84docker compose up -d
85
86# 4. View logs
87docker compose logs -f

One-Liner

Run this command to download and set up the recipe in one step:

terminal

1curl -fsSL https://docker.recipes/api/recipes/label-studio-enterprise/run | bash

Troubleshooting

Label Studio shows 'Database connection failed': Check POSTGRES_USER and POSTGRES_PASSWORD environment variables match between services
Redis connection timeout errors: Increase Redis memory limit or check if Redis container has sufficient RAM allocation
File upload failures with large media assets: Configure NGINX client_max_body_size and Label Studio's LABEL_STUDIO_LOCAL_FILES_SERVING_ENABLED setting
PostgreSQL 'too many connections' error: Adjust max_connections in PostgreSQL config or implement connection pooling in Label Studio
Slow annotation interface loading: Verify Redis is properly connected and consider increasing Redis memory or using Redis persistence
NGINX 502 Bad Gateway errors: Ensure Label Studio container is fully started before NGINX attempts to proxy requests

Community Notes

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