Logwell
Self-hosted logging platform with real-time streaming, full-text search, and OTLP-compatible ingestion. Deploy in minutes, own your data.
Ficha actualizada 23 sept 2026, 2:26 · upstream 23 sept 2026, 2:14 · release v1.3.1
Qué es Logwell
Descripción editorial construida a partir del repositorio, su documentación y sus señales de mantenimiento.
Logwell is a lightweight, self-hosted log aggregation platform for developers who want structured logging without the complexity of ELK or the costs of cloud services. It provides real-time streaming via SSE-powered log tailing, full-text search through PostgreSQL with tsvector indexing, and OTLP-native ingestion requiring no proprietary SDKs.
Logwell is designed as a drop-in replacement for popular observability stacks like Loki/Grafana or ELK, offering the same functionality in a single self-hosted instance. It eliminates vendor lock-in by using PostgreSQL as its backend instead of Elasticsearch, reducing infrastructure complexity and costs. The platform supports real-time log streaming with batch processing, provides incident intelligence through error/fatal fingerprinting, and offers complete data ownership with no telemetry or phone-home requirements.
Logwell is particularly well-suited for small to medium-sized applications, startups, and side projects where teams need a simple logging solution without the overhead of distributed tracing, metrics collection, or complex RBAC systems. It also supports zero-configuration deployments via Docker Compose, making it accessible to developers who want to quickly set up their own observability infrastructure.
- Self-hosted log aggregation for small-to-medium applications
- Full-text search across application logs without managing Elasticsearch
- Real-time log streaming during development and debugging
- Incident correlation with error/fatal message fingerprinting
- Zero-configuration deployments via Docker Compose
- Teams requiring complete data ownership without vendor lock-in
- OTLP-native ingestion requires no proprietary SDKs or custom parsers
- PostgreSQL backend with tsvector provides full-text search in a single database
- Real-time streaming via SSE-powered log tailing with automatic batching
- Incident intelligence with error/fatal message correlation and timeline views
- Zero telemetry — fully air-gapped deployments supported without phone-home
- Not designed for high-volume production systems (10k+ logs/second)
- No built-in distributed tracing or metrics collection capabilities
- Limited RBAC and audit trail features compared to enterprise solutions
- Single-instance architecture limits horizontal scaling without external load balancers
- Incident resolution is limited by configurable quiet periods rather than automated alerting
Perfil de infraestructura
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Deploy Logwell using Docker Compose with PostgreSQL, Elasticsearch (optional), and ClickHouse for metrics. Set up a reverse proxy (Nginx) in front of the application to handle TLS termination and API routing. Configure environment variables for database connection strings, authentication secrets, and log retention policies. For production deployments, consider adding rate limiting via Redis or an external service to prevent abuse from automated tools like curl. Use Docker Compose to manage all services including PostgreSQL, Elasticsearch, ClickHouse, the Logwell application itself, and a reverse proxy. Enable SSL/TLS for API endpoints using Let's Encrypt certificates. Configure log rotation and retention policies in .env files. For multi-tenant environments, implement project-level isolation via separate API keys per tenant. Monitor resource usage with Prometheus/Grafana to ensure Postgr
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