Principle:OpenHands OpenHands Server Startup
| Knowledge Sources | |
|---|---|
| Domains | Server_Architecture, SaaS_Infrastructure |
| Last Updated | 2026-02-11 21:00 GMT |
Overview
Initializing server infrastructure with health checks, logging, and monitoring during startup ensures the application is fully observable and operationally ready before accepting production traffic.
Description
The Server Startup principle defines the bootstrap sequence that prepares the SaaS server for production operation. This includes configuring structured logging across all application modules, initializing monitoring and metrics collection for session events and agent interactions, setting up health check endpoints that load balancers and orchestrators use to determine readiness, and establishing administrative utilities for email validation and user management. The startup sequence must complete successfully before the server begins accepting external traffic, ensuring that all observability infrastructure is in place to capture the very first request. A failed startup should prevent the server from entering the load balancer rotation, avoiding the scenario where requests are routed to an incompletely initialized instance.
Usage
Apply this principle when deploying a server that requires production-grade observability from the moment it starts serving traffic. The startup sequence should configure logging first (so subsequent initialization steps are logged), then monitoring infrastructure (so metrics capture begins immediately), then health check endpoints (so the orchestrator can detect readiness), and finally any administrative utilities. This ordering ensures that problems during startup are visible in logs and that the server does not advertise readiness prematurely.
Theoretical Basis
The server bootstrap pattern configures observability and readiness probes before accepting traffic, following the principle of defense in depth for operational reliability. Health checks serve as readiness probes in container orchestration platforms (such as Kubernetes), allowing the infrastructure to route traffic only to fully initialized instances. Monitoring listeners implement the observer pattern, subscribing to application events (session starts, agent actions, conversation creation) and forwarding metrics to external monitoring systems without coupling the business logic to any specific metrics backend. Structured logging provides a consistent format for log entries across all modules, enabling centralized log aggregation and search. Together, these components form the observability triad (logs, metrics, health) that enables operators to understand system behavior, detect anomalies, and respond to incidents. The singleton pattern for the monitoring listener ensures a single authoritative instance manages the metrics lifecycle.