# Deployment

# Deployment

This page covers deployment concepts for Curiosity Workspace. The exact deployment model (desktop, VM, containers) may vary, but the production concerns are consistent.

# Deployment goals

• Reliability: predictable uptime and recoverability
• Security: controlled access, hardened configuration, audited operations
• Scalability: handle data growth and query load
• Reproducibility: promote changes from dev → staging → prod safely

# Environments

At minimum, maintain:

• Dev: experimentation and rapid iteration
• Staging: pre-production verification with prod-like config
• Prod: restricted access, controlled changes

# What to version and promote

Treat these as deployable artifacts:

• connector code
• endpoint code
• interface/front-end bundles
• schema migrations and ingestion pipeline changes
• search/index configuration
• NLP pipeline configuration

# Deployment on OpenShift

Curiosity can be deployed on OpenShift using Docker images. To ensure data persistence, it is recommended to use a StatefulSet with attached persistent storage.

1. Prerequisites: A working OpenShift cluster and administrative access.
2. Docker Image: Use the official image from Docker Hub. For production, always use a versioned tag (e.g., curiosityai/curiosity:12345) instead of latest.
3. Storage: Configure a PersistentVolumeClaim (PVC) and attach it to your StatefulSet to maintain workspace state across pod restarts.
4. Configuration: Use environment variables to configure the workspace. Sensitive information like administrator passwords should be stored in OpenShift Secrets.

# Operational checklist (baseline)

• Persistent storage with backups
• TLS termination (directly or via a reverse proxy)
• Secrets in a secret manager
• Monitoring and alerting for:
  • availability
  • ingestion failures
  • index rebuild failures
  • latency spikes

# Next steps

• Observe health and performance: Monitoring
• Set permission boundaries early: Permissions