How do I configure LlamaIndex for high availability?

To configure LlamaIndex for high availability, focus on redundancy, load balancing, and fault tolerance. Start by deploying multiple instances of LlamaIndex services across separate servers or cloud availability zones. Use orchestration tools like Kubernetes or Docker Swarm to manage these instances, ensuring automatic restarts if a node fails. Pair this with a load balancer (e.g., Nginx or HAProxy) to distribute incoming requests evenly, preventing overload on any single instance. For stateful components like metadata databases, use a replicated database such as PostgreSQL with streaming replication or a managed service like Amazon RDS Multi-AZ. This ensures data remains accessible even if a database node fails.

Next, implement fault tolerance at the application layer. Design your LlamaIndex integration to handle transient failures by adding retries for API calls to external services (e.g., LLM APIs or vector databases). Use libraries like Tenacity in Python to automate retries with exponential backoff. Incorporate health checks into your LlamaIndex services to allow load balancers to detect and route traffic away from unhealthy instances. For example, create an endpoint that verifies connectivity to dependent services like storage or databases. Additionally, configure LlamaIndex to persist indexes in redundant storage, such as a distributed filesystem (e.g., Amazon S3, Google Cloud Storage) or a distributed cache like Redis. This ensures index data survives node failures and remains accessible to all instances.

Finally, set up monitoring and automated recovery. Use tools like Prometheus and Grafana to track metrics such as request latency, error rates, and node health. Configure alerts to notify your team when thresholds are breached (e.g., high error rates or degraded storage performance). For automated recovery, leverage cloud provider features like AWS Auto Scaling Groups or Kubernetes Horizontal Pod Autoscaling to replace failed nodes without manual intervention. Regularly test your setup by simulating failures (e.g., shutting down nodes or disconnecting databases) to validate redundancy and recovery processes. For example, use chaos engineering tools like Chaos Monkey to terminate instances randomly and ensure the system rebalances traffic and restarts services as expected.