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title Fault Tolerance
subtitle Handle failures gracefully with request migration, cancellation, and graceful shutdown

Dynamo provides comprehensive fault tolerance mechanisms to ensure reliable LLM inference in production deployments. This section covers the various strategies and features that enable Dynamo to handle failures gracefully and maintain service availability.

Overview

Fault tolerance in Dynamo operates at multiple levels:

Layer Mechanism Purpose
Request Migration, Cancellation Handle in-flight request failures
Worker Health Checks, Graceful Shutdown Detect and recover from worker failures
System Load Shedding, Request Rejection Prevent system overload
Infrastructure etcd HA, NATS resilience Handle infrastructure component failures

Key Features

Request Migration

When a worker fails during request processing, Dynamo can migrate in-progress requests to healthy workers. The migration system:

  • Preserves partial generation state (accumulated tokens)
  • Transparently continues generation on a new worker
  • Maintains seamless token flow to clients

See Request Migration for details.

Request Cancellation

Dynamo supports canceling in-flight requests to free computational resources:

  • Graceful stop signals for clean termination
  • Kill signals for immediate termination
  • Hierarchical cancellation propagation through request chains

See Request Cancellation for details.

Graceful Shutdown

Workers handle shutdown signals (SIGTERM/SIGINT) gracefully:

  • Immediately stop accepting new requests
  • Optionally drain in-flight requests before terminating
  • Clean up resources (engines, connections, temp files)

See Graceful Shutdown for details.

Request Rejection (Load Shedding)

When workers are overloaded, Dynamo rejects new requests to prevent cascading failures:

  • Configurable busy thresholds based on KV cache utilization
  • Real-time worker load monitoring
  • HTTP 503 responses with retry guidance

See Request Rejection for details.

Health Checks

Dynamo provides multiple health check mechanisms:

  • HTTP Endpoints: /health and /live endpoints for orchestration
  • Canary Health Checks: Active monitoring via periodic test requests
  • Engine Monitoring: Automatic shutdown on engine failure detection

See Health Checks for details.

Configuration Quick Reference

Feature Environment Variable Default
Worker health port DYN_SYSTEM_PORT 9090
Canary health checks DYN_HEALTH_CHECK_ENABLED false (K8s: true)
Canary wait time DYN_CANARY_WAIT_TIME 10 seconds
Health check timeout DYN_HEALTH_CHECK_REQUEST_TIMEOUT 3 seconds
Decode blocks threshold --active-decode-blocks-threshold None (disabled)
Prefill tokens threshold --active-prefill-tokens-threshold None (disabled)

Failure Scenarios and Recovery

Worker Pod Restart

  1. Worker receives SIGTERM from Kubernetes
  2. Endpoints are immediately invalidated (no new requests)
  3. In-flight requests complete or migrate (based on configuration)
  4. Resources are cleaned up
  5. Pod restarts with fresh state

Worker Crash (Unexpected)

  1. etcd lease expires (TTL-based detection)
  2. Client discovers endpoint removal via etcd watch
  3. New requests route to remaining healthy workers
  4. In-flight requests on crashed worker are migrated (if enabled)

Network Partition

  1. Worker loses connectivity to etcd/NATS
  2. Lease keep-alive fails, lease eventually expires
  3. Worker is removed from service discovery
  4. Traffic reroutes to reachable workers

GPU Failure

  1. Engine health check detects GPU error (XID, OOM, etc.)
  2. Worker initiates graceful shutdown
  3. Runtime is shut down, engine cleaned up
  4. Process exits with code 1 for pod restart

Testing Fault Tolerance

Dynamo includes a comprehensive testing framework for validating fault tolerance:

  • Request cancellation tests
  • Migration tests with worker failures
  • etcd HA failover tests
  • Hardware fault injection (GPU XID, network partitions)

See Fault Tolerance Testing for details.

Related Documentation