> For clean Markdown content of this page, append .md to this URL. For the complete documentation index, see https://docs.nvidia.com/dynamo/llms.txt. For full content including API reference and SDK examples, see https://docs.nvidia.com/dynamo/llms-full.txt.

# Components

## Docs

- [Frontend](https://docs.nvidia.com/dynamo/v1.3.0/components/frontend.md): API gateway that exposes OpenAI HTTP and KServe gRPC endpoints and handles request preprocessing, routing, and response formatting.
- [Frontend Guide](https://docs.nvidia.com/dynamo/v1.3.0/components/frontend/frontend-guide.md): Configures the KServe gRPC frontend, including supported endpoints, gRPC tuning, and registering OpenAI or tensor-based backends.
- [Frontend Configuration Reference](https://docs.nvidia.com/dynamo/v1.3.0/components/frontend/configuration-reference.md): Complete reference for all frontend CLI arguments, environment variables, and HTTP endpoints
- [Python Route Extensions](https://docs.nvidia.com/dynamo/v1.3.0/components/frontend/python-route-extensions.md)
- [Tokenizer](https://docs.nvidia.com/dynamo/v1.3.0/components/frontend/tokenizer.md): Selects between the default HuggingFace and fastokens tokenizer backends for BPE models served through the Dynamo Frontend.
- [Router](https://docs.nvidia.com/dynamo/v1.3.0/components/router.md): KV cache-aware router that picks workers by combined prefill and decode cost to maximize throughput and minimize latency.
- [Routing Concepts](https://docs.nvidia.com/dynamo/v1.3.0/components/router/routing-concepts.md): Cost model, worker selection, and routing primitives for the Dynamo router
- [Multi-DC KV Routing and the DC Relay](https://docs.nvidia.com/dynamo/v1.3.0/components/router/multi-dc-kv-routing-and-the-dc-relay.md): Aggregate exact KV ownership in each DC and publish compact state to a global consumer
- [Configuration and Tuning](https://docs.nvidia.com/dynamo/v1.3.0/components/router/configuration-and-tuning.md): Router behavior, event transport, load tracking, and tuning guidance
- [Deficit Round Robin Queue Scheduling](https://docs.nvidia.com/dynamo/v1.3.0/components/router/deficit-round-robin-queue-scheduling.md): Weighted arbitration across router policy classes
- [Priority Scheduling](https://docs.nvidia.com/dynamo/v1.3.0/components/router/priority-scheduling.md): Request priority across the Dynamo router and backend engines
- [Disaggregated Serving](https://docs.nvidia.com/dynamo/v1.3.0/components/router/disaggregated-serving.md): Prefill and decode routing with the Dynamo router
- [Topology-Aware KV Transfer](https://docs.nvidia.com/dynamo/v1.3.0/components/router/topology-aware-kv-transfer.md): Runtime metadata and decode routing semantics for topology-aware prefill/decode handoff
- [Router Operations](https://docs.nvidia.com/dynamo/v1.3.0/components/router/router-operations.md): Replica topology, state management, recovery, and remote indexers
- [Router Examples](https://docs.nvidia.com/dynamo/v1.3.0/components/router/router-examples.md): Worked examples for the KvRouter Python API, Kubernetes deployments, and custom routing patterns.
- [Standalone KV Indexer](https://docs.nvidia.com/dynamo/v1.3.0/components/router/standalone-indexer.md): Run the KV cache indexer as an independent HTTP service for querying block state
- [Standalone Selection Service](https://docs.nvidia.com/dynamo/v1.3.0/components/router/standalone-selection-service.md): Select workers and account for reservations without forwarding inference requests
- [Standalone Slot Tracker](https://docs.nvidia.com/dynamo/v1.3.0/components/router/standalone-slot-tracker.md): Run active-request load accounting as an independent HTTP service
- [KV Event Replay — Dynamo vs vLLM](https://docs.nvidia.com/dynamo/v1.3.0/components/router/kv-event-replay-dynamo-vs-v-llm.md): How the two systems handle gap detection, replay, and recovery for KV cache events
- [Planner](https://docs.nvidia.com/dynamo/v1.3.0/components/planner.md): Autoscaler that adjusts prefill and decode replicas using engine performance models and traffic prediction to meet TTFT and ITL SLAs.
- [Planner Guide](https://docs.nvidia.com/dynamo/v1.3.0/components/planner/planner-guide.md): Configures Planner optimization targets, scaling modes, and PlannerConfig fields for production deployments.
- [Global Planner Deployment Guide](https://docs.nvidia.com/dynamo/v1.3.0/components/planner/global-planner-guide.md): Deploys GlobalPlanner as the centralized scaling layer for multi-DGD policy enforcement and single-endpoint multi-pool deployments.
- [Planner Examples](https://docs.nvidia.com/dynamo/v1.3.0/components/planner/planner-examples.md): Examples for custom load predictors and the VirtualConnector for non-Kubernetes scaling environments.
- [Profiler](https://docs.nvidia.com/dynamo/v1.3.0/components/profiler.md): Automated performance analysis that finds optimal prefill and decode parallelism and generates SLA-driven deployment configurations.
- [Profiler Guide](https://docs.nvidia.com/dynamo/v1.3.0/components/profiler/profiler-guide.md): Runs the AI Configurator-driven profiling pipeline that turns a model, SLA targets, and backend into a ready-to-deploy DGD.
- [Profiler Examples](https://docs.nvidia.com/dynamo/v1.3.0/components/profiler/profiler-examples.md): Complete DGDR profiling examples for dense and MoE models across rapid and thorough search strategies.
- [KVBM](https://docs.nvidia.com/dynamo/v1.3.0/components/kvbm.md): Unified memory layer and write-through KV cache spanning GPU, host, SSD, and remote storage via NIXL for TensorRT-LLM and vLLM.