# Tensormesh Platform Documentation - [Welcome to Tensormesh Platform](https://docs.tensormesh.ai/introduction.md): Self-hosted KV caching for your vLLM fleet on Kubernetes. - [Getting Started](https://docs.tensormesh.ai/installation/getting-started.md): Pick an install method for Tensormesh Platform and verify your cluster is ready. - [Compatibility Matrix / Supported Models](https://docs.tensormesh.ai/installation/compatibility.md): Models, serving engines, cache features, and recovery scenarios supported on the latest Tensormesh release — and the exact versions to deploy. - [Install with Helm](https://docs.tensormesh.ai/installation/helm.md): Install Tensormesh Platform from the official Helm chart. - [E2E Quickstart](https://docs.tensormesh.ai/installation/example.md): Install the operator, point vLLM at the engine, run an inference, and verify the KV cache is reused. - [Modify an Existing vLLM Deployment](https://docs.tensormesh.ai/installation/existing-deployment.md): Patch an existing vLLM deployment to consume the LMCache engine created by the Tensormesh Operator. - [Troubleshooting](https://docs.tensormesh.ai/installation/troubleshooting.md): Diagnose common install and day-2 issues with Tensormesh Platform. - [CPU Offloading](https://docs.tensormesh.ai/configuration/cpu-offloading.md): Offload KV cache from GPU memory into host DRAM — the default cache tier. - [External Storage Offloading](https://docs.tensormesh.ai/configuration/filesystem-offloading.md): Use a filesystem-backed L2 cache with Tensormesh Platform by mounting storage into the engine pod and configuring the raw L2 adapter. - [Non-Prefix KV Caching](https://docs.tensormesh.ai/configuration/cacheblend.md): Reuse KV cache beyond prefix boundaries with CacheBlend - [KVCache Encryption](https://docs.tensormesh.ai/configuration/kvcache-encryption.md): Encrypt KV cache bytes at rest in the L2 tier with aesgcm, using a master key you provide as a Kubernetes Secret. - [Peer-to-Peer KV Transfer](https://docs.tensormesh.ai/configuration/p2p.md): Enable direct KV cache transfer between engine pods so warm prefixes can be read from any peer in the fleet, not just the local L1 or a shared L2 backend. - [PD Disaggregation](https://docs.tensormesh.ai/configuration/pd-disaggregation.md): Separate the prefill and decode phases onto dedicated vLLM instances to improve TTFT and GPU utilization at scale. - [Multi-Tenancy](https://docs.tensormesh.ai/management/multi-tenancy.md): Isolate cache reuse and capacity across tenants, users, and environments with cache_salt and per-tenant quotas. - [Observability](https://docs.tensormesh.ai/observability.md): Export LMCache engine metrics and traces via an OpenTelemetry Collector — to in-cluster Prometheus/Tempo or an external backend. - [Metrics](https://docs.tensormesh.ai/observability/metrics.md): The cache-engine metrics the operator exposes, and how to read the ones that matter. - [CLI](https://docs.tensormesh.ai/reference/cli.md): The Tensormesh Platform CLI for observing and operating LMCacheEngine fleets on Kubernetes. - [NVIDIA Dynamo](https://docs.tensormesh.ai/integrations/dynamo.md): Offload KV cache from Dynamo vLLM workers to the Tensormesh engine over cross-pod CUDA IPC. - [Overview](https://docs.tensormesh.ai/ui/introduction.md): The Tensormesh Operator UI — a dashboard for your cache fleets: health, capacity, and GPU visibility. - [Installation](https://docs.tensormesh.ai/ui/installation.md): Install the Operator UI into your cluster, next to the operator. - [Configuration](https://docs.tensormesh.ai/ui/configuration.md): Connect metric history, GPU telemetry, and additional clusters; the rest needs no setup. - [Access & Security](https://docs.tensormesh.ai/ui/access-and-security.md): Who can reach the dashboard, how to put SSO in front of it, and why it's safe to run in production. - [Monitoring Your Fleet](https://docs.tensormesh.ai/ui/monitoring-your-fleet.md): Overview, Fleet Map, Metrics, Health, and Thresholds — what each screen shows and when to use it. - [Thresholds & Notifications](https://docs.tensormesh.ai/ui/thresholds-and-notifications.md): Decide what counts as a problem, and get notified the moment it happens. - [Troubleshooting & FAQ](https://docs.tensormesh.ai/ui/troubleshooting.md): Common setup problems and short answers to frequent questions. - [Architecture](https://docs.tensormesh.ai/reference/architecture.md) - [Configuration](https://docs.tensormesh.ai/reference/configuration.md): Every values.yaml key for the Tensormesh Platform Helm chart, plus ready-to-use example overlays. - [Glossary / Vocabulary](https://docs.tensormesh.ai/reference/glossary.md): Plain-language definitions of the terms used throughout the Tensormesh Platform docs.