Skip to main content
Fish Audio Enterprise ships as a Helm chart that installs the whole speech stack into a cluster you run. Both Helm profiles use the same chart and the same procedure; they differ only in how usage is accounted.
This page covers what the deployment involves and what you need to decide. The commands, values, and troubleshooting are in the deployment runbook, which ships in the deployment guide download for the chart version you install. See Releases. The runbook is versioned with the chart; this page is not, so follow the runbook when they differ.

​
Choose a billing profile

The bearer-token rules follow the profile: online requests must carry a Fish Audio API key with credit, while offline accepts any stable non-empty token and records it verbatim as the billing identity — the same semantics as the All-in-One’s usage accounting. Both profiles serve model weights from inside the cluster by default. The online profile can point the workers at S3-compatible storage instead — Fish Audio’s hosted bucket or your own; the deployment runbook’s “Model source” section covers the how. The offline profile stays in-cluster, since it runs with no egress. “Offline” means runtime-offline: installation still pulls images and the chart from a registry. For a cluster with no network access at all, see Air-gapped deployments.

​
What gets installed

The chart deploys the edge API, the model API layer, an inference router and worker, a vocoder, a text normalizer, the model warehouse that serves the weights when you use the default in-cluster model source, and Redis. Everything lands in one namespace, in the single-worker shape the delivery was sized against. Ingress and TLS are off by default. Put your own ingress controller or load balancer in front of the edge API service, or enable the chart’s if you want Kubernetes to manage that layer.

​
What you decide before installing

Three Kubernetes Secrets have to exist before the install: registry credentials, the license bundle, and one shared between the in-cluster model store and the workers that read from it (with an external model source, that secret instead carries the real access keys for the storage — the runbook covers it). The license bundle is the certificate and key pair downloaded from Developer → Self Host; the services that enforce it stay down until the Secret exists, and refuse requests once the certificate lapses — renewal is described in Operations. The model-store secret authenticates nothing outside the cluster, so the value is yours to choose. For production, prefer External Secrets, Sealed Secrets, or your cloud secret manager over plain Secrets.

​
What to expect

Image references are pinned in the chart, so you select a version with a Helm argument rather than by editing tags. The first install is slow: the inference worker compiles its GPU graphs and the vocoder builds its inference engine before either becomes ready, which takes far longer than any later rollout. Both artifacts are cached on shared storage, so subsequent starts are quick, as long as that storage persists. Upgrades, rollback, and uninstall are all standard Helm operations. The runbook covers the order to do them in and what to check at each step.

​
Next steps