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 delivery forms 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 documentation bundle alongside 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 delivery form

Both forms serve model weights from inside the cluster, so neither reaches an external object store at runtime. “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, 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, a JWT secret for the edge API, and one shared between the in-cluster model store and the workers that read from it — that one authenticates nothing outside the cluster, and the value is yours to choose. Generate the JWT secret once and keep it stable — changing it invalidates issued tokens. 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