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Capsule Service

A Capsule Service is a small, self-contained service unit that exposes a standard runtime governance surface — registration, heartbeat, health, configuration, actions, and audit — without becoming a heavyweight platform citizen.

一个 Capsule Service 是轻量、自治、可注册、可观测、可配置、可操作、可审计的小型服务单元。

What a Capsule Service is

  • Registerable — announces itself to a control plane (Opstage) and gets a stable identity.
  • Observable — reports health, version, and runtime metadata on a regular cadence.
  • Configurable — declares what configuration it exposes; configuration changes are observable to operators.
  • Operable — declares actions that operators can trigger from the control plane.
  • Auditable — every meaningful event becomes an audit record.

Why "Capsule" instead of "Microservice"?

Most "services" in an AI product are not classic microservices. They are short-lived workers, automation scripts, API bridges, per-account or per-session runtimes, or experimental connectors. They are too small for a full service mesh, but too important to leave unmanaged.

Capsule Services are designed to fill that gap.

DimensionMicroserviceCapsule Service
Primary goalBusiness domain decompositionLightweight capability governance
RuntimeLong-running serviceService / worker / connector / agent runtime
ManagementService mesh / platform engineeringAgent-based runtime governance
Typical stackJava/Spring, Go, NodeNode, Python, Java, scripts, workers
DeploymentCluster-managedAnywhere with outbound network
IdentityCluster service accountAgent token issued by Opstage

Why the AI era produces many Capsule Services

AI products tend to multiply small, specialized runtimes:

  • Integration adapters translating between vendor APIs and your internal contracts;
  • Playwright workers that drive a browser session per task;
  • Account pools that own a credential, a cookie jar, or an OTP reader;
  • AI Agent runtimes — long-lived loops that need observable state and safe operator controls;
  • Proxy checkers, scrapers, OCR workers, LLM tool runtimes, scheduled jobs.

A typical AI product ends up with dozens of these. Each is too small to deserve its own admin panel, but the fleet as a whole needs one.

Typical examples

  • Integration service — fronts an external API with a stable internal contract
  • Playwright Worker — runs a browser session, often with credentials
  • Account Pool — owns and rotates accounts/cookies
  • Session Pool — owns long-lived authenticated sessions
  • AI Agent Runtime — runs an autonomous loop with tools
  • OTP Reader — reads one-time passwords from inboxes
  • Proxy Checker — verifies and curates outbound proxies

Minimum requirements to be a Capsule Service

To be governed by Opstage, a service must:

  1. Embed (or sit behind) an Agent that can speak the Capsule Management Contract.
  2. Have a stable code and a manifest (name, version, description, declared actions).
  3. Expose a health probe — even a synchronous "I'm alive" suffices.
  4. Optionally declare configuration sources and actions.

That's it. There is no requirement to use a specific framework, runtime, or deployment model.

What a Capsule Service is not

  • It is not a microservice with a different name.
  • It is not required to be stateless.
  • It is not required to be HTTP-facing.
  • It is not required to be containerized.

→ Continue with Opstage and Agent.

Code and docs released under Apache-2.0. "Xtrape", "Xtrape Capsule", and "Opstage" are trademarks of their respective owners.