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name: orchestration-and-deployment description: "Build and route Jina Flow and Gateway topologies, multi-Executor deployments, readiness checks, and export commands." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

Orchestration and Deployment

Use this sub-skill when a task involves Flow, multiple Deployments, Gateway configuration, replicas/shards, YAML topologies, readiness/profiling, or static exports to Docker Compose/Kubernetes/schema artifacts.

Read first

• Flow and Gateway reference for topology, protocol, and Gateway routing behavior.
• YAML and export reference for load_config, save_config, variables, schema/export commands, and deployment materialization.
• Troubleshooting for startup, readiness, multiprocess, protocol, export, and local-vs-production topology issues.
• Use create_minimal_flow_project.py to create a tiny local Flow project from scratch.
• Use validate_flow_yaml.py to statically inspect a Flow/Deployment YAML file.

Quick example

from jina import Flow, Executor, requests
from docarray import BaseDoc, DocList

class InputDoc(BaseDoc):
    text: str = ""

class EchoExecutor(Executor):
    @requests(on="/echo")
    def echo(self, docs: DocList[InputDoc], **kwargs) -> DocList[InputDoc]:
        for doc in docs:
            doc.text = f"echo:{doc.text}"
        return docs

flow = Flow(protocol="grpc", port=12345).add(uses=EchoExecutor)
with flow:
    flow.block()

Boundaries

• Use this sub-skill for topology and deployment graphs. Use executor-service-patterns for service logic inside a single Executor.
• Use client-and-protocols for caller-side request semantics.
• Use observability-and-production for Docker Compose, Kubernetes, JCloud, Hub, and production observability operations that go beyond static export.