Imported from jeremylongshore/tons-of-skills-marketplace (plugins/saas-packs/palantir-pack/skills/palantir-deploy-integration/SKILL.md). Install upstream with npx skills add jeremylongshore/tons-of-skills-marketplace --skill palantir-deploy-integration. Copyright stays with the author (MIT).

Palantir Deploy Integration

Overview

Deploy Foundry-integrated applications to cloud platforms (GCP Cloud Run, AWS Lambda, Docker) with proper secrets management and health checks.

Prerequisites

• Passing CI tests: palantir-ci-integration
• Production OAuth2 credentials from Developer Console
• Cloud platform CLI configured (gcloud, aws, etc.)

Instructions

Step 1: Dockerfile

FROM python:3.11-slim
WORKDIR /app
COPY requirements.txt .
RUN pip install --no-cache-dir -r requirements.txt
COPY src/ ./src/
EXPOSE 8080
CMD ["uvicorn", "src.main:app", "--host", "0.0.0.0", "--port", "8080"]

Step 2: Deploy to Google Cloud Run

set -euo pipefail
PROJECT_ID=$(gcloud config get-value project)
SERVICE_NAME="foundry-integration"
REGION="us-central1"

# Build and push container
gcloud builds submit --tag "gcr.io/$PROJECT_ID/$SERVICE_NAME"

# Deploy with secrets from Secret Manager
gcloud run deploy "$SERVICE_NAME" \
  --image "gcr.io/$PROJECT_ID/$SERVICE_NAME" \
  --region "$REGION" \
  --set-secrets "FOUNDRY_HOSTNAME=foundry-hostname:latest" \
  --set-secrets "FOUNDRY_CLIENT_ID=foundry-client-id:latest" \
  --set-secrets "FOUNDRY_CLIENT_SECRET=foundry-client-secret:latest" \
  --min-instances 1 \
  --max-instances 10 \
  --timeout 60 \
  --allow-unauthenticated

Step 3: Health Check Endpoint

# src/main.py
from fastapi import FastAPI
import foundry, os

app = FastAPI()

@app.get("/health")
async def health():
    try:
        client = get_foundry_client()
        list(client.ontologies.Ontology.list())
        return {"status": "healthy", "foundry": "connected"}
    except Exception as e:
        return {"status": "degraded", "foundry": str(e)}, 503

Step 4: Environment-Specific Configuration

# src/config.py
import os
from dataclasses import dataclass

@dataclass
class FoundryConfig:
    hostname: str
    client_id: str
    client_secret: str
    scopes: list[str]

    @classmethod
    def from_env(cls) -> "FoundryConfig":
        env = os.environ.get("ENVIRONMENT", "development")
        scopes_map = {
            "development": ["api:read-data"],
            "staging": ["api:read-data", "api:write-data"],
            "production": ["api:read-data", "api:write-data", "api:ontology-read"],
        }
        return cls(
            hostname=os.environ["FOUNDRY_HOSTNAME"],
            client_id=os.environ["FOUNDRY_CLIENT_ID"],
            client_secret=os.environ["FOUNDRY_CLIENT_SECRET"],
            scopes=scopes_map.get(env, ["api:read-data"]),
        )

Output

• Containerized Foundry integration deployed to cloud platform
• Secrets injected via cloud secrets manager
• Health check endpoint verifying Foundry connectivity
• Environment-specific scope configuration

Error Handling

Resources

• Cloud Run Documentation
• Foundry Authentication

Next Steps

For observability setup, see palantir-observability.