Deepgram Deploy Integration

Table of Contents

• Overview
• Prerequisites
• Instructions
• Output
• Error Handling
• Examples
• Resources

Overview

Deploy Deepgram integrations to various cloud platforms and container environments including Docker, Kubernetes, AWS Lambda, Google Cloud Run, and Vercel.

Prerequisites

• Production API key ready
• Infrastructure access configured
• Secret management in place
• Monitoring configured

Instructions

Step 1: Containerize with Docker

Build a multi-stage Dockerfile with non-root user, health checks, and production optimizations.

Step 2: Configure Orchestration

Choose deployment target: Docker Compose (simple), Kubernetes (scale), or serverless (event-driven).

Step 3: Manage Secrets

Use platform-native secret management (K8s Secrets, AWS Secrets Manager, GCP Secret Manager).

Step 4: Set Up Health Checks

Configure liveness and readiness probes against /health endpoint.

Step 5: Configure Auto-scaling

Set up HPA (Kubernetes) or managed scaling with CPU-based thresholds at 70% utilization.

Step 6: Create Deploy Script

Build environment-aware deploy script that runs build, tests, deploys, and smoke tests.

Output

• Dockerfile with multi-stage build and health checks
• Docker Compose or Kubernetes manifests
• Serverless configuration (Lambda/Cloud Run/Vercel)
• Deploy script with environment selection
• Auto-scaling configuration

Error Handling

Examples

Quick Docker Build & Run

set -euo pipefail
docker build -t deepgram-service .
docker run -p 3000:3000 -e DEEPGRAM_API_KEY=$DEEPGRAM_API_KEY deepgram-service  # 3000: 3 seconds in ms

Deploy Script Usage

./scripts/deploy.sh staging    # Deploy to staging
./scripts/deploy.sh production # Deploy to production

See detailed implementation for advanced patterns.

Resources

• Docker Best Practices
• Kubernetes Deployments
• AWS Lambda with Node.js
• Google Cloud Run