Solutions & Deployment

Explore WaddleAI's architecture, deployment scenarios, and integration options. From local development to enterprise-scale production deployments.

How WaddleAI Processes Requests

Interactive dataflow showing how requests move through WaddleAI's architecture

Choose Integration Method

User Input

Authentication & Security

Intelligent Routing

LLM Providers

Response Processing

User Response

VS Code Extension

@waddleai chat participant with context awareness

< 50ms
Avg Latency
100%
Security Scanned
99.9%
Uptime SLA
10K+
Requests/Min

Deployment Architecture Scenarios

Choose your deployment strategy based on scale, complexity, and requirements

WaddleAI Proxy

Management Server

OpenWebUI

PostgreSQL

Redis

Development Setup

Perfect for local development and testing

  • Single-command deployment
  • All services included
  • Easy configuration

Resource Requirements

Minimal hardware requirements

  • 8GB RAM minimum
  • 4 CPU cores
  • 100GB storage

Use Cases

Ideal scenarios for Docker deployment

  • Local development
  • Small team testing
  • Proof of concept

Implementation Guide

Step-by-step guides for each deployment scenario

Docker Compose

Quick start for development and small-scale deployments

1

Clone Repository

git clone https://github.com/penguintechinc/waddleai
2

Configure Environment

cp .env.testing .env
3

Launch Stack

docker-compose -f docker-compose.testing.yml up
What You Get:
  • • WaddleAI Proxy (Port 8000)
  • • Management Portal (Port 8001)
  • • OpenWebUI (Port 3001)
  • • PostgreSQL & Redis

Kubernetes

Production-ready scalable deployment with high availability

1

Setup Cluster

Kubernetes 1.25+ with Ingress controller

2

Deploy Helm Chart

helm install waddleai ./helm/waddleai
3

Configure Auto-scaling

HPA and VPA for dynamic scaling

Production Features:
  • • Auto-scaling (3-10 replicas)
  • • High availability PostgreSQL
  • • Redis clustering
  • • Ingress with SSL termination

Cloud Native

Fully managed enterprise deployment with global scale

1

Contact Sales

Discuss requirements with Penguin Technologies

2

Architecture Design

Custom cloud architecture for your needs

3

Managed Deployment

We handle hosting, monitoring, and maintenance

Enterprise Benefits:
  • • 99.9% uptime SLA
  • • Global CDN deployment
  • • 24/7 monitoring
  • • Automatic disaster recovery

Integration Examples

Real-world examples of WaddleAI integrations across different platforms

VS Code Extension

// Install WaddleAI VS Code Extension
1. Press F5 to launch Extension Development Host
2. Set API key: "WaddleAI: Set API Key"
3. Open Chat panel and type:
@waddleai Help me write a REST API
✓ Context-aware assistance with full workspace info
  • Context-aware code assistance
  • Multi-model support (GPT-4, Claude, LLaMA)
  • Streaming responses in chat

OpenAI API Drop-in

# Python Example
import openai
client = openai.OpenAI(
api_key="wa-your-key",
base_url="http://localhost:8000/v1"
)
# Use exactly like OpenAI API
response = client.chat.completions.create(...)
  • 100% OpenAI API compatible
  • Drop-in replacement for existing code
  • Enhanced security and routing

Ready to Deploy WaddleAI?

Choose the deployment option that fits your needs, from quick Docker setup to enterprise cloud deployment with full management.

Start with DockerView Pricing Plans