Deployment Overview

Agent Kernel is a multi-cloud AI agent runtime that supports multiple deployment modes across AWS, Azure, and GCP for different use cases.

Deployment Modes

Quick Comparison

Mode	Best For	Scalability	Cold Start	Cost	Fault Tolerance
Local/CLI	Development, testing	N/A	Instant	Free	Manual restart
REST API	Web apps, APIs	Manual scaling	Instant	Server costs	Manual
AWS Lambda	Variable load (AWS)	Auto-scaling	1-3s	Pay per use	High - Auto-retry, multi-AZ
AWS ECS	Consistent load (AWS)	Auto-scaling	Instant	Running containers	Very High - Multi-AZ, auto-recovery
Azure Functions	Variable load (Azure)	Auto-scaling	1-3s	Pay per use	High - Auto-retry, multi-region
Azure Container Apps	Consistent load (Azure)	Auto-scaling	Instant	Running containers	Very High - Multi-zone, auto-recovery
GCP Cloud Run Serverless	Variable load (GCP)	Auto-scaling (scale-to-zero)	1-3s	Pay per use	High - Auto-retry, multi-zone
GCP Cloud Run Containerized	Consistent load (GCP)	Auto-scaling (min≥1)	Instant	Running containers	Very High - Always-on, auto-recovery
MCP Server	AI integrations	Manual	Instant	Server costs	Manual
A2A Server	Agent networks	Manual	Instant	Server costs	Manual

Local Development

Uses agentkernel.CLI module.

python my_agent.py

• Interactive CLI
• Instant feedback
• No deployment needed

Learn more →

REST API Server

Uses agentkernel.RESAPI module.

python my_agent.py

• HTTP endpoints
• Easy integration
• Self-hosted

Learn more →

AWS Serverless

Uses Agent Kernel terraform modules

# Configure the modules and run
terraform init && terraform apply

• Lambda functions
• API Gateway
• Auto-scaling
• Pay per request

Learn more →

AWS Containerized

Uses Agent Kernel terraform modules

# Configure the modules and run
terraform init && terraform apply

• ECS Fargate
• Application Load Balancer
• Consistent performance
• Lower latency

Learn more →

Azure Serverless

Uses Agent Kernel terraform modules

# Configure the modules and run
terraform init && terraform apply

• Azure Functions
• API Management
• Auto-scaling
• Pay per request

Learn more →

Azure Containerized

Uses Agent Kernel terraform modules

# Configure the modules and run
terraform init && terraform apply

• Azure Container Apps
• Azure Front Door / App Gateway
• Consistent performance
• Lower latency

Learn more →

GCP Serverless

Uses Agent Kernel terraform modules

# Configure the modules and run
terraform init && terraform apply

• Cloud Run (scale-to-zero)
• API Gateway
• Auto-scaling
• Pay per request

Learn more →

GCP Containerized

Uses Agent Kernel terraform modules

# Configure the modules and run
terraform init && terraform apply

• Cloud Run (always-on, min_instance_count≥1)
• API Gateway
• Consistent performance
• Lower latency

Learn more →

Choosing a Deployment Mode

Development

→ Local/CLI: Fast iteration, no setup

Small Web App

→ REST API: Simple, self-hosted

Variable Traffic on AWS

→ AWS Lambda: Auto-scales, pay per use

High Traffic on AWS

→ AWS ECS: Consistent performance

Variable Traffic on Azure

→ Azure Functions: Auto-scales, pay per use

High Traffic on Azure

→ Azure Container Apps: Consistent performance, KEDA-based scaling

Variable Traffic on GCP

→ GCP Cloud Run Serverless: Auto-scales to zero, pay per use

High Traffic on GCP

→ GCP Cloud Run Containerized: Consistent performance, no cold starts

AI Integration

→ MCP/A2A: Protocol-based integration

Multi-Cloud Strategy

Agent Kernel's multi-cloud support enables you to:

• Deploy the same agent code to AWS, Azure, or GCP without modification
• Avoid vendor lock-in - switch clouds or run on multiple clouds
• Optimize costs - choose the best pricing model for each workload
• Geographic redundancy - distribute across cloud providers
• Leverage cloud-specific services - use the best of each platform

Fault Tolerance Considerations

Agent Kernel provides different levels of fault tolerance depending on your deployment mode:

Production-Grade Fault Tolerance

AWS ECS/Fargate offers the highest level of fault tolerance on AWS:

• Multi-AZ task distribution for zone-level failures
• Automatic task replacement on failures
• Health check-based routing
• Configurable auto-scaling
• Rolling deployments with zero downtime
• Application Load Balancer with health monitoring

Learn more about AWS ECS fault tolerance →

Azure Container Apps offers the highest level of fault tolerance on Azure:

• Multi-zone replica distribution for zone-level failures
• Automatic replica replacement on failures
• Health check-based routing
• KEDA-based auto-scaling
• Rolling deployments with zero downtime
• Built-in ingress with health monitoring

Learn more about Azure Container Apps fault tolerance →

AWS Lambda provides built-in fault tolerance:

• Serverless architecture with automatic scaling
• Multi-AZ execution by default
• Automatic retry on failures
• No infrastructure management
• Inherently resilient to hardware failures

Learn more about AWS serverless fault tolerance →

Azure Functions provides built-in fault tolerance:

• Serverless architecture with automatic scaling
• Multi-region execution capabilities
• Automatic retry on failures
• No infrastructure management
• Inherently resilient to hardware failures

Learn more about Azure serverless fault tolerance →

GCP Cloud Run Serverless provides built-in fault tolerance:

• Serverless architecture with automatic scaling (scale-to-zero)
• Multi-zone execution by default
• Automatic retry on failures
• No infrastructure management
• Inherently resilient to hardware failures

Learn more about GCP serverless →

GCP Cloud Run Containerized offers high fault tolerance on GCP:

• Always-on instances (min_instance_count≥1) for consistent performance
• Automatic replica replacement on failures
• Multi-zone distribution
• Auto-scaling based on traffic
• No cold starts

Learn more about GCP containerized →

State Persistence

All production deployment modes support resilient state management:

AWS Options:

• DynamoDB: Multi-AZ replication, automatic backups, 99.999% SLA
• Redis: Cluster mode with automatic failover, replication

Azure Options:

• Cosmos DB: Multi-region replication, automatic backups, 99.999% SLA
• Azure Cache for Redis: Cluster mode with automatic failover, replication

GCP Options:

• Firestore: Multi-region replication, automatic backups, 99.999% SLA
• Memorystore Redis: High availability with automatic failover

Learn more about fault tolerance →

Next Steps

• Local Deployment
• AWS Deployments:
  • AWS Serverless
  • AWS Containerized
• Azure Deployments:
  • Azure Serverless
  • Azure Containerized
• GCP Deployments:
  • GCP Serverless
  • GCP Containerized
• Fault Tolerance
• Configuration