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Run Fiddler AI Observability in your preferred cloud environment with native platform integrations. Deploy as a fully managed Partner AI App on AWS SageMaker, run in your Kubernetes clusters, or leverage cloud-native services for ML model monitoring at scale.

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Why Cloud Platform Integrations Matter

Modern AI systems are built on cloud infrastructure. Fiddler’s cloud platform integrations ensure you can:
  • Maintain Data Sovereignty - Keep all your data and models within your existing cloud security boundaries
  • Simplify Procurement - Subscribe through cloud marketplaces with consolidated billing
  • Leverage Existing Infrastructure - Use your current IAM, networking, and security configurations
  • Scale Seamlessly - Cloud-native deployment automatically scales with your ML workloads
  • Reduce Operational Overhead - Managed platform integrations eliminate manual infrastructure management

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AWS Deployments

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AWS SageMaker Partner AI App

Run Fiddler as a fully managed Partner AI App within Amazon SageMaker. Best for: Enterprise AWS customers wanting seamless SageMaker integration with zero external infrastructure Key Features:
  • Fully managed infrastructure within your AWS account
  • Native SageMaker Studio integration
  • No external accounts or data transfer required
  • Automatic updates and maintenance handled by AWS
  • Consolidated AWS billing through Marketplace
Deployment Options:
  • 30-Day Free Trial - Full functionality for up to 5 models (infrastructure costs apply)
  • Tiered Subscriptions - Small, Medium, and Large configurations for different team sizes
  • AWS Marketplace - Monthly or annual subscriptions with flexible pricing
Status: ✓ GA - Production-ready Get Started with AWS SageMaker Partner AI App → Related AWS Integrations:

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Multi-Cloud & Kubernetes

While AWS SageMaker Partner AI App is our featured cloud platform integration, Fiddler supports deployment across multiple cloud providers:

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Supported Deployment Patterns

Cloud Platforms:
  • AWS - Native SageMaker Partner AI App (recommended), EC2, EKS
  • Azure - Azure ML integration (contact sales), AKS deployment
  • Google Cloud - GKE deployment, Vertex AI connectivity
  • Private Cloud - On-premises Kubernetes with cloud connectivity
Kubernetes Deployments:
  • Helm Charts - Production-grade Kubernetes deployment templates
  • Operator Pattern - Automated lifecycle management for Fiddler clusters
  • Multi-Cluster Support - Monitor ML models across distributed Kubernetes environments
  • Cloud-Agnostic - Run on EKS, AKS, GKE, or on-premises Kubernetes
Container Orchestration:
  • Docker Compose - Development and testing environments
  • Docker Swarm - Small-scale production deployments
  • Kubernetes - Enterprise production deployments

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Deployment Architecture Patterns

Use AWS SageMaker Partner AI App for zero-infrastructure management: 
AWS Account (Your VPC)
├── SageMaker Studio (UI Access)
├── Fiddler Partner AI App (Managed)
│   ├── Compute (Managed by AWS)
│   ├── Storage (Your S3 buckets)
│   └── Database (Managed RDS)
└── Your ML Models (SageMaker Endpoints)
Advantages:
  • No operational overhead
  • Automatic scaling and updates
  • AWS handles infrastructure security
  • Seamless Studio integration

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Pattern 2: Self-Managed Kubernetes

Use Helm Charts for full control over infrastructure: 
Cloud Provider (Your Kubernetes Cluster)
├── Fiddler Namespace
│   ├── API Server Pods
│   ├── Worker Pods
│   ├── Database (StatefulSet)
│   └── Storage (PersistentVolumes)
└── Ingress/Load Balancer
Advantages:
  • Full infrastructure control
  • Cloud-agnostic deployment
  • Custom security configurations
  • On-premises compatibility

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Pattern 3: Hybrid Multi-Cloud

Deploy Fiddler in one cloud, monitor models across all: 
Primary Cloud (Fiddler Installation)
├── Fiddler Platform
└── Centralized Monitoring Dashboard

Connected Clouds
├── AWS (SageMaker models)
├── Azure (Azure ML models)
├── GCP (Vertex AI models)
└── On-Premises (Legacy models)
Advantages:
  • Unified observability across clouds
  • Centralized governance and compliance
  • Flexible hybrid architecture

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Getting Started

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For AWS Customers

Quick Start Path:
  1. Subscribe - Get Fiddler from AWS Marketplace
  2. Deploy - Use SageMaker Partner AI Apps one-click deployment
  3. Configure - Run the Quick Setup Script for IAM roles
  4. Monitor - Connect your SageMaker models and LLM applications
Full AWS Deployment Guide → Need Help?

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For Kubernetes Deployments

Prerequisites:
  • Kubernetes 1.21+ cluster
  • Helm 3.8+ installed
  • Storage provisioner (for persistent volumes)
  • Ingress controller (for external access)
Installation: 
# Add Fiddler Helm repository
helm repo add fiddler https://helm.fiddler.ai
helm repo update

# Install Fiddler
helm install fiddler fiddler/fiddler \
  --namespace fiddler \
  --create-namespace \
  --set license.key=<your-license-key> \
  --set ingress.enabled=true \
  --set ingress.hostname=fiddler.your-domain.com
Contact Sales for Kubernetes Deployment →

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For Other Cloud Providers

Azure Customers: Google Cloud Customers:

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Migration & Upgrade Paths

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From Other Monitoring Platforms

Migrating from Competitor Platform:
  1. Parallel Deployment - Run Fiddler alongside existing monitoring
  2. Data Migration - Import historical metrics and model metadata
  3. Gradual Cutover - Model-by-model transition with zero downtime
  4. Training & Onboarding - Dedicated support during migration
Common Migration Sources:
  • Arize - Direct migration tools available
  • Weights & Biases - Model metadata import supported
  • DataRobot - Custom migration scripts available
  • Custom Solutions - API-based migration assistance

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Upgrading Within Fiddler

AWS SageMaker Partner AI App Upgrades:
  • Tier Upgrades - Scale from Small → Medium → Large as needed
  • Version Updates - Automatic updates during maintenance windows
  • Trial to Production - Requires redeployment (preserve data with migration scripts)
Self-Managed Upgrades:
  • Helm Upgrades - Standard helm upgrade process
  • Rolling Updates - Zero-downtime deployments
  • Backup & Restore - Automated backup before each upgrade

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Security & Compliance

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Data Residency

AWS SageMaker Partner AI App:
  • All data stays within your AWS account and region
  • No external data transfer to Fiddler’s infrastructure
  • Choose your preferred AWS region during deployment
Self-Managed Deployments:
  • Full control over data location
  • Support for air-gapped environments
  • On-premises deployment options

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Compliance Certifications

  • SOC 2 Type II - Fiddler platform certified
  • GDPR - Data processing agreements available
  • HIPAA - Compliant deployment options for healthcare
  • FedRAMP - In progress (contact for timeline)

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Security Features

  • Encryption at Rest - All stored data encrypted (AWS KMS, customer-managed keys)
  • Encryption in Transit - TLS 1.3 for all network communication
  • SSO Integration - SAML 2.0, OIDC support (Azure AD, Okta, AWS SSO)
  • RBAC - Role-based access control with fine-grained permissions
  • Audit Logging - Complete audit trail of all platform activities

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Cost Optimization

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AWS SageMaker Partner AI App Pricing

Total Cost of Ownership (TCO):
  • Software License - Billed through AWS Marketplace
  • Infrastructure - AWS resource costs (EC2, RDS, S3, etc.)
  • Data Transfer - Minimal costs (data stays in your VPC)
Tier Selection Guidelines:
Team SizeModels MonitoredRecommended TierEst. Monthly Cost*
< 10 users< 20 modelsSmall500−500 - 1,000
10-50 users20-100 modelsMedium1,500−1,500 - 3,000
50+ users100+ modelsLarge3,000−3,000 - 6,000
*Infrastructure costs only (software license additional) Cost Optimization Tips:
  • Start with Small tier for POCs and development
  • Use Reserved Instances for production workloads (20-40% savings)
  • Right-size tier based on actual usage metrics
  • Scheduled scaling for non-production environments

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Self-Managed Cost Optimization

  • Spot Instances - Use for worker nodes (50-70% savings)
  • Auto-Scaling - Scale compute based on monitoring load
  • Storage Tiering - Move historical data to cheaper storage classes
  • Multi-Tenancy - Share Fiddler instance across multiple teams

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Monitoring Infrastructure Health

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Platform Metrics

AWS SageMaker Partner AI App:
  • View infrastructure health in SageMaker Console
  • CloudWatch metrics for Fiddler components
  • Automatic alerting for platform issues
  • AWS Support for troubleshooting
Self-Managed:
  • Prometheus metrics exported by default
  • Grafana dashboards for infrastructure monitoring
  • Health check endpoints for uptime monitoring
  • Integration with existing observability stack

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Support & Resources

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AWS SageMaker Partner AI App

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Self-Managed Deployments

  • Enterprise Support - 24/7 support with SLA guarantees
  • Deployment Assistance - Professional services for setup
  • Training - Platform administrator training programs
  • Community - Join our Slack community

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Need Help Choosing?

Not sure which deployment option is right for you? We’re here to help:
Featured Integration: The AWS SageMaker Partner AI App is our recommended deployment for AWS customers, offering the fastest time-to-value with zero operational overhead. Learn more →