Comparison / Sagemaker
Deploy Smarter
Scale Freely
Seldon Core 2 is a modular, data-centric framework that gets models into production at scale. Designed to work stand-alone or complement SageMaker, Seldon fills common innovation gaps to help teams move faster with confidence.
At a Glance
Sagemaker
Seldon
Startup Performance
Notebooks take ~5 minutes to start; JupyterLab Spaces up to 30 minutes. Cold starts interrupt workflows and slow iteration.
Lightweight architecture with near-instant startup and consistent performance across restarts. Developers stay in flow.
Cost Efficiency
40% higher than EC2 equivalents. Always-on endpoints with no scale-to-zero mean you pay for idle compute.
Scale-to-zero and multi-model serving cut costs dramatically. Transparent pricing with no hidden data or storage fees.
Deployment Flexibility
Fully tied to AWS. Deployments depend on AWS infrastructure and services, limiting portability.
Cloud-agnostic and Kubernetes-native. Deploy across AWS, GCP, Azure, on-premise, or edge, with full portability.
Monitoring & Observability
Basic latency and error metrics only. Logs are fragmented across CloudWatch and lack diagnostic depth.
Centralized monitoring with drift/outlier detection, request tracing, and detailed diagnostics in one unified view.
Experimentation & Model Serving
Static A/B testing with limited routing. No dynamic optimization or automated rollbacks.
Advanced traffic control (multi-armed bandit (MAB), shadow, canary) and rollback automation. Faster, safer experimentation at scale.
Developer Experience
Complex setup with IAM, VPC, and lifecycle scripts. Local mode behaves differently from production.
GitOps-native workflow with true local development and consistent environments. Simple, fast, and intuitive.
Governance & Compliance
Basic registry and versioning. Lacks approval workflows, lineage tracking, and audit trails.
Full governance with version control, approval flows, and enterprise-grade auditability for compliance.
Data Integration
Requires data in S3. Limited connectivity with external warehouses and data lakes.
Direct integration with diverse data sources, no forced data migration or duplication.
Resource Management
Manual scaling and rightsizing. Frequent GPU availability and quota issues.
Automated scaling and optimization across clusters. Multi-cloud fallback ensures availability.
Security & Access Control
Complex IAM setup and shared responsibility confusion. REST-only endpoints.
Simple, unified security model with fine-grained permissions and multi-protocol support (REST, gRPC, GraphQL).
Built for the Future of Machine Learning and AI
With its modular, data-centric design, Seldon Core 2 brings flexibility, standardization, and performance together, empowering businesses to optimize every stage of their ML lifecycle.
Innovate Freely
Freedom to build and deploy ML your way, whether on-prem, in the cloud, or across hybrid stacks.
With support for traditional models, custom runtimes, and GenAI frameworks, Seldon fits your tech, your workflows, and your pace without vendor lock-in.
Learn Once, Apply Everywhere
Scale confidently with a unified deployment process that works across all models, from traditional ML to LLMs.
Seldon eliminates redundant workflows and custom containers, enabling your teams to launch faster, reduce errors, and scale ML consistently.
Zero Guesswork
Get real-time insights into every model, prediction, and data flow no matter how complex your ML architecture.
From centralized metric tracking to step-by-step prediction logs, Seldon empowers you to audit, debug, and optimize with complete transparency.
Efficient by Design
Modular framework scales dynamically with your needs, no overprovisioning, no unused compute.
Features like Multi-Model Serving and Overcommit help you do more with less, cutting infrastructure costs while boosting throughput.
Explore Core 2
Core 2 is a modular framework with a data-centric approach, designed to help businesses harness the growing complexities of real-time deployment and monitoring.
Download Core 2 Product Overview
Core 2 Architecture
Seldon Core 2 leverages a microservices-based architecture with two layers:
Manage inference servers, model loading, versioning, pipeline configurations, running experiments, and operational state to ensure resilience against infrastructure changes
Handle real-time inference requests using REST and gRPC protocols with the Open Inference Protocol (OIP) and are powered by Envoy for intelligent routing
It also enables interoperability and integration with CI/CD and broader experimentation frameworks like MLflow by Databricks and Weights & Biases.
Seldon Ecosystem
The Seldon ecosystem streamlines model deployment, monitoring, and governance for data-critical use cases like fraud detection, search, and personalization.
Good Things Come to Those Who Click
Whether you’re training the next great LLM or keeping an eye on the one already in production, these guides help you build smarter, steadier systems.
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