DevZero vs. Sedai
Overview#
DevZero and Sedai both aim to optimize cloud infrastructure costs, but they take different approaches and specialize in different areas.
How They Compare#
| Feature | DevZero | Sedai |
|---|---|---|
| Primary Focus | Kubernetes-native cost optimization | Broad cloud resource optimization |
| Optimization Approach | Live rightsizing with CRIU migration | AI-driven autonomous optimization |
| Pod Restarts Required | No — zero-downtime migration | Varies by optimization type |
| GPU Optimization | Full GPU support (MIG, checkpoint/restore) | Limited GPU support |
| Kubernetes Depth | Deep Kubernetes-native with bin packing | Kubernetes + serverless + VMs |
| Autoscaling | Predictive ML-based scaling | Autonomous scaling with guardrails |
| Cloud Support | AWS, Azure, GCP | AWS, Azure, GCP |
| Typical Savings | 40-80% on Kubernetes workloads | 20-40% across cloud resources |
Key Differences#
Kubernetes-Native vs. Broad Cloud#
DevZero is purpose-built for Kubernetes optimization, providing deep integration with Kubernetes primitives like resource requests, limits, QoS classes, and node scheduling. Sedai takes a broader approach, optimizing across serverless, VMs, and containers, which means less depth in any single area.
Zero-Downtime Optimization#
DevZero's CRIU-based live migration technology allows resource adjustments without pod restarts. This is critical for stateful workloads like databases, caches, and long-running ML training jobs where restarts cause significant disruption and cost.
GPU-First Approach#
DevZero provides dedicated GPU optimization including NVIDIA Multi-Instance GPU (MIG) partitioning, checkpoint/restore for training on spot instances, and GPU-aware scheduling. This is essential for organizations running AI/ML workloads where GPU costs dominate cloud spend.
Depth of Kubernetes Optimization#
DevZero provides intelligent bin packing, workload-aware scheduling, and live consolidation that goes beyond what general-purpose optimization platforms offer. This Kubernetes-native approach enables deeper savings.
When to Choose DevZero#
- Your primary cost driver is Kubernetes infrastructure
- You run GPU-intensive AI/ML workloads
- You need zero-downtime optimization for production
- You want the deepest possible Kubernetes cost reduction
When to Choose Sedai#
- You need to optimize across multiple cloud service types (serverless, VMs, containers)
- Your optimization needs span beyond Kubernetes
- You want a single platform for all cloud resources
Get Started#
Try DevZero free and see your Kubernetes savings potential within 24 hours.