Elastic Deployment
Overview
Elastic Deployment is a flexible orchestration feature provided by the Yotta SaaS platform that enables users to quickly create, scale, and manage GPU-powered workloads based on custom images. It is designed to deliver elastic scaling, multi-region deployment, and disaster recovery, ensuring that your applications remain highly available, fault-tolerant, and performant.
Key Features
🧩 Custom Image Deployment Launch Pods directly from your own container images to instantly start the computing environment you need.
⚙️ Multi-Worker Deployment Create multiple Worker Instances with a single click to handle high-concurrency or large-scale computational workloads.
🌍 Multi-Region Scheduling Pods can automatically distribute across different Regions, enabling cross-region deployment and improving overall system stability and fault tolerance.
📈 Elastic Scaling Adjust the number of Workers at any time based on workload demand — scale up for high-load periods and scale down to reduce cost.
Typical Use Cases
AI Training & Inference Deploy multiple workers across regions to accelerate distributed AI workloads and improve throughput.
High-Availability Service Deployment Distribute services across multiple regions to eliminate single points of failure.
Data Processing & Computation Dynamically expand worker nodes to support distributed processing and failover resilience.
Core Advantages
🌍 Cross-Region Elastic Distribution Supports multi-region resource scheduling for high availability and global workload balancing.
🛡 Built-In Disaster Recovery Automatically fails over to available regions in case of a regional outage, ensuring continuous business operations.
Summary
Elastic Deployment provides Yotta users with a powerful, flexible way to launch, scale, and manage distributed GPU workloads across multiple regions. Whether for AI model training, inference services, or large-scale data processing, Elastic Deployment ensures performance, reliability, and efficiency at global scale.
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