Yotta Shakti Cloud: AI Cluster | Manage and Scale AI Workloads with Shakti Clusters

Efficiently Manage and Scale AI Workloads with Shakti Clusters

Streamline Resource Allocation, Optimize Performance, and Scale Seamlessly for Demanding AI Applications.

Overview

Transform Your High-Performance Workloads with Shakti Clusters Powered by Kubernetes/SLURM.

Unmatched GPU Power

Leverage NVIDIA H100 and L40S GPUs for fast deep learning, data analytics, and simulations delivering top performance and results.

Seamless Workload Management

Shakti Clusters support SLURM and Kubernetes for easy orchestration, enabling simplified deployment and scaling with automated resource management.

Scalable and Flexible Deployment

Start with just 2 nodes and scale effortlessly as needed. Shakti Clusters adapt to any workload, offering flexibility for teams of all sizes.

Benefits of Shakti Clusters

Scalable and Flexible Resource Management

Kubernetes auto-scales apps based on traffic, while SLURM manages compute-heavy tasks. Together, they optimize resource use and adapt to changing needs efficiently.

Efficient Job Scheduling and Orchestration

SLURM/Kubernetes ensure that both batch jobs and web traffic are balanced efficiently across the infrastructure, improving performance and reducing downtime.

Cost-Efficient Resource Utilization

Kubernetes and SLURM optimize resource utilization, leading to better efficiency and lower operational costs.

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Product Use Cases

High-Performance Computing (HPC) Workloads

SLURM handles large-scale compute tasks like simulations and data analysis, while Kubernetes adds containerized orchestration and scalability. For example, a research lab can use SLURM for job scheduling and Kubernetes to scale resources as needed.

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Machine Learning and AI Model Training

ML model training demands high compute power. SLURM efficiently schedules GPU-based training tasks, while Kubernetes manages container deployment and scaling. Together, they optimize resource use and speed up large-scale training jobs.

Shakti_Cluster_machine-learning-and-AI-model

Big Data Analytics and Processing

Big data processing needs high compute power and parallel execution. SLURM schedules tasks across clusters, while Kubernetes manages and scales tools like Hadoop and Spark, ensuring efficient, cost-effective processing.

Why Shakti Clusters?

Optimized for Kubernetes and SLURM

With Kubernetes for orchestration and SLURM for HPC, Shakti Clusters offer the best of both worlds—ideal for everything from web apps to AI training and simulations.

Enterprise-Grade Security and Compliance

Shakti Clusters prioritize security with end-to-end encryption, access controls, and compliance with GDPR, HIPAA, and ISO standards—ensuring data protection and enterprise-grade reliability.

Comprehensive Workload Compatibility

Shakti Clusters support diverse workloads like simulations, big data, financial modeling, and AI/ML training—making them ideal for healthcare, finance, manufacturing, and academia.

Pricing

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FAQs

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