PanaAI AI Platform

PanaAI AI Platform has powerful cluster management capabilities, offers various services to customers while efficiently using & scaling the GPU infrastructure from management system.

infrastructure manage

PannaAI AI Platform utilizes the power of containers and Kubernetes to manage AI infrastructure.

  • Effectively manage server hardware, including CPUs, memory modules, and GPUs, providing high-performance, energy-efficient, and scalable services.
  • Administer network devices such as switches, routers, and network interfaces, creating a robust and reliable network infrastructure to enable rapid data transfer and efficient communication between servers and devices.
  • Oversee storage solutions, including hard drives, solid-state drives (SSDs), and Storage Area Networks (SANs), which are critical for data retention and retrieval, meeting the growing demands of data storage.

AI Bare Metal, Orchestration, and Virtualization

  • PanaAI AI platform leverages Kubernetes to orchestrate a resilient and auto-scaling platform with containerized workloads. By utilizing Kubernetes’ auto-scaling capabilities, GPU cloud resources are managed effectively to ensure optimal performance and resource utilization.
  • Provides server virtualization solutions that allow organizations to run multiple virtual servers on a single physical server: this consolidation reduces hardware costs, minimizes power consumption, and optimizes server utilization, leading to significant cost savings and improved efficiency.
  • Streamline provisioning, scaling, and monitoring of virtualized resources: these tools help organizations effectively manage their virtualized environments and adapt to evolving needs.

AI MLOps Platform Management System

  • PanaAI AI platform management allows building, training, and deploying models while running MLOps without the need to spend effort and resources on managing GPU cloud infrastructure. This unified system manages multiple cloud resources, data sources, system performance, logs, policies, and other business functions.
  • Through monitoring and analytics, it provides real-time insights into data center performance, supporting proactive issue identification, capacity planning, and predictive maintenance, ensuring the data center operates at maximum efficien.

LLM Deployment and Optimization

PanaAI AI platform supports the deployment and optimization of large language models (LLMs) to meet business requirements and deliver the greatest competitive advantage to customers.

  • Depending on the model complexity and scale, suitable servers or clusters are provided with adequate computational power and storage capacity.
  • The platform includes monitoring and log analysis systems to track model status and performance metrics in real-time, allowing for prompt issue detection and resolution.
  • Enhanced data security and privacy measures ensure that sensitive information is protected from leakage or misuse.
  • Auto-scaling and self-healing capabilities are used to respond to traffic fluctuations and errors, ensuring minimal downtime.

cloud management tools

Configuration automation tools could offer these benefits:

  • Flexibility and agility
  • Easy to use, adapt, expand
  • Stable,  widely used
  • Enable continuous integration, continuous updates
  • Cost effective

PanaAI AI platform offers comprehensive lifecycle maintenance, precise fault diagnosis, and advanced energy management, supporting advanced applications such as large language models, real-time analytics, and scientific simulations.

Asset Management

Monitor resources through automated discovery, inventory, and asset maintenance.

Intelligent Diagnostics

Leverage an extensive server fault diagnosis library to enable automated fault detection and resolution, along with automated analysis of monitoring metrics. This approach ensures equipment stability while reducing manual maintenance efforts.

Unified Control

Centralized management of multiple compute nodes and network topology, utilizing advanced energy monitoring systems and power control strategies to minimize energy consumption.