Autoscaler

The automatic adjustment of computing resources in response to changing workloads to optimize performance, availability, and cost efficiency.

The practice of distributing workloads or requests across multiple computing resources to improve scalability, availability, and resource utilization.

A group of interconnected machines running Kubernetes that work together to deploy, schedule, scale, and manage containerized applications across multiple worker nodes under the control of a centralized control plane.

A virtual or physical compute resource that provides CPU, memory, storage, and networking for running applications and workloads.

A Graphics Processing Unit (GPU) is a specialized parallel processor designed to perform large-scale mathematical computations efficiently, making it the primary hardware for training and running AI models.