Platform Engineering and DevEx: Practical Implementation of Self-Hosted Large Language Models
platform engineeringDevExgenerative AILLMproductivityCNCF**Private infrastructure**: Start with on-premises GPU clusters to maintain data control. 2.
**Private infrastructure**: Start with on-premises GPU clusters to maintain data control. 2.
the latter’s capabilities by offering: - **Resource Optimization**: Kubernetes enables efficient utilization
. - **Optimizing hardware utilization**: Abstracting hardware-specific configurations (e.g., GPUs, TPUs
Slice represents a fixed list of devices on a node, including attributes such as vendor, product ID, GPU
federation model allows for seamless integration of heterogeneous clusters, optimizing resource utilization
It integrates with GPU operators to automate resource scheduling, enabling efficient utilization of hybrid
traffic patterns, complicating resource allocation. - **Hardware Heterogeneity**: Diverse GPU types
it provides a robust framework for managing distributed workloads, ensuring efficient resource utilization
face significant bottlenecks, particularly during cold starts, where the time required to initialize GPU
**System Layer**: Hardware resource management ensures optimal utilization of accelerators (GPU/TPU),