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The New Stack
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Kubernetes + LLMs: Cast AI Solves the Cost Puzzle
- Cast AI has launched an AI Optimizer service that automatically cuts the cost of deploying large language models (LLMs) by integrating with any OpenAI-compatible API endpoint.
- Cast AI has also launched AI Enabler, which leverages the vendor’s Kubernetes infrastructure optimisation capabilities to intelligently route queries from organisations and DevOps to the most cost-efficient LLM.
- DevOps teams can compare LLMs side-by-side for performance and cost with the Cast AI Playground, another tool from the provider.
- Cast AI is helping developers manage the costs of AI operations with its AI Optimizer and now AI Enabler.
- The costs of running LLMs can grow quickly, with a single instance of an LLM hosting reaching upwards of $20,000 per month.
- MLOps teams responsible for building and maintaining the infrastructure for generative AI workloads struggle to determine the best model for their specific needs.
- Cast AI’s various tools help developers get their arms around the growing number of LLMs and the costs to run them.
- AI Enabler compares LLMs and creates benchmarks, helping developers to optimise performance and cost.
- Cast AI has launched Commercially Supported Container Live Migration, which enables automatic and uninterrupted migration of stateful and uninterruptible workloads in Kubernetes.
- Cast AI is integrating the Container Live Migration feature with its other automation tools, including Bin-Packing and Eviction, Cluster and Node Rebalancing, Spot Fallback, Spot Interruption ML Prediction, and Spot Instance Price Drift Rebalancing.
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