MLOps Platform
The main features of hydrospheredata/hydro-serving are: Model Serving.
Open-source alternatives to hydrospheredata/hydro-serving include: bentoml/bentoml — BentoML is a machine learning model serving framework and GPU-accelerated inference server designed to package,… bentoml/openllm — OpenLLM is a framework for deploying, managing, and scaling open-source large language models. ebhy/budgetml — Deploy a ML inference service on a budget in less than 10 lines of code. ggerganov/llama.cpp — llama.cpp is a high-performance C++ inference engine and runtime for executing large language models locally across… gojek/merlin — Kubernetes-friendly ML model management, deployment, and serving. apache/predictionio — PredictionIO is a machine learning server designed for the deployment of predictive models to transform raw data into…
BentoML is a machine learning model serving framework and GPU-accelerated inference server designed to package, deploy, and scale AI models as production-ready REST APIs. It functions as an AI model lifecycle manager and an inference graph orchestrator, enabling the chaining of multiple models and custom logic into complex pipelines for advanced task sequences. The framework distinguishes itself through a dynamic batching engine that optimizes GPU throughput and an artifact-based packaging system that bundles model weights and dependencies into immutable archives for consistent deployment. It
OpenLLM is a framework for deploying, managing, and scaling open-source large language models
Deploy a ML inference service on a budget in less than 10 lines of code.
PredictionIO is a machine learning server designed for the deployment of predictive models to transform raw data into actionable predictions. It manages the full lifecycle of machine learning operations, from ingesting event data via APIs to hosting production-ready predictive services for real-time inference. The system supports distributed model training by spreading computational workloads across a cluster of nodes to increase processing speed. It enables the implementation of custom prediction engines using programming languages or the application of pre-built model templates for common t