Cloudera AI Inference

What it does

Cloudera AI Inference is a service for serving traditional ML models, large language models, and generative AI models in production. It takes in models from development, including those from TensorFlow, PyTorch, Scikit-learn, and Hugging Face Transformers, and exposes them through Open Inference Protocol APIs for traditional ML and an OpenAI-compatible API for LLMs. Its output is online and batch predictions with monitoring of latency, throughput, and resource use.

People use it to move models from development to production, roll out new versions with canary or blue-green patterns, and monitor model quality through metrics such as sentiment, user feedback, and drift. Cloudera states it is powered by NVIDIA NIM microservices, and it can run on Cloudera on cloud across AWS, Azure, and Google Cloud, or on premises behind a firewall.

It suits enterprise teams that need inference across hybrid or multi-cloud environments, especially in regulated sectors such as government, healthcare, and financial services. Access is through Cloudera's product pages, which direct readers to a product tour and documentation; on-premises pricing is by contact sales, and cloud use is billed in Cloudera Compute Units, excluding infrastructure and networking costs. Some features are marked as coming soon.

What it can do

• Deploy models from development to production across on-premises, public cloud, and hybrid environments
• Real-time low-latency predictions and batch processing for larger datasets
• Serve traditional ML models via Open Inference Protocol APIs and LLMs via an OpenAI-compatible API
• Support for TensorFlow, PyTorch, Scikit-learn, and Hugging Face Transformers models
• Incremental rollouts with canary and blue-green deployments (feature coming soon)
• Monitor model metrics such as latency, throughput, resource utilization, sentiment, and drift

Works with

• Cloudera AI Registry for model storage, versioning, and management
• CI/CD pipelines and MLOps tools via open standards (per the page's open APIs feature)

Before you choose

• Cloud pricing is per Cloudera Compute Unit (CCU) and excludes infrastructure, networking, and other cloud provider costs.
• Several features, including authorization, canary and blue-green deployments, A/B testing, and online model management, are marked as coming soon and require contacting Cloudera.

Listed under

• Coding
• Sandboxes and infrastructure
• Enterprise AI
• Hybrid cloud
• Inference
• LLM serving
• MLOps
• Model deployment

Get started

Start with the product tour; documentation is available for implementation guides.

1. Register the model in the Cloudera AI Registry to store, version, and manage it.
2. Deploy the model to a cloud or on-premises environment, set up endpoints, and configure autoscaling.
3. Monitor latency, throughput, resource utilization, and model health to troubleshoot and optimize.

Cloud consumption is billed per CCU, with CCU estimates excluding infrastructure and networking costs. The pricing page does not state a free tier or trial for this product. On-premises pricing is not published.

Source: cloudera.com/products/pricing.html, checked 29 Oct 2026. Prices can change; check before you buy.

Sources for this overview

Product pages, documentation, and pricing checked 29 Oct 2026. Each source supports part of the overview; availability and prices can change.

• Cloudera AI Inference Service: Enterprise AI Inference | Cloudera ↗www.cloudera.com
• Cloudera Platform Pricing | Cloudera ↗www.cloudera.com
• Cloudera for developers | Cloudera ↗www.cloudera.com

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cloudera.com: product, pricing and policy pages

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Last checked 29 Oct 2026. Every field keeps its source and date; unknown means we couldn’t confirm it.