Product Overview
With Qwak Serving, you can deploy scalable models to production with just one click, reducing the barriers between data science and engineering teams.
Qwak Serving enables teams to deliver prediction services in a fast, repeatable, and scalable manner, complete with advanced metrics, logging, and alerting capabilities.
Qwak Serving enables teams to deliver prediction services in a fast, repeatable, and scalable manner, complete with advanced metrics, logging, and alerting capabilities.
Main Benefits
One click deployment
Easily deploy models using the Qwak UI, CLI, or SDK.
Auto scaling
Qwak Serving automatically scales deployed models based on predefined metrics.
Observability
Easily track the metrics, logs, and performance of your models in one place with Qwak Serving.
Getting Started
Deploy a Qwak build using any of the mentioned modes using Qwak CLI, management application, or Python SDK.
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Qwak Serving Use Cases
Batch inference
Deploy your models as batch inference jobs when you need to generate many predictions at once using scalable compute resources.
Real-time inference
Use Qwak Serving to deploy your models as real-time endpoints and generate predictions on a single observation at runtime.
Streaming inference
Use Qwak Serving to deploy your model as a streaming application and trigger it in an asynchronous manner or on an existing stream of data.
