Qwak Architecture

Overview

With Qwak, you can deploy and iterate on your machine learning models faster, gain control and visibility of your production machine learning environment, and ensure the privacy and security of your data and models.

Qwak offers multiple deployment options to suit your business needs, while minimizing maintenance overhead:

Qwak Cloud

Deploy your models and features on Qwak's private and secure cloud environment with a simple ramp up and quicker deployment times. Keep your data encrypted with no added overhead.

With Qwak Cloud, you can deploy your first model within minutes!

Qwak Hybrid

Keep your data and models stored in your own cloud environment while still taking advantage of a managed solution. Qwak provides a CloudFormation template to create a cross-account IAM role, granting Qwak the necessary permissions for environment setup and management.

The Qwak environment can be installed in 2 ways:

Default (Recommended)

Deploy into a new VPC. The deployment CloudFormation creates all the necessary components to ensure everything works as expected.

Existing VPC

Deploy Qwak resources in to an existing VPC environment along with existing resources within the VPC

❗️

We take data privacy seriously.

That's why all data is encrypted by default, ensuring that your machine learning models and data remain private and secure at all times - whether you choose Qwak Cloud or Hybrid Deployment.

For more information please refer to our Data & Privacy document.

High Level Architecture

Qwak's architecture consists of two main components: the Control Plane and the Data Plane.

Control Plane

The Control Plane is managed in Qwak's cloud and handles non-sensitive metadata. It communicates with the Data Plane to delegate sensitive operations such as model and data operations.

Data Plane

The Data Plane hosts the model repository, Feature Store, Qwak Inference Lake, and handles the model and data operations (model building, deployment, feature creation, etc).
The Data Plane uses the following services:

• EKS Cluster to manage Qwak services
• S3 for storing model output data
• Elasticache to manage the online feature store