System Architecture
Different variations of the ZenML architecture depending on your needs.
Last updated
Different variations of the ZenML architecture depending on your needs.
Last updated
This guide walks through the various ways that ZenML can be deployed, from self-hosted OSS, to SaaS, to self-hosted ZenML Pro!
This page is intended as a high level overview. To learn more about how about to deploy ZenML OSS, read this guide.
A ZenML OSS deployment consists of the following moving pieces:
ZenML OSS Server: This is a FastAPI app that manages metadata of pipelines, artifacts, stacks etc. Note: In ZenML Pro, the notion of a ZenML server is replaced with what is known as a "Tenant". For all intents and purposes, consider a ZenML Tenant to be a ZenML OSS server that comes with more functionality.
OSS Metadata Store: This is where all ZenML tenant metadata is stored, including ML metadata such as tracking and versioning information about pipelines and models.
OSS Dashboard: This is a ReactJS app that shows pipelines, runs, etc.
Secrets Store: All secrets and credentials required to access customer infrastructure services are stored in a secure secrets store. The ZenML Pro API has access to these secrets and uses them to access customer infrastructure services on behalf of the ZenML Pro. The secrets store can be hosted either by the ZenML Pro or by the customer.
ZenML OSS is free with Apache 2.0 license. Learn how to deploy it here.
To learn more about the core concepts for ZenML OSS, go here.
If you're interested in assessing ZenML Pro SaaS, you can create a free account.
If would like to self-host ZenML Pro, please book a demo.
The above deployment can be augmented with the ZenML Pro components:
ZenML Pro Control Plane: This is the central controlling entity of all tenants.
Pro Dashboard: This is a dashboard that builds on top of the OSS dashboard, and add further functionality.
Pro Metadata Store: This is a PostgreSQL database where all ZenML Pro related metadata is stored such as roles, permissions, teams, and tenant management related data.
Pro Add-ons: These are Python modules injected into the OSS Server for enhanced functionality.
Identity Provider: ZenML Pro offers flexible authentication options. In cloud-hosted deployments, it integrates with Auth0, allowing users to log in via social media or corporate credentials. For self-hosted deployments, customers can configure their own identity management solution, with ZenML Pro supporting custom OIDC provider integration. This allows organizations to leverage their existing identity infrastructure for authentication and authorization, whether using the cloud service or deploying on-premises.
ZenML Pro offers many additional features to increase your teams productivity. No matter your specific needs, the hosting options for ZenML Pro range from easy SaaS integration to completely air-gapped deployments on your own infrastructure.
You might have noticed this architecture builds on top of the ZenML OSS system architecture. Therefore, if you already have ZenML OSS deployed, it is easy to enroll it as part of a ZenML Pro deployment!
The above components interact with other MLOps stack components, secrets, and data in the following scenarios described below.
To learn more about the core concepts for ZenML Pro, go here
For the ZenML Pro SaaS deployment case, all ZenML services are hosted on infrastructure hosted by the ZenML Team. Customer secrets and credentials required to access customer infrastructure are stored and managed by the ZenML Pro Control Plane.
On the ZenML Pro infrastructure, only ML metadata (e.g. pipeline and model tracking and versioning information) is stored. All the actual ML data artifacts (e.g. data produced or consumed by pipeline steps, logs and visualizations, models) are stored on the customer cloud. This can be set up quite easily by configuring an artifact store with your MLOps stack.
Your tenant only needs permissions to read from this data to display artifacts on the ZenML dashboard. The tenant also needs direct access to parts of the customer infrastructure services to support dashboard control plane features such as CI/CD, triggering and running pipelines, triggering model deployments and so on.
The advantage of this setup is that it is a fully-managed service, and is very easy to get started with. However, for some clients even some metadata can be sensitive; these clients should refer to the other architecture diagram.
We also offer a hybrid SaaS option where customer secrets are stored on the customer side. In this case, the customer connects their own secret store directly to the ZenML server that is managed by us. All ZenML secrets used by running pipelines to access infrastructure services and resources are stored in the customer secret store. This allows users to use service connectors and the secrets API to authenticate ZenML pipelines and the ZenML Pro to third-party services and infrastructure while ensuring that credentials are always stored on the customer side.
In the case of self-hosting ZenML Pro, all services, data, and secrets are deployed on the customer cloud. This is meant for customers who require completely air-gapped deployments, for the tightest security standards. Reach out to us if you want to set this up.
Are you interested in ZenML Pro? Sign up and get access to Scenario 1. with a free 14-day trial now!
