Overview of C3 AI Supported Deployments
C3 AI Applications support flexible deployment options including C3 AI-managed or customer-managed cloud deployments on Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP). The choice of deployment option will have implications on project timelines, service-level agreement (SLA), and RACI requirements.
See the most recent C3 AI Installation Guides on the C3.AI website for more information.
C3 AI-managed cloud deployment overview
For C3 AI-managed cloud deployment, C3 AI provides a dedicated subaccount with dedicated compute, storage, and networking resources. All cloud resources are dedicated to your account and will not be shared with any other customer. C3 AI employs industry leading cyber security and access control practices to protect your applications and data.
C3 AI-managed cloud deployments are typically completed within two (2) days of the scheduled deployment start.
All the services are hosted in C3 AI cloud account for the specified cloud provider: Amazon Web Services (AWS), Google Cloud Platform (GCP), or Microsoft Azure cloud account.
C3 AI customer-managed deployment overview
In C3 AI, a cluster is a C3 AI deployment in the cloud that functions as the environment for developing and deploying C3 AI Applications. Your organization can choose to have multiple clusters or just one, depending on your needs.
For customer-managed AWS cloud deployments
You can optionally deploy the C3 AI cluster in your own AWS Virtual Private Cloud (VPC), a feature known as customer-managed deployment. You can use a customer-managed deployment to exercise additional control over your network configurations to comply with specific cloud security and governance standards your organization may require.
An AWS VPC allows you to provision a logically isolated section of the AWS cloud where you can launch AWS resources in a virtual private secure network. The VPC is the network location for your C3 AI clusters.
A deployment start schedule for a customer-managed deployment is dependent on the customer.
A customer-managed deployment is a good solution if you have:
- Security policies that prevent Platform-as-a-Service (PaaS) or Software-as-a-Service (SaaS) providers from creating VPCs in your own AWS account.
- An approval process to create a new VPC, in which the VPC is configured and secured and well-documented by internal information security or cloud engineering teams.
- A team with Terraform expertise and a change management system that are available for on-going management of infrastructure for the C3 AI cluster.
Benefits include:
- Lower privilege level: You maintain more control of your own AWS account. And you do not need to grant C3 AI as many permissions as you do for a C3 AI-managed deployment. For example, there is no need for permission to create VPCs.
- Maintain more control of your own AWS account and limit outgoing connections.
For customer-managed GCP cloud deployments
You can optionally deploy the C3 AI cluster in your own GCP Virtual Private Cloud (VPC), a feature known as customer-managed deployment. You can use a customer-managed deployment to exercise additional control over your network configurations to comply with specific cloud security and governance standards your organization may require.
A GCP VPC allows you to provision a logically isolated section of the GCP Cloud where you can launch GCP resources in a virtual private secure network. The VPC is the network location for your C3 AI clusters.
A deployment start schedule for a customer-managed deployment is dependent on the customer.
A customer-managed deployment is a good solution if you have:
- Security policies that prevent Platform-as-a-Service (PaaS) or Software-as-a-Service (SaaS) providers from creating VPCs in your own GCP projects.
- An approval process to create a new VPC, in which the VPC is configured and secured and well-documented by internal information security or cloud engineering teams.
- A team with Terraform expertise and a change management system that are available for on-going management of infrastructure for the C3 AI cluster.
Benefits include:
- Lower privilege level: You maintain more control of your own GCP project. And you do not need to grant C3 AI as many permissions as you do for a C3 AI-managed deployment. For example, there is no need for permission to create VPCs.
- Maintain more control of your own GCP account and limit outgoing connections.
For customer-managed Microsoft Azure cloud deployments
You can optionally deploy the C3 AI cluster in your own Azure Virtual Network (VNet), a feature known as customer-managed deployment. You can use a customer-managed deployment to exercise additional control over your network configurations to comply with specific cloud security and governance standards your organization may require.
An Azure Virtual Network (VNet) allows you to provision a logically isolated section of the Azure Cloud where you can launch Azure resources in a virtual private secure network. The VNet is the network location for your C3 AI clusters.
A deployment start schedule for a customer-managed deployment is dependent on the customer.
A customer-managed deployment is a good solution if you have:
- Security policies that prevent Platform-as-a-Service (PaaS) or Software-as-a-Service (SaaS) providers from creating VNets in your own Azure subscription.
- An approval process to create a new VNet, in which the VNet is configured and secured and well-documented by internal information security or cloud engineering teams.
- A team with Terraform expertise and a change management system that are available for on-going management of infrastructure for the C3 AI cluster.
Benefits include:
- Lower privilege level: You maintain more control of your own Azure subscription. And you do not need to grant C3 AI as many permissions as you do for a C3 AI-managed cloud deployment. For example, there is no need for permission to create VNets.
- Maintain more control of your own Azure account and limit outgoing connections.