How It Works

The simplest mental model for Tensor9 is that it delivers your existing SaaS stack into any customer environment. Your customers then use your product by interacting with their own private instance of your stack. To make this easy for you, Tensor9 watches your existing SaaS stack (in your cloud), and continuously synchronizes to your customers (in their environment).

Tensor9 is is able to accomplish this for a variety of customer environment by reading the infrastructure-as-code representation of your stack (e.g. CloudFormation, Terraform/OpenTofu, Kubernetes Helm, Pulumi) and compiling it into a form suitable for deployment to your customers' environments.

Tensor9 is unique because of its digital twin approach to deployment and observability:

Tensor9 maintains a nano-sized digital twin of the stack running in each customer's environment. This digital twin reflects the deployment and operational state of its corresponding customer stack. When you deploy changes to your SaaS stack, Tensor9 automatically synchronizes those changes to the digital twin for each customer, which in turn trigger deployments to the corresponding customer stacks. Similarly, logs, metrics and alerts produced by a customer stack are continuously published back to its digital twin. Software and hardware failures are also continuously published back to the digital twin. The end result is that you can observe, debug, and support your customer's stack as if it were local by observing and deploying to its digital twin.