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Customer Cloud Deployments

A Customer Cloud Deployment (CCD) is set of software components created by STRM Privacy, deployed in your infrastructure. The goal is for your data and encryption keys, never having to leave your infrastructure, strengthening security even further regarding data subject privacy. Since data subject information never leaves your infrastructure, you have full control over the data, where it's stored, how long it's stored, who can access it, etc.


Data Planes were successfully tested on various (managed) Kubernetes implementations: local (K3S) , GKE, EKS , AKS, OVHcloud.


In the diagram below, you can see where all software runs in a CCD setup:

  • On the left is your infrastructure (e.g. an AWS EKS cluster in your account).
  • On the right is the STRM Privacy Control Plane (managed by STRM Privacy), which is accessible by gRPC services over the internet.

ccd infra


With the Helm Chart that is used to install the Data Plane in your infrastructure, you can enable/disable various components (e.g. disable streaming and only keep batch if only batch jobs are required).

Supporting the Control Plane

The entities doing the data processing receive their configuration from the STRM Privacy Control Plane, which is not part of your cluster. Inside your Data Plane, several agents run that frequently poll the STRM Privacy API. Based on the configuration provided by the control plane, the agents determine whether any new entities (e.g. a stream, a batch exporter, ...) are needed, or existing ones should be updated or removed. The agents are therefore indirectly controlled via user actions in the STRM Privacy Console and/or the CLI. Furthermore, the agents automatically keep the resources running in your Data Plane up-to-date.


All components part of the Data Plane directly (i.e. part of the Helm Chart), are not updated automatically. For updating your Data Plane, please see the updating docs.

The agents are an implementation of the desired state approach, which is used by many other popular tools (such as Kubernetes itself). Basically, it comes down to three steps:

  1. Retrieve the desired state from a central configuration location.
  2. Retrieve the actual running state in your infrastructure.
  3. Compare the two and make the necessary changes to the actual running state make it equal to the desired state.
  4. Repeat.

This pattern is very robust, handles failures and dependencies between resources very well. The only requirement is that outgoing traffic to is allowed. No need for incoming port forwarding rules, DMZ, etc.


All communication to and from the STRM Privacy Control Plane is TLS encrypted, and defined by an open-source gRPC protocol.

Deployment in your infrastructure

The process of installing the STRM Privacy in your infrastructure is as follows:

  • First, the data plane is deployed by you, using the Helm Chart. Here you can customize your cluster. This has to be done once at the start and if you'd like to install new versions of the Data Plane. It's your cluster, so we don't auto-update anything that is part of the Helm Chart. You decide if you'd like to upgrade and when it happens. The Helm Chart installs all components that are required to run streaming and batch data pipelines within your own infrastructure.
  • optional
    The third party components in the Data Plane are also deployed by you, using our Helm chart. You can choose if you'd like to use our pre-packaged versions of Kafka, Redis and Postgres, or if you'd like to connect to an external Kafka, Redis and/or Postgres. For example RDS, ElastiCache or Confluent. **Note the remark below.**
  • The rest is deployed by the STRM Privacy agents, using the desired state approach, as described before.

The Kafka, Redis and Postgres deployments that are included in the Helm Chart are not configured for, nor should be used for a production setting. Please refer to the products offered by your Cloud Vendor to see the offering for these requirements.

You can choose what components you want to enable, there are two major categories:

  • Stream Processing. requires Kafka, Redis, Event Gateway, Streams Agent, Data Connectors Agent and Exporters Agent.
  • Batch Processing. requires Postgres, Data Connectors Agent and Batch Jobs Agent.

Both can be enabled simultaneously if the requirement is to run both stream and batch data pipelines.