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ExplanationsHow Five Safes TES worksSystem Architecture
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Prerequisites

System Architecture

The Five Safes TES (Task Execution Service) is designed to handle sensitive data analysis within a secure and controlled environment. The architecture followed by a Fan-out pattern for the implementation and is organized into multiple layers and application components.

Aggregation is supported via external tools and after 5S-TES completes analysis tasks, users can run a dedicated aggregation tool to collect and summarise results.

Figure 1: Illustration of the context diagram for Five Safes TES architecture. Click for interactive mode.

Components Architecture

The Five Safes TES is divided into multiple layers of process and multiple app stack as discussed below.

The layers of the architecture are:

  • Submission Layer: Entrypoint for user requests, authentication, and authorisation.
  • TRE Layer: Core processing layer for data analysis.

The Five Safes TES app stack includes:

  • Submission App: Handles user submissions.
  • TRE Agent App: Manages task execution within the TRE for data analytics.
  • Egress App: Checks and approve/reject the results of the analysis.

Figure 2: App structure and data flow within Five Safe TES. Click for interactive mode, including data flow walkthrough.

The data flow diagram above is interactive. Click twice on the diagram to enter interactive mode, and then click on the blue ‘Start’ button at the top of the diagram to enter the data flow walkthrough.

Operational Overview

The high level overview of working of the Five Safes TES is as follows:

Submission App

  1. The process begins with the end user or researcher submitting a request for the desired analysis through the Trusted Research Environments. Then, authentication and authorisation checks are performed to ensure the user is assigned to the relevant project.

  2. The request is then placed in a queue as a task for the corresponding nodes in the federated network and the researcher can track the stages of the analysis.

TRE Agent App

  1. The TRE Agent in the TRE Layer monitors the queue for new jobs (tasks). Once identified, TRE agent get the task and start the pre-processing of the task.

  2. A tool called Camunda will dynamically inject the ephemeral credentials into the environment variables of the TES message, which Executor will use to connect to the database.

  3. The standardised payload is sent to the Executor, then the analysis will be executed against TRE’s restricted database.

  4. The results of this analysis are then saved in storage at the TRE Layer.

Egress App

  1. After the analysis results are stored, the TRE notifies the data owner (a designated human reviewer) to approve the release of results.

  2. The owner can now reviews the output and, if approved, authorises the egress.

  3. Upon approval, the results are copied over to the Submission layer’s storage, and finally, the researcher receives the analysis results.

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