chapter ten

10 Digital twins in production

 

This chapter covers

  • Approaches to running a digital twin in production
  • Security, governance, and ethical considerations for digital twins
  • Digital twin operations
  • Continuing strategic alignment and value realization

Moving a digital twin from prototype or proof-of-concept to production is the final step in delivering a system that delivers on the promised business value. This transition is important because a digital twin only generates sustained value when it operates reliably within the chaotic, always-on environment of the real world. It is one thing to model a system when you control the inputs and can experiment and pivot at will, and an entirely different challenge to operate a system that is integrated into live operational workflows.

Production is where digital twins either become strategic assets or costly prototypes, and the difference lies in operational discipline, governance, and continuous alignment with business goals. Understanding these concerns is essential if a digital twin is to deliver sustained value rather than a one-time technical success.

10.1 Selecting the right deployment platform

10.1.1 Public cloud providers

10.1.2 Digital twin development platforms

10.1.3 Fully managed digital twin platforms

10.2 Security as a cross-cutting concern

10.2.1 Expanding the threat model

10.2.2 Identity everywhere

10.2.3 Policy as code

10.3 Digital twin operations

10.3.1 Observability

10.3.2 Model lifecycle management

10.3.3 Change management

10.3.4 Cost management

10.3.5 Software dependency management

10.4 Aligning to strategy and measuring value

10.4.1 Operational impact

10.4.2 User adoption and trust

10.4.3 Financial value

10.5 Governance, ethics, and responsibility

10.5.1 Decision authority

10.5.2 Accountability and ownership

10.5.3 Ethical use

10.5.4 Auditability and traceability

10.6 A production readiness checklist

10.7 Summary