IT Infrastructure Digital Twin for Rapid Pre-Production Replication
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Solution Overview
Problem
Maintaining pre-production testing environments for software changes in corporate IT infrastructures is expensive and laborious, often requiring duplication of hardware and software licenses, and companies lack efficient tools to quickly replicate and test changes without disrupting production.
Innovation Solution
A digital twin system that identifies and classifies servers in an IT infrastructure using telemetry and network-crawling data to create executable scripts, allowing rapid replication of a pre-production environment in the cloud for testing, validation, and backup purposes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a pre-production testing environment is maintained to test software changes, then software changes can be tested before deployment, but the cost of hardware and software licenses doubles
Solution Approach 1:
The patent creates a digital twin (virtual copy) of the production IT infrastructure that can be deployed on-demand in the cloud. This digital twin replicates the server graph, configurations, and interconnections of the production environment, enabling pre-production testing without requiring physical duplication of hardware and software licenses. The digital twin can be quickly instantiated, used for testing, and then decommissioned, eliminating the need for permanent duplicate infrastructure.
Solution Approach 2:
The patent transitions from physical infrastructure to virtual infrastructure by creating a digital representation of the IT environment. This dimensional shift from physical to virtual allows the testing environment to exist in a different realm (cloud-based virtual environment) rather than requiring physical duplication of the production hardware and software stack.
2Reliability
If in-house IT professionals manually build pre-production environments, then comprehensive testing can be achieved, but the process takes months and requires deep knowledge of all servers
Solution Approach 1:
The system automatically discovers and replicates the production IT infrastructure by crawling the network, identifying servers, and mapping their interconnections without requiring manual intervention from IT professionals. The digital twin service autonomously builds the testing environment by programmatically recreating the server graph and configurations, eliminating the need for experts to manually configure each component.
Solution Approach 2:
The patent performs preliminary discovery and mapping of the production environment in advance, creating a digital blueprint of the IT infrastructure. This preliminary action captures the complete server graph, configurations, and interconnections before the testing environment is needed, enabling rapid deployment of the digital twin when required for pre-production testing.
3Reliability
If the digital twin is updated to reflect production changes, then the testing environment remains accurate, but continuous synchronization increases complexity
Solution Approach 1:
The system implements periodic resynchronization by allowing users to trigger updates at discrete intervals or events. Rather than continuous real-time synchronization, the digital twin can be refreshed periodically to reflect changes in the production environment, balancing accuracy requirements with operational simplicity. This periodic update approach reduces the complexity of the synchronization mechanism while maintaining adequate accuracy for testing purposes.
Data Source
Figure 1A
Figure 1B
Figure 2A
AI summary
A digital twin of an IT infrastructure is created to identify a group of critical servers (called "base servers") needed to replicate the IT infrastructure in a cloud-computing environment. To identify the correct base servers and their actual server configurations, the IT infrastructure is crawled and various telemetry, connection, and network data is analyzed against data sets of other known servers. The digital twin is created to include these base servers and their particular configurations. Then, the digital twin may be deployed on demand in the cloud-computing environment using executable scripts that mimic the base servers and their particular configurations, creating a replication of the IT infrastructure for various purposes (e.g., redundancy, testing, etc.).