Various technical risks and technical debts are identified during the design of the system. Technical risks refer to occurrences of unwanted and sometimes unexpected behaviors that could impact the operation of the system negatively. Technical debts refer to identified behaviors, solutions, and concepts that may improve the operation of the system but are not realized.

Risks

The risks associated with the EDDIE project are categorized into two groups:

1. Risks for Developers

Risk	Description	Applicable Measures
Monolithic Architecture	EDDIE is developed and deployed as a monolithic application primarily using Java. This architecture limits extensibility since plugins can only be developed in Java, restricting the use of other programming languages.	Gradually transition to a modular architecture or adopt a microservices approach to allow the integration of other languages. Maybe also define and implement a clear plugin API that supports cross-language compatibility through standard protocols (e.g., REST, gRPC).
Multitenancy Workarounds	EDDIE was not initially designed for multitenancy. The current implementation uses workaround mechanisms, introducing potential risks related to security and stability.
Security	The lack of a robust, multitenancy-first design increases the risk of data breaches or unauthorized access.	Conduct regular security audits focusing on multitenancy-specific risks and implement tenant isolation mechanisms, such as sandboxing or scoped access controls, to enhance security.
Stability	Workarounds may lead to unpredictable behavior or system crashes under specific conditions.	Perform thorough load testing and edge-case testing to identify and address stability issues. Develop a migration plan to refactor the system for native multitenancy support.

2. Risks for Users

Risk	Description	Applicable Measures
Unvalidated Data	AIIDA could send unvalidated data that diverges from validated values. This could lead to incorrect processing or decisions within the framework.	Implement stricter data validation mechanisms at the point of entry to ensure all incoming data meets expected standards. Further develop fallback strategies or error handling to mitigate the impact of invalid data during runtime.
API Instability	The Regional Data-sharing Infrastructure (RDI) may modify its APIs without prior notice, rendering the regional connector non-functional. This can disrupt critical integrations and cause delays.	Update the affected Regional Connector. Establish automated monitoring tools to detect API changes and alert developers. Maintain a buffer layer in the architecture that decouples direct API usage, enabling easier updates when changes occur.
Upload Bottlenecks	AIIDA causing upload bottlenecks due to limited bandwidth.	Reduce volume or frequency of real-time data transmissions.

Technical Debt

The following areas represent unresolved technical debt that must be addressed to ensure system maintainability and stability:

Dept	Description	Applicable Measures
Legacy CSS Framework	The Bootstrap CSS framework is still in use for simulation purposes, specifically for simulating communication with the MDA. This dependency should be replaced with a modern or custom solution to align with current standards and improve maintainability.	Replace Bootstrap with a more lightweight and modern CSS framework, or develop a custom styling solution tailored to project needs Perform regression testing after replacing the framework to ensure consistency in the simulation output.
API Change Detection	Related to the risk of API instability (R1), there is no established mechanism to identify or anticipate changes in third-party APIs. A proactive solution, such as subscribing to relevant newsletters or implementing automated monitoring tools, should be developed to enable engineers to adapt API calls effectively.	Develop a subscription process for API updates through newsletters or RSS feeds. Implement automated tools (e.g., API schema diff tools) to detect changes in third-party APIs and provide actionable insights to engineers.