Opportunities

IXL Experimentation Offerings

As part of our initial offering within the Innovation Exchange Lab, we are collaborating with the UDRA team and industry partners to provide access to the implementation of UDRA 1.0.

Unified Data Reference Architecture (UDRA) – What is it?

The Assistant Secretary of the Army for Acquisition, Logistics, and Technology (ASA-ALT) Deputy Assistant Secretary of the Army (DASA) for Data, Engineering, and Software (DES) is defining a Unified Data Reference Architecture that introduces Data Mesh principles into the Army’s data architecture. Data Mesh is a data architecture based on a federated and decentralized approach to analytical data production, sharing, access, and management in complex and large-scale environments, within or across organizations. It is characterized by federated computational governance, self-service infrastructure, treating and providing data as a product, and autonomous data domains that are responsible for their data. The Unified Data Reference Architecture (UDRA) is intended to guide the implementation of interoperable data sharing across all Army acquisition programs.

Our UDRA Reference Implementation

The Unified Data Reference Implementation (UDRI) is the representation of the UDRA 1.0. Registrants can implement their solutions against the UDRI services and components to understand alignment and make informed decisions on potential product development.

DOWNLOAD THE UDRA Documentation

Download the UDRA 1.0 Release – Review the current reference architecture to gain an understanding of UDRA 1.0.

Helpful Materials to Guide Your Registration:

UDRA Self Assessment – leverage this worksheet to help guide you through your own product alignment with the UDRA
Army Directive 2024-02 – Read the Secretary of the Army’s directive on new software acquisition.

Once you begin registration, a pre-brief engagement with vendors will outline process of participation, methods and requirements for obtaining architecture artifacts, API documentation, Integration guidance, specific demonstration objectives, and infrastructure entrance criteria.

Important Note

Any Personally Identifiable Information (PII) and/or sensitive information submitted during registration will be held as Controlled Unclassified Information (CUI). You should NOT submit any Classified information or Privately held Intellectual Property or content. Only provide what is already publicly available.

Frequently Asked questions

Can I submit my products capabilities during my initial registration?

Yes, you can include a detailed description and attach your product fact sheets or a product white paper (no more than 15 pages) during registration.

Can I customize the environment to be sure we have enough resources conduct experiments?

Yes here a the technical requirements you can share in your request:
What are the minimum hardware and software requirements for deploying your solution in our environment?
Does your software require specific databases, operating systems, or server configurations? If so, identify which ones
What kind of computing resources (CPU, RAM, storage) are optimal for running your software efficiently in our setup?

What information do I need to provide to show my product’s compatibility?

In your whitepaper submission (no more than 15 pages), address the following:
1. Data Mesh Principles Compliance:
a. Solutions must align with Data Mesh principles, emphasizing decentralized data ownership, domain-oriented decentralized governance, self-serve data infrastructure as a product, and data as a product.
b. How the solution brings specific capabilities or features to address the services/activities defined in UDRA.
2. Interoperability: Solutions must offer well documented and extensible APIs or Open APIs and adhere to industry standards that facilitate interoperability with existing and future systems in the data ecosystem.
3. Modular and Scalable: The solution’s architecture should be modular and scalable, allowing components to be independently developed, deployed, and scaled.
4. Observability and Monitoring: Solutions should include capabilities for monitoring and observability to track data lineage, quality, and usage metrics.
5. Self-Service Capabilities: Solutions should facilitate self-service data discovery, access, and consumption, empowering end-users and reducing reliance on centralized IT support.
6. Security and Privacy: Solutions should adhere to security and privacy standards, including data encryption at rest and in transit, access controls, and compliance with the Zero Trust model.

Inclusion of any real-world examples of your solutions deployment in environments adhering to data mesh principles, and/or your solutions alignment to UDRA use cases would be helpful to share as well.

Will my software be scanned for security and malware.

Software scanning required for submission

For more questions, see:

IXL Questions 23 Apr24

Technical Details Examples:

Here are examples of product related content you may wish to share during registration.

1. Technical Requirements:

What are the minimum hardware and software requirements for deploying your solution in our environment?

Does your software require specific databases, operating systems, or server configurations? If so, identify which ones

What kind of computing resources (CPU, RAM, storage) are optimal for running your software efficiently in our setup?

2. Compatibility and Scalability:

How compatible is your software with our existing data infrastructure and tools, especially those adhering to data mesh principles?

Can you provide examples of organizations similar to ours that have successfully scaled their data infrastructure using your software?

What is the maximum data volume and user load your solution can handle effectively, and how does it scale as our needs grow?

3. Integration and Interoperability:

a. Integration Capabilities:

Does your software offer APIs or data connectors for seamless integration with other data-related tools and platforms in our ecosystem?

How does your software handle data transformations and schema evolution when integrated with diverse data sources within a data mesh environment? Any context specific to Army is a bonus

b. Interoperability with Third-party Tools:

Are there any third-party tools or technologies that your software is specifically designed to work well with within a data mesh architecture?

How does your software facilitate interoperability between different domain-oriented data products and services in a decentralized data mesh environment?

4. Data Governance and Security:

a. Data Governance Measures:

What data governance features does your software offer to ensure data quality, lineage, and metadata management within a data mesh architecture?

How does your solution support data discovery and cataloging, especially in a decentralized data environment with multiple domains?

b. Security Protocols:

What security protocols and encryption standards are employed to protect data both in transit and at rest?

Can you describe the access control mechanisms within your software, especially in scenarios where different domains need different levels of access to shared data resources?

How does your software handle data privacy and compliance requirements

Software scanning required for submission