Earlier this year, the Department of Defense announced it had achieved a “minimum viable version” of the Combined Joint All-Domain Command and Control system (CJADC2), a significant step toward interconnecting forces across land, sea, air, space and cyberspace, giving warfighters rapid access to information that could have a major impact.
As CJADC2 evolves, so must DoD's edge infrastructure. Organizations must ensure the infrastructure they use delivers accurate intelligence in all situations, regardless of the environment or the allies involved. That infrastructure must be resilient in harsh and remote environments and dynamically configurable so intelligence is delivered quickly and reliably even as operations and objectives change.
AI and automation can help the Defense Department achieve these two goals, but they must first overcome the limitations of traditional hardware that make it difficult to get data to soldiers.
Breaking away from “box studies”
Proprietary, siloed platforms will not meet the CJADC2 goal of systems that “sense, understand, and act quickly” on information gained from AI, automation, machine learning, and predictive analytics.
Fortunately, the Department of Defense is standardizing hardware through open architecture approaches such as the Army’s C5ISR Modular Open Suite of Standards (CMOSS) and C5ISR Modular Form Factor (CMFF), allowing the Army and other defense agencies to escape the proprietary “boxologies” that are holding them back from taking full advantage of the edge and AI.
Increased flexibility offers multiple benefits. Military branches can build a more dynamic, resilient infrastructure that can be quickly launched and deployed in any situation. Warfighters can gain real-time insight to gain a “decisive advantage” over their adversaries.
Building self-healing, configurable networks
Operating in harsh environments, traveling from one operation to another, and challenges with sharing information among allies can all lead to disruptions or degradation of communications and intelligence gathering.
To overcome these challenges, the Department of Defense must build a self-healing edge infrastructure. When issues arise, the network must be able to recover and repair quickly and automatically, without the need for human intervention. AI and machine learning enable the network to detect common issues like latency, degradation, and other performance factors and respond appropriately, while automation allows the network to respond to these issues immediately.
Edge networks must also be composable. Composability relies on virtualization and automation to dynamically recreate network, compute, and storage resources as needed. This gives soldiers the flexibility to connect to different assets, which is useful when working across multiple agencies and with different allies that may rely on their own network infrastructure.
Gaining an advantage with open source
Just as the Department of Defense is embracing open standards in hardware, the department is also actively implementing open source software through efforts like the Army's Open Source Intelligence (OSINT) Strategy. The Army and other military services can support OSINT and similar efforts by overlaying resilient, configurable networks with open source software that can take full advantage of automation and AI at the edge.
Open source automation can be applied across a wide variety of domains, use cases, and infrastructure types. Teams can easily write code to specify automation tasks and apply the same protocols to any edge environment, eliminating the impact of incompatible technologies. For example, soldiers working with multiple peers in remote locations can specify steps the network should take to automatically reroute traffic if bandwidth or capacity is insufficient.
Meanwhile, open source containers enable teams to port applications, including those that use AI, from one environment to another. Containers wrap all the components of an application, including the files required to run the application, into a very small, ephemeral package, enabling application portability. Powerful AI resources can be easily created and transferred between missions to run on standardized hardware.
Ongoing maintenance for ongoing intelligence
Keeping these implementations up to date will be key to their success, so the DoD must break away from standard software maintenance cycles and embrace continuous evolution, something they are already doing through the advancement of programs like CJADC2.
That effort must continue to the front line to ensure warfighters maintain highly accurate strategic intelligence.
Christopher Yates is the Department of Defense and Army principal architect at Red Hat.
