The Department of Defense (DoD) leads adoption of cloud technologies to advance its various missions. As battlefields become more diverse and more dispersed edge computing is essential to support the DoD with insights and threat assessments that enable real-time decision making. To realize the full potential of edge technologies, cloud and edge ecosystems are coming together to support todays warfighters. MeriTalk sat down with Frank Reyes, cloud solutions leader at Maximus, to discuss the DoDs cloud strategy, the future of cloud computing across the DoD, and how industry can partner with the DoD to support cloud integration and achieve mission success.
MeriTalk: With DEOS, Cloud One, Stratus, and others, the Defense Department is taking a multi-cloud approach to cloud computing. What is driving the DoDs cloud strategy?
Reyes: There are three key drivers for the DoDs multi-cloud strategy. The first is interoperability and data portability. The DoD collects, stores, and analyzes vast amounts of data from multiple domain systems. With a multi-cloud approach, it can integrate data from a variety of systems and applications, allowing the data to be accessed and shared more efficiently across the different service branches, commands, and coalition partners. The second driver is agility. The DoD needs to rapidly access its infrastructure and applications to support evolving mission requirements. With a multi-cloud approach, the DoD takes advantage of diverse cloud service offerings to enable rapid provisioning and deployment of mission-critical applications. The third driver is innovation. The DoD recognizes the importance of harnessing emerging technologies including artificial intelligence (AI), machine learning (ML), advanced analytics, Internet of Things, and others to gain a competitive edge. A multi-cloud strategy allows the DoD to tap into innovations being developed by its cloud service providers (CSPs).
MeriTalk: Cloud-native applications are increasingly powerful. How are they helping DoD agencies meet their missions faster?
Reyes: By adopting cloud-native applications and architectures, the DoD can accelerate from monolithic to microservices architectures. This allows the department to develop, deploy, and scale applications faster, respond faster to changing mission needs, and deliver capabilities more efficiently. And, with the real-time data streams, ML algorithms, and predictive analytics baked into most cloud computing platforms, the DoD is able to generate insights from large data sets for better situational awareness and more effective operations.
MeriTalk: From remote sensors to satellites to drones, the DoD is collecting more data at the edge. How is that impacting the DoDs cloud needs and cloud computing capabilities?
Reyes: The DoDs ability to collect data from edge devices has grown exponentially, and cloud computing is currently the best capability that provides the infrastructure, storage capacity, and advanced analytics tools required to accommodate large-scale ingest, rapid analysis, and long-term retention of massive volumes of edge data.
The DoDs cloud needs are also being shaped by the requirements to establish reliable and secure connectivity between edge devices and the cloud infrastructure, especially in environments where backhaul is limited. Real-time or near real-time data transmission from remote sensors, satellites, and drones to the cloud is essential for that timely decision-making. The CSPs now offer a range of hardware that provides secure, high-bandwidth connectivity to facilitate the seamless data transfer between edge devices and the cloud.
And, when you dont have backhaul capability, you need to do your computing at the edge. The DoD is reducing latency, improving response times, and alleviating the burden on centralized cloud infrastructures by adopting more edge computing at the point of collection. This distributed approach enhances the performance of mission-critical applications, enabling real-time decisions.
MeriTalk: As edge computing continues to grow, what can Federal technology leaders do now to prepare for more insights generated at the edge?
Reyes: Leaders should strongly be considering leveraging the global infrastructure, such as edge servers and points of presence locations, closer to where the data is collected. Government can co-invest in these services with CSPs, along with partnering to enhance bandwidth and connectivity, including 5G and low-Earth satellite capabilities. As security is paramount with any device collecting and sharing information at the edge, government should develop security protocols for edge devices and data transmission.
MeriTalk: As the DoD explores use cases for generative AI, how will this affect edge computing and the DoDs cloud capability needs at the edge?
Reyes: Because generative AI involves computationally intensive tasks and requires large foundational models, it will be challenging to use the technology at the edge unless there are edge devices and capabilities to support it. That will require investments in purpose-built edge devices with improved compute capabilities. Improved devices will also allow the DoD to process data collected at the edge before sending it to the cloud for further analysis, reducing the amount of data transferred to the cloud. Another benefit of generative AI at the edge is improved cybersecurity. When sensitive DoD data supporting AI is processed and encrypted locally, the DoD maintains greater control over that data, which helps reduce the risk of unauthorized access.
MeriTalk: Can you share an example of how generative AI can be used in the field with the right cloud computing capabilities to support it?
Reyes: One example is images collected by drones in the field. Currently, drones on a mission collect information and images and send those back to a central location for analysis, which takes time. But, if we add edge computing resources and generative AI technology onto the drone, the device can process the data in near real-time and make inferences based on its training. Moving the compute function and generative AI technology to the edge drastically increases situational awareness and decision-making speed.
MeriTalk: What are some other ways cloud functionality at the edge can support the DoDs mission?
Reyes: Beyond the benefits of real-time data analysis to improve decision time, moving cloud functionality to the edge will be critical in environments with limited connectivity. Cloud at the edge also supports latency-sensitive applications such as precision-guided munitions and unmanned vehicle controls that require extremely low latency for performance. By moving cloud functionalities to the edge, those latency-sensitive applications can be executed locally, minimizing roundtrip time to the offsite cloud and enabling near instantaneous response time.
MeriTalk: The Joint Warfighting Cloud Capability (JWCC) allows the DoD to explore and acquire cloud solutions to serve missions from headquarters to the tactical edge. How can industry support the DoDs evolving cloud needs so it can realize the full potential of advanced edge technologies?
Reyes: First, industry can develop and offer meaningful cloud solutions that are tailored specifically to take advantage of an edge cloud computing infrastructure, cloud-enabled generative AI, and smarter edge devices. Industry can also help enable the seamless integration of those advanced edge technologies with the cloud. Secondly, industry can invest in the development and deployment of edge computing around the world and smaller edge computing infrastructure devices and in establishing standards-based interfaces, protocols, and APIs that enable seamless communication and data exchange between the edge devices and cloud for agencies. The third area is training support. Industry can help DoD personnel gain the necessary skills and knowledge they need to really understand how to extract the value of these new edge devices and cloud computing infrastructure.
MeriTalk: How can Maximus support the DoD with improving cloud capabilities to realize the full potential of edge technologies?
As a Federal systems integrator, we know the cloud and edge very well. With our expertise in cloud computing, we offer tailored solutions integrating cloud and edge ecosystems to enhance the DoDs ability to leverage data at the edge more efficiently. We collaborate with technology teams to design data architectures, implement a data governance framework, and leverage advanced analytics techniques to extract valuable insights from the vast amount of data generated by edge technologies. We then layer on AI and ML capabilities to deliver real-time situational awareness and fast decision-making capabilities. Maximus is also keenly focused on security and compliance. Our Maximus Cloud solution is FedRAMP accredited, and we manage multiple security operations centers throughout government. We can leverage that experience to implement robust security measures ensuring data protection while meeting regulatory standards.
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