Edge to Hyperscale: Total Modernization in Government Missions

Driven by mission availability and performance needs, infrastructure modernization -- largely to the hyperscale cloud -- has been the dominant modernization trend for years in the US Federal Government.

Today, data and machine learning are prominent themes in conversations with CIOs and mission owners when it comes to modernization with US Federal Civilian, Defense, and Intelligence organizations rightly focused on putting data at the center of their enterprise and mission ops.

Data Has Gravity and that impacts Mission Modernization at the Edge 

Many mission applications operate in edge environments like Forward Operating Bases (FOBs), remote border posts, at sea and in the air, or in regions upended by natural disasters.  These applications are creating massive amounts of data at the edge from test events, unmanned aerial vehicles, Internet of Things (IoT) operations, and cyber sensors often in the most austere environments.  

This data at the edge has mass and consequently gravity.  While some of that data can be processed at the edge on bare metal or cloud edge devices like Amazon Web Services (AWS) Snow or Oracle 's Roving Edge devices, the edge is neither highly scalable or accessible by definition. As mission owners lean in to leverage continuing advances in Gen AI and other forms of AI and machine learning, getting that data to where it can be processed requires significant energy and time.

Gravity at the edge means federal CIOs and mission owners will need to move more aggressively to reassess architecture and ensure that applications are rationalized on the proper infrastructure in the right location.      

Gravity Driving Architecture 

That gravity still matters. When you modernize an application into a given cloud service provider (CSP) for economic or performance reasons, that application’s data may still need to exist (raw or refined) in other clouds, on bare metal or on another classification fabric – with all the performance, storage and timeliness challenges with moving large chunks of that mission data. 

These infrastructure, application and data architectures are obviously more challenging when operating in degraded or denied mission environments where bandwidth, power, and network availability is limited or non-existent for extended periods. This is where a relentless focus on application strategy matters, so that all the design decisions and tradeoffs map back to ensuring the app does what it’s supposed to, serving those who need it, in the way they need it, when and where they need it.

Meeting the Challenge: Scaled Modernization Through the Factory and Generative AI 

Beyond sound architecture -- to consistently and reliably drive all domain modernization at scale you need a factory. We built Accenture Federal’s Cloud Migration and Modernization Factory (CM2F) to drive this holistic modernization process -- data, infrastructure and application -- at scale for US Federal consumers, including classified mission owners.  CM2F enables rationalization and design for applications wherever they are starting and ending their journey – coupled with migration wave planning and execution to provide total transparency to the modernization lifecycle for stakeholders, budget and mission owners.

CM2F accelerates and controls the process of application, infrastructure and data modernization -- going beyond cloud. Of course with actual development, process alone is not enough as automation and tooling are key to accelerated and cost-efficient delivery. Cloud native, serverless and Container-based development are the obvious accelerants – and in the DoD those are often channeled through the software factories like PlatformOne, KESSEL RUN and others. Accenture's GenWizard can advance it even further, integrating with your source code repositories and your SDLC tools (e.g. Jira) for seamless integration with your DevSecOps process. Once in the DevSecOps cycle, we then employ leading tools such as GitHub CoPilot and Amazon Q to further accelerate code generation. 

Wrap 

The cloud revolution of the past decade gave US government mission owners reliable infrastructure. Today, the AI/ML revolution, mostly on those very same clouds, is giving US government mission owners at-scale analytic and alerting capabilities on massive data to drive real value-added decision making in a highly contested economic and geopolitical environment.  

That massive data used in machine learning often begins its life at the edge – driving another wave of modernization to rationalize how and where missions process and use data, and creating new value added services along the way. The modernization choices in this hyper-converged world are inextricably linked to mission success – to ultimately deliver highly functional, highly available, highly secure, and resilient modern applications to power critical missions forward – with the right data getting to decision makers, operators and analysts alike. 

Justin Shirk is Managing Director, Mission Operations and Cloud Ecosystems Lead at Accenture Federal Services.