How to ensure a seamless and secure experience across cloud impact levels

The national security community is stronger when users can take advantage of a connected foundation for secure innovation. But as classification levels for cert...

January 26, 2024 12:25 pm

4 min read

This content was provided by Microsoft Federal.

The national security community is stronger when users can take advantage of a connected foundation for secure innovation. Classified cloud platforms deliver that collaborative space with scalability, access at the edge, and most importantly, security. But as classification levels for certain workloads increase, how can agencies ensure a seamless user experience while still protecting vital data and applications—and how should this work in an era of multicloud environments?

Security from core to edge

Classified cloud is all about mission enablement. While on-premise legacy systems will continue to play a critical role, the reality is that work is increasingly done remotely. Also, the data sources that feed these classified environments can be anywhere around the globe. Sensors, satellites, autonomous vehicles, IoT devices, and more support full awareness of environments and situations.

The ability to securely capture and process data, then share the insights at the precise point and time of need, delivers a crucial advantage for everyone from decision makers to operators at the edge.

Of course, not all of the data an agency gathers and shares receives the same level of classification. DoD Impact Levels exist for this reason, and air-gapped classified cloud platforms reflect those standards. This helps fend off inbound threats before they can impact data, systems, and the mission, while a Zero Trust approach helps keep any internal threats contained.

Navigating across classification levels

While the ability to host workloads on platforms with differing impact levels is a huge benefit, working with data across those platforms can sometimes be challenging. A tool developed to support workloads at one classification level often needs to be available to other users working accessing a different secure environment.

It’s likely you’ll need to work with information across classification levels, but you’ll also need to make sure the necessary services are available. For instance, the ID management provider used on your commercial-level platform may not be the same for your secret cloud. Multicloud environments make this even more challenging.

Multicloud’s interoperability challenge

As agencies are migrating workloads to the cloud, some are doing so across multiple cloud platforms. Cloud environments are not inherently interoperable, and all too often, an individual will start their cloud journey and only consider the interoperability impact of multicloud at a later date.

While there may be a number of reasons to spread workloads across multiple platforms, the best practice is to keep related workloads within a single cloud service provider’s (CSP’s) ecosystem. This delivers the advantages of speed and easier management, but also can enable services created for one classification level to be reused securely.

So when choosing a cloud provider for classified workloads, consider consistency across a CSPs commercial (IL 2), Government (IL 4 & 5), Secret (IL 6), and Top Secret regions means the applications can often be easily promoted to those higher classification levels. This saves time, effort, and overall costs, while providing continuity for users and administrators alike.

Preparing for AI in a classified environment

Beyond migrating current workloads, it’s becoming clear that agencies need to prioritize their readiness for AI-based applications. From powering intelligent copilots to automate everyday tasks to accelerating critical enterprise processes, AI will free up personnel at every level to focus on mission goals.

To support this evolution, the cloud platform needs to both allow experimentation with innovative AI use cases and ensure security for your data, systems, and people.

An effective AI lifecycle-management process accounts for:

Data acquisition: how information for use by AI systems is captured and stored at the right security level.
Ingestion, staging and sharing of data: how information is tagged, labeled, and placed in a secure database—and audited, so you know who is touching that information.
Secure hosting: enabling testing and validation in walled-off environments, so no one can inject data that can skew outcomes.
Deployment and locking models down: ensuring the “right people, right time, right access” approach is always followed to control how—and if—AI models can be altered or reengineered.

Most importantly, strict governance is needed to ensure that data is protected, results are used appropriately, and AI supports human decision making effectively.

Next steps toward a seamless experience

Implementing a classified cloud platform that supports multiple classifications takes considerable planning and knowledge of best practices. This is often impractical to do completely in-house, and can also pull personnel away from mission-related work. It’s important to work with a trusted CSP and technology partners that bring not only expertise but people who have lived the mission.

Through an open, honest information exchange, both you and your trusted cloud partner will benefit from a clearer understanding of goals, obstacles, and new technologies. This helps define the path forward through a platform that supports multiple classification levels and innovation—empowering you to modernize your mission systems for today’s and tomorrow’s challenges.

Learn how classified cloud can empower the people who power the mission at https://aka.ms/ClassifiedMissionCloud