The Growth of milCloud 2.0 Demands a New Monitoring Approach
February 28, 2022
Applications
The addition of Amazon Web Services and VMware to the Defense Department’s milCloud 2.0 contract will make it easier for agencies to transition applications and services to the cloud.
However, the acceleration of this effort may bring its own challenges. MilCloud is a substantial operation, with more than 1,200 virtual servers as of early 2021. The addition of AWS and VMware will allow agencies to add to this number, making an already complex service even more challenging to manage.
How can agencies ensure all their applications, regardless of where they reside, will work seamlessly, securely, and reliably across the DOD’s massive network footprint? This can only be achieved by moving beyond a traditional, siloed approach to network monitoring in favor of complete observability across all aspects of the DOD infrastructure.
Instead of looking at storage, computing, and networking as separate entities, administrators must have an omnipresent view of how each of these components works together, inside and outside the network perimeter and across databases, servers, and applications.
Only then will they be able to understand every interaction, connection point, and data transfer, ensuring the stability, reliability, and security of their cloud services.
Agencies that can achieve this level of omniscience will experience several benefits, including the following.
Secure and frictionless collaboration. Agencies will create a safer environment without impeding collaboration between individuals and teams. Administrators will be better positioned to detect potential vulnerabilities or anomalies that could result from all manner of collaboration, including the sharing of information across agencies and remote work environments. Beyond security, administrators will be able to quickly discern whether applications are performing up to standards.
Fast and accurate anomaly detection. The ability to analyze and visualize log data for anomaly detection was noted as a key priority of the White House’s cybersecurity executive order.
Agencies must be able to analyze log data quickly and easily—including events that occurred, the time of the occurrence, and other factors—across the entire ecosystem. Only then can they effectively determine the extent of any potential anomaly and the threat it may or may not pose.
Smarter threat response, fewer alerts. Artificial intelligence (AI) can be beneficial in these cases. By leveraging AI and machine learning, agencies can automate their observations, allowing technology to scan the ecosystem and sift through massive amounts of disparate data, automatically remediating threats as they appear without creating havoc among users.