An expanded suite of information security tools and services, reduction in technical debt, and reduced operating cost are all possible with a properly planned and architected cloud solution. The benefits of a flexible, scalable, yet secure cloud architecture can help Federal agencies realize the fiscal and operational efficiencies of moving to the cloud while continuing to provide required citizen services. For some Federal agencies the return on investment (ROI) can be significant.
To achieve the best ROI possible Federal agencies must seek a balanced solution architecture that provides the optimal level of interoperability, closely align to the agency mission, and bolsters its information security posture. Undoubtedly, there will be challenges and obstacles to achieving a balanced solution architecture so having a strategy in place to address those challenges will be key to success.
It takes a village
Finding the right vendor, cloud service provider, and building a skilled workforce is foundational to everything that follows. It is critical that the selected vendor understands, and embraces, the agency mission. The selected vendor must be able to identify complementary technologies, develop a cloud architecture, and support transformation/migration management services. When selecting a cloud service provider, the agency’s current technology (app, security, data) stack, IT governance requirements, and funding levels will be key inputs to the decision-making process, especially when seeking a Hybrid architecture. Having a skilled workforce in place to support the cloud migration and transformation efforts will help ensure mission alignment. A skilled workforce will be able to work very closely with vendors and the cloud service provider to ensure current and future needs are communicated and addressed.
"To achieve the best ROI possible Federal agencies must seek a balanced solution architecture that provides the optimal level of interoperability, closely align to the agency mission, and bolsters its information security posture."
Cloud is not cheap
Federal agencies are generally risk averse, and this is primarily due to the unpredictable nature of federal funding. Developing a business case to justify the required level of funding will be one of the most important upfront tasks undertaken by agency CIO’s. To help ensure the appropriate level of funding it is important to secure leadership buy-in at the highest level. When trying to secure leadership buy-in, a Cost Benefit Analysis and ROI can help communicate the importance and efficiencies of moving to the cloud. A complete Risk Assessment along with solid mitigation strategies will help immensely. Additionally, agencies should not bite of more than they can chew. To help reduce the complexities and large initial funding required agencies should develop an incremental roadmap that clearly demonstrates capability early and often.
Improved interoperability and expanded information security services are just two of the many benefits to migrating from traditional data centers into a cloud environment. Advances in Artificial Intelligence (AI) have introduced a number of improved network monitoring tools and dashboards. These tools provide automated delivery of network health, real-time intrusion and response information, and real-time application availability status. There are many AI advances that can influence an agency’s decision to implement Zero Trust and/or improve Network Segmentation. Agencies must consider current and future needs when reviewing information security technologies. For example, with the case of Zero Trust, agencies must find the best fit. Should Zero Trust be Centralized or Distributed? Will Continuous Authorization be implemented?
There are several early adopters within the Federal government that have piloted using container-based computing models. Depending on application interoperability needs and the implemented information security model a container-based computing model may be worth looking into.
Cloud service providers are now offering online Machine Learning (ML) and other AI related services to its customers. Customers can now quickly build, train and deploy machine learning models, or build custom models. Services such as image and video analysis, advanced text analytics, and document analysis can be quickly stood up without large upfront cost and time.
Most cloud service providers today offer Storage ‘as a Service’ which can help to significantly reduce operating cost and improve shared services. With current advances in AI-enabled chips there’s potentially another abstraction layer that can help improve application performance by moving more of the data analysis and discovery services to these specialized chips. Advances in “pattern discovery” can significantly reduce the complexity and time currently needed to identify anomalies and correlations within structured and unstructured data. Having access to an AI-enabled chip can help you take advantage of advances in “pattern discovery”.