The federal government directs more than $100 billion annually toward information technology, yet roughly 80% of that spending feeds the operation and maintenance of existing systems rather than building new ones. A July 2025 Government Accountability Office audit surfaced 11 critical federal legacy IT systems in urgent need of replacement, with some running on programming languages like COBOL and assembly code that most universities stopped teaching years ago. Of the 10 systems the GAO originally flagged in 2019, just three have completed modernization as of early 2025. The picture is particularly stark in grants management, where agencies responsible for distributing hundreds of billions of dollars in public funding still rely on fragmented workflows, manual tracking, and infrastructure architectures that predate modern cloud computing.
Sarat Mahavratayajula, an enterprise cloud architect, Sr. Software Engineer at Sherwin-Williams, and author of Software Engineering & Data Engineering in the Age of Cloud and AI, has spent over 13 years designing scalable platforms across private and public sector organizations. His earlier work on the GovGrants platform, a cloud-native grant management system built on Salesforce that processes more than 45,000 grant awards and over $47 billion in public funding each year, placed him directly inside the modernization challenge that most federal technology strategies only describe in abstract terms. Mahavratayajula’s experience offers a practitioner’s view into what it actually takes to move government systems off legacy infrastructure and onto platforms built for the demands of modern grant administration.
The True Cost of Keeping Legacy Grant Systems Running
Federal grants to state and local governments ranked among the top five categories of national expenditure in fiscal year 2025, when total federal spending reached $7.1 trillion. These grants fund healthcare delivery, K-12 education, highway construction, emergency preparedness, and dozens of other programs that touch nearly every American household. The systems administering those programs, however, often lag a generation behind the technology available to manage them. GAO data shows that the most critical federal legacy systems collectively consume approximately $337 million per year in maintenance costs alone, a figure that excludes the harder-to-measure expenses of security incidents, compliance gaps, and delayed program delivery.
Grant amendments illustrate the problem concretely. After an award is issued, agencies frequently need to adjust funding levels, extend timelines, or modify project scope. On legacy platforms, each amendment requires manual recalculation, paper-based approval routing, and disconnected audit documentation. Mahavratayajula confronted this exact bottleneck while architecting the Grant Management Amendment Module within GovGrants, where he built automated lifecycle management, version-controlled record updates, and integrated audit trails that replaced workflows previously dependent on spreadsheets and email chains.
“A single delayed grant amendment can hold up millions of dollars meant for classrooms or disaster recovery,” Mahavratayajula says. “When you trace the cause, it is almost always a systems problem. The people doing the work are capable. The platforms they are working on are not.”
What Cloud-Native Grant Architecture Actually Looks Like
Worldwide public cloud spending hit $723.4 billion in 2025 and is tracking toward $900 billion by 2026. Government and public sector cloud adoption has reached 57%, and more than 60% of government organizations are now prioritizing investment in business process automation. But adoption percentages obscure an important distinction: migrating a system to cloud hosting is not the same as redesigning it for cloud-native operation. Many government agencies have moved workloads to AWS or Azure without fundamentally rethinking the application logic, data models, or integration patterns underneath. The result is legacy architecture running in a cloud environment, incurring new hosting costs without capturing the efficiency gains that cloud-native design makes possible.
Mahavratayajula’s approach to GovGrants took the opposite path. Rather than lifting existing workflows into a hosted environment, he designed a modular Salesforce-native architecture where the grant lifecycle operates as a connected system. Application intake, evaluation, award generation, amendment processing, funding distribution, and compliance reporting all share a unified data model. He also built a DevOps deployment framework that enabled standardized, repeatable rollouts across multiple government customers, significantly reducing implementation risk and timeline. As an article reviewer for IEEE access, Mahavratayajula brings a research-grounded perspective to platform decisions that is uncommon in government technology projects.
“There is a difference between putting a legacy process in the cloud and building a cloud-native process,” Mahavratayajula explains. “If your amendment workflow still requires someone to manually recalculate funding in a spreadsheet and email it for approval, hosting that spreadsheet on AWS does not solve the problem.”
Compliance by Design, Not by Afterthought
Government grant programs operate under layered regulatory oversight. Federal agencies must satisfy OMB Uniform Guidance requirements, Single Audit Act provisions, and agency-specific financial reporting standards. Every modification to a grant award, whether a budget reallocation of $500 or a multi-million-dollar scope change, demands complete traceability. Nearly 95% of government IT leaders acknowledge that at least some portion of their cloud spending is wasted, and nearly half estimate that waste exceeds 25% of their entire cloud investment. When compliance infrastructure is bolted onto systems that were not designed for it, the waste compounds. This challenge is also reflected in his published work on content security policy drift in Salesforce Lightning environments, which analyzes how inconsistencies in embedded integration boundaries can lead to policy fragmentation and security exposure when enforcement is not tightly coupled with application architecture. Teams spend hours assembling audit documentation from disconnected sources rather than generating it automatically from transaction records.
The amendment module Mahavratayajula built for GovGrants treated compliance as an architectural constraint rather than a reporting layer. Every grant modification automatically generates a versioned record with timestamps, approval chains, and financial reconciliation data. Automated workflow orchestration routes amendments through the correct approval hierarchy without manual intervention, and integrated audit logging produces the documentation that regulators require without additional staff effort. Organizations using similar automated grant lifecycle platforms have reported productivity improvements of up to 35% over manual processes.
“Compliance is not something you layer on after the system is built,” Mahavratayajula observes. “If the architecture does not enforce traceability at the transaction level, every audit becomes a forensic exercise. That costs agencies more in staff time and risk exposure than the modernization itself would have cost.”
Scaling Across Agencies Without Rebuilding From Scratch
Over 90% of enterprises now use at least one cloud service, and 94% of large organizations have adopted cloud infrastructure in some form. Yet government technology procurement remains uniquely fragmented. Each agency operates under its own security accreditation, data governance policies, and workflow requirements. A grants management platform that works for one federal agency may require significant re-engineering before it can serve another. This fragmentation is one of the primary reasons legacy systems persist: agencies default to maintaining what they already have because the cost and complexity of deploying something new across their specific environment feels prohibitive.
Mahavratayajula addressed this directly by creating a DevOps deployment framework for GovGrants that standardized implementation patterns across multiple government customers. The framework treated environment-specific configuration as a variable rather than a custom build, allowing the core platform logic, data model, and compliance architecture to remain consistent while accommodating the regulatory and operational differences between agencies. That emphasis on standardized, secure deployment is also reflected in his published work on AI-enhanced DevSecOps pipelines, which explores how intelligent threat detection can be embedded directly into automated delivery workflows so that organizations can scale deployments without separating speed from security. This approach reduced deployment timelines and lowered the barrier for new agencies to adopt the platform without requiring the kind of bespoke development that makes government IT projects notoriously expensive. Mahavratayajula, who also serves as Vice Chair of the IEEE Eastern North Carolina Section (ENCS), applies this same principle of repeatable, standards-based design to his broader work in enterprise cloud architecture.
“The biggest barrier to modernization in government is not technology. It is the assumption that every agency needs a custom-built solution,” Mahavratayajula notes. “When you design for configurability instead of customization, you can deploy across agencies in weeks rather than years. That changes the economics of the entire conversation.”
From Systems of Record to Systems of Decision
By 2026, Gartner projects that more than 75% of government organizations will evaluate digital transformation by its sustained mission impact rather than by migration completion alone. The government cloud market is forecast to reach $145.2 billion by 2034, with security and compliance requirements accelerating procurement decisions. For grants management in particular, the next phase of modernization is about moving from systems of record, where data is captured and stored, to systems of decision, where real-time information shapes funding allocation, risk identification, and program performance evaluation.
Mahavratayajula’s GovGrants architecture anticipates this shift. By consolidating the full grant lifecycle into a platform capable of handling more than 45,000 awards annually within a unified data model, the system produces the structured, queryable datasets that agencies need to assess which programs are delivering results and where funding bottlenecks persist. Integration with federal systems like SAM.gov and Grants.gov reduces information silos and supports the cross-agency visibility that modernization strategies have promised for years. These architectural principles are consistent with Mahavratayajula’s published research, including a Google Scholar-cited study on cloud-native analytics frameworks that examines how streaming data architectures can power operational intelligence at enterprise scale.
“The real return on modernization is not that processes run faster,” Mahavratayajula reflects. “It is when the data starts working for you. When grant information flows through a platform designed for analysis, agencies can identify which programs are delivering outcomes, where funding is delayed, and how to reallocate resources before problems compound. That is the shift from recording what happened to informing what should happen next.”
