With over 20 years of expertise in enterprise software, infrastructure, and security and a track record that includes leading WatchDox to a successful acquisition by BlackBerry, Moti is passionate about building scalable solutions and driving innovation in application architecture.
In this interview, Moti discusses how vFunction uses AI-driven tools to help organizations reduce architectural technical debt, simplify their systems, and ensure long-term scalability and resilience.
M.R. Rangaswami: What are the challenges with software engineering and application development that inspired you to found vFunction?
Moti Rafalin: Application architecture is one of the most impactful factors for improving application scalability, resiliency, and long-term competitiveness. While technical debt is a well-known issue, its most common and damaging form – architectural technical debt (ATD) – is especially enigmatic, causing severe performance issues that result in lost revenue opportunities, delayed projects, and customer churn. Despite the risks associated with technical debt, many companies continue to focus on new development at the expense of architectural sustainability. This short-term focus often results in what we refer to as the “boiling frog syndrome,” where the gradual accumulation of technical debt goes unnoticed until it’s too late. Without addressing technical debt, applications require large modernization projects every three to five years, diverting an organization’s energy and resources from new development.
vFunction was founded to tackle this problem by providing the first AI-driven architectural observability platform, enabling teams to proactively reduce complexity, manage ATD, and ensure their applications remain resilient and scalable as business demands evolve. vFunction’s platform initially focused on understanding and visualizing the dependencies between business domains, thereby enabling organizations to efficiently break down overly complex monolithic applications into manageable components. This not only reduces ATD but also allows teams to unlock cloud-native benefits like elasticity and scalability, ensuring their systems can evolve efficiently with market demands. vFunction’s architectural observability platform has evolved to support microservices, focusing on preventing the accumulation of technical debt in distributed environments by mapping microservices dependencies, detecting drift and architectural issues, and enabling rules-based governance.
M.R.: What is architectural observability? How is it unique? And how does it differ from other application observability platforms?
Moti: Architectural observability is the ability to analyze an application’s architecture, mainly through learning its dynamic flows, to gain deep insights into its structure, detect architectural drift, and identify and address complexity and technical debt. Unlike application observability platforms that focus on symptoms of problems, like poor performance and outages, architectural observability shifts left, focusing on the core architectural issues and drift that are the root cause of many performance and scalability issues. Architectural observability connects the dots between architectural decisions and their impact on overall business goals, offering a holistic view of how architecture evolves over time and how it influences application quality and technical debt.
vFunction’s AI-driven architectural observability platform is unique in its ability to analyze and visualize the architecture across a company’s entire app portfolio, using its patented dynamic code analysis and offering actionable insights that help teams continuously reduce complexity. vFunction leverages OpenTelemetry to understand and address complexity for any microservices stack. It empowers engineering leaders to quickly pinpoint mission-critical technical debt, continuously simplify their applications, and ensure their development cycles contribute directly to the organization’s high-level objectives. With intuitive visualizations and AI-powered benchmarking, vFunction allows architects and technical leads to make informed application decisions, while developers can focus on delivering new features or refactoring with the support of intelligently prioritized tasks. This level of transparency and direction ensures that all team members can track their progress and contribute to the organization’s success without introducing new risks or unknowns.
M.R.: Neglecting software complexity and technical debt threatens long-term business growth. How can companies take a strategic, proactive approach to reduce complexity and prioritize technical debt?
Moti: A strategic, proactive approach to reducing software complexity and prioritizing technical debt begins with consistently measuring, prioritizing, and resolving technical debt. This approach offers a clear path for organizations to manage this challenge in a phased, scalable way:
- 1) Measure technical debt continuously, gaining real-time insights into how close the organization is to the “boiling point” where accumulated debt starts to erode engineering velocity, compromise application security, and limit scalability. This requires dedicating engineering resources to ongoing remediation efforts, rather than waiting for a system failure or tackling technical debt only during large, often inefficient, modernization projects.
- 2) Once technical debt is identified and measured, the next step is to prioritize the most critical issues. This involves reviewing the data and focusing on KPIs that prevent the issue from reaching a boiling point.
- 3) In the most mature phase of technical debt management, organizations make a strategic decision to invest more heavily in continuous remediation efforts. The entire engineering team, including architects, SREs, and application owners, fully engage in this process. Together, they work to modernize the application architecture, prevent architectural drift, and build scalable, resilient systems on an ongoing basis.
The platform’s architectural governance capabilities enable organizations to combat microservices sprawl by setting and enforcing rules that prevent drift and ensure alignment with design intent. Meanwhile, comprehensive user flow analysis features for microservices align design intent with actual implementation to keep architectural integrity intact while accelerating development.
vFunction’s platform supports organizations at every stage of this maturity model by offering AI-driven tools that identify, prioritize, and help remediate technical debt. Whether the organization is just beginning to measure the scope of its technical debt or is ready to invest fully in its resolution, vFunction provides the observability, governance, and automation necessary to guide that journey.
By adopting this strategic, phased approach to technical debt, companies can reduce complexity, protect long-term application resiliency and scalability, and position themselves for sustainable innovation and growth.
M.R. Rangaswami is the Co-Founder of Sandhill.com