Roman Spitzbart, VP, Solutions Engineers at Dynatrace, shares insights with Tahawultech.com on how the company is championing real-time observability, secure data governance, and AI-powered automation to support transparency and trust across regulated industries.
Interview Excerpts:
How is Dynatrace positioning itself to lead conversations around transparent and responsible AI governance in the enterprise space?
Responsible AI governance begins with real-time visibility. It’s not enough to identify issues after the damage is done. Dynatrace integrates observability into AI applications from day one, ensuring organisations can track, govern, and secure usage as it happens. In a climate where AI adoption often outruns regulatory readiness, Dynatrace helps enterprises maintain control, transparency, and due diligence.
How does Dynatrace’s Grail engine support traceability and explainability of AI models, particularly in regulated industries like banking and finance?
Grail provides deep visibility into every step of a transaction, including the AI layer—whether that’s a language model or inference engine. This aligns with our core approach of tracking end-user interactions across complex applications. In regulated industries, the focus is on preventing data intermingling. Dynatrace ensures that all AI interactions are contextually bound to each customer’s data, maintaining strict isolation to safeguard compliance.
With growing concerns about data privacy and compliance, how does Dynatrace ensure long-term data security and audit-readiness while maintaining rapid querying capabilities?
Our unified storage architecture eliminates the need to move data between hot and cold layers, which can compromise access controls. This design keeps data instantly accessible while retaining all security parameters. We rely on hyperscalers like AWS, Azure, and GCP for storage but enforce granular, built-in access controls. Every action is authenticated based on user rights, ensuring audit readiness and robust compliance without performance trade-offs.
How is the intersection of observability and AI governance evolving, and what role will Dynatrace play in this future?
AI governance is accelerating innovation, and observability must keep pace. Dynatrace is embedding automation and AI observability into the application lifecycle to ensure issues are preemptively managed. Our platform supports secure, cost-efficient deployment of AI systems by ensuring visibility isn’t an afterthought.
“We aim to help organisations monitor and optimise AI use at scale—without compromising compliance or budget.”
Given Dynatrace’s global footprint and access to sector-specific data, how do you ensure data sovereignty while enabling advanced insights like demand forecasting?
Data is an enterprise’s most valuable resource, but we treat it as our customer’s property. Dynatrace does not access or analyse customer data without explicit approval. Any such access follows a strict audit trail and customer-controlled process. Even as a SaaS provider, we do not bypass this. We ensure full data segregation and transparency, reinforcing trust in our role as a custodian, not an owner, of enterprise data.