Behind every seamless digital experience is an infrastructure team working hard to keep systems scalable, responsive, and resilient. In this episode of IT Infrastructure as a Conversation, I’m joined by Jesmar Cannaò, COO of ProxySQL, to explore the story behind one of the most trusted open source tools in database management today.

What began as a side project born from the frustrations of a single DBA has evolved into a critical component for teams managing MySQL and PostgreSQL environments around the world. Jesmar walks us through the origins of ProxySQL and explains how it empowers DBAs by placing intelligent query routing, load balancing, and failover handling directly in their hands.

We discuss the architectural advantages of ProxySQL in both cloud-native and on-premise setups, its ability to operate with minimal friction inside Kubernetes, and why open source remains at the heart of its mission. Jesmar also offers a candid look at what it takes to build a distributed team, maintain performance across time zones, and foster a global community of contributors and users.

As database architectures grow more complex and DBA roles continue to shift, ProxySQL is evolving to meet those changes head-on. With the recent alpha release of its PostgreSQL protocol support and plans to expand further in 2025, Jesmar outlines how the team is staying ahead of industry demand.

Whether you're a database engineer, a cloud architect, or simply someone trying to future-proof your infrastructure, this conversation is full of practical insight into what open source can offer in a fast-changing world.

Explore more at proxysql.com and join the conversation around high-performance infrastructure that does not compromise on transparency, flexibility, or control.

In a world where business users expect instant insights from tools like Power BI and Tableau, few stop to consider the heavy lifting happening behind the scenes. Dashboards may look simple, but the infrastructure powering them often involves layers of complex data engineering, expensive queries, and frustrating delays. This mismatch is what Nicolas Korchia, Co-founder and CEO of Indexima, calls the BI paradox.

In this episode of IT Infrastructure as a Conversation, Nicolas joins Neil to explore how Indexima is solving this issue by automating the most painful parts of business intelligence. Rather than forcing engineers to build yet another manual data pipeline, Indexima uses AI to identify query patterns and automatically generate dynamic tables directly within Snowflake. The outcome is faster dashboards, lower compute costs, and a smoother experience for analysts and engineers alike.

We unpack how Indexima’s engine monitors live dashboard usage, detects inefficiencies, and rewrites queries on the fly to target optimized aggregation layers. This not only improves performance but also contributes to sustainability by reducing the volume of data scanned and processed. For organizations under pressure to balance data speed with environmental impact, it is a practical and forward-looking approach.

Nicolas also shares real-world use cases from retail and finance, where customers have slashed dashboard load times from minutes to milliseconds and eliminated the need for nightly data extracts. The conversation touches on broader trends too, including the role of large language models in BI workflows and how tools like ChatGPT might soon assist in building semantic layers.

For anyone responsible for scaling data infrastructure, this episode provides a grounded look at how automation is reshaping BI from the ground up. If your teams are still wrestling with slow dashboards and spiraling query costs, this is a conversation worth listening to.

What if the future of analytics was not about working harder, but about letting your infrastructure work smarter?

As AI agents begin to influence how businesses operate, there's growing urgency around building infrastructure that supports their complexity without adding new risks. In this episode of IT Infrastructure as a Conversation, I speak with Alexander Alten, Co-Founder and CEO of Scalytics, about the architecture powering the next generation of AI and machine learning systems.

Alexander’s journey includes leadership roles at Cloudera, Allianz, and Healthgrades, and a deep commitment to building scalable, privacy-respecting technologies. At Scalytics, he's helping organizations avoid the limitations of centralizing data by building distributed systems that support federated learning. Rather than extracting and duplicating data across systems, Scalytics enables analysis directly at the source, making it easier for businesses in regulated industries to innovate with confidence.

Recorded live at the IT Press Tour in Malta, our conversation dives into the origins of Scalytics Connect, the company's AI agent infrastructure that leverages open-source frameworks like Apache Wayang. We explore why ETL pipelines often create fragility instead of flexibility, how decentralization supports both compliance and collaboration, and why open-source technologies continue to outperform closed systems over the long term.

For any CIO, CTO, or data architect looking to align AI capabilities with real-world constraints, Alexander’s perspective offers a refreshingly pragmatic path forward. His framework simplifies the complexity of federated machine learning while preserving data sovereignty, auditability, and future-proof flexibility.

If your organization is struggling with data silos, regulatory friction, or the scaling of AI models, this episode offers insight into a model that avoids duplication, improves trust, and accelerates results by treating infrastructure as the foundation for intelligent systems.