1) First things first – who are you?
Tell us your story beyond the LinkedIn bio! What’s your background, current role, and what gets you genuinely excited in the world of tech?
I’m Reshma Masutha A, a Computer Science Engineering graduate and now a Software Engineer Trainee at Udu Labs.
My journey into the data world didn’t start with expertise; it started with curiosity. One small step into databases slowly turned into a genuine passion for understanding how data powers everything around us.
What excites me the most is the way data can transform confusion into clarity, problems into solutions, and ideas into real, meaningful decisions. Every concept I learn feels like unlocking a new layer of how technology thinks.
Along the way, communities like Postgres Women India played a huge role in shaping my confidence. Their meetups, mentors, and knowledge-sharing opened doors I never expected and helped me discover that the world of data is not just deep, but incredibly empowering.
2) Why Data, Databases & PostgreSQL?
What hooked you? Was there a specific feature, project, or “wow” moment that made you choose PostgreSQL (or made PostgreSQL choose you)?
PostgreSQL chose me before I chose it!
My first real exposure came at the PostgreSQL Women India meetup in IITM. Until then, databases felt theoretical — but that day, I understood how powerful, elegant, and open PostgreSQL really is.
The “wow moment” was realizing how much control Postgres gives over data — indexing, JSONB, performance tuning — all while staying open-source and developer-friendly. That moment made me want to go deeper and explore PostgreSQL as a career direction.
3) What’s keeping you up at night (in a good way)?
What project or problem are you currently obsessed with? Share what you’re building, learning, or solving right now.
Right now, I’m obsessed with learning deeper internals — especially how PostgreSQL handles storage, indexing, and query planning under the hood.
At work, I’m exploring real-world database scenarios, and every new concept sparks more curiosity. Understanding performance, query optimization, and the architecture of modern data systems is what I’m constantly learning at the moment.
4) What’s been your biggest learning or challenge on this journey?
Tell us about a lesson learned, a mistake that taught you something, or that pivotal “aha!” moment. Bonus points if you can make the readers laugh about it!
My biggest learning on this journey is that databases look simple on the surface, but once you dive in, you realize how deep and complex they truly are. I started with the assumption that SQL was just basic select–insert–update, but the moment I encountered indexes, VACUUM, buffers, and EXPLAIN ANALYZE, everything changed — it felt like discovering a whole new world. Even creating a database through psql for the first time was completely new to me, and I remember being both excited and terrified at the same time. One memorable challenge was debugging a slow query for quite a while before realizing I had simply forgotten to create an index — a small detail that made a huge difference. These experiences have taught me patience, curiosity, and the importance of understanding the fundamentals rather than rushing through the basics.
5) If you could go back in time…
What’s one thing you’d tell yourself when you first started with Databases? What advice would have saved you hours of head-scratching?
I would tell myself:
“Don’t be scared of databases — they’re not as difficult as they look. Start small, practise consistently, and everything will click faster than you think.”
I’d also remind myself that community events and meetups are powerful: one meetup changed my entire direction, opened doors, and connected me with the people who helped me grow.
6) Your lightbulb moment
What’s one PostgreSQL concept or feature you finally understood and felt genuinely proud of? Was it understanding JSONB? Finally grasping indexes? Making sense of EXPLAIN ANALYZE? Tell us when it clicked!
My real lightbulb moment was the day I stopped running EXPLAIN ANALYZE and started reading it.
Understanding why a query was slow — seeing sequential scans, row estimates, timing — felt like unlocking a secret language of PostgreSQL. That moment changed the way I think about performance.
Another magical click was discovering JSONB. The idea that PostgreSQL could be relational and flexible at the same time felt like a superpower — structured tables living peacefully with semi-structured data in the same system.
These two concepts made me appreciate that PostgreSQL isn’t just a database… it’s a beautifully engineered system with depth, intelligence, and endless possibilities.
7) Who or what helped you grow?
A mentor, a community, a course, a blog, a YouTube channel, give a shoutout to whoever or whatever has influenced your learning the most. (Feel free to share links or names!)
The biggest influence in my learning journey has been the PostgreSQL Women India community. Their IITM meetup is what sparked my interest in databases, and the clear explanations from Aarti NR ma’am, Neeta Goel ma’am, and Gayathri Varadarajan ma’am gave me the confidence to explore PostgreSQL deeply. I’m also grateful to Balaji Krishnarajan, my CEO at Udu Labs, whom I first met at that meetup — his support helped me step into the data world.
Another strong support system has been the startup community created by GCT alumnus Vijay Chandrasekhar, which I joined through a friend. His guidance encouraged me to keep learning and stay consistent.
I also want to thank the React Chennai community, who boosted my confidence during my early meetups and inspired me to continue attending more events.
Together, these communities and mentors have played a major role in shaping my growth.
8) Describe your Data journey in one word.
Yep, just one! Make it count.
Transforming
Talk Title: PostgresML: Revolutionizing Machine Learning with SQL
In today’s data-driven world, organizations often struggle with complex machine learning infrastructures and data movement challenges. This talk introduces PostgresML, a game-changing PostgreSQL extension that brings machine learning capabilities directly into your database. We’ll explore how PostgresML enables developers and data teams to perform sophisticated ML operations using familiar SQL commands, eliminating the need for separate ML systems. Through live demonstrations, we’ll showcase practical implementations of model training, real-time predictions, and GPU acceleration features. Whether you’re a database engineer, ML practitioner, or technical lead, you’ll learn how to leverage PostgresML to simplify your ML pipeline, enhance security, and accelerate deployment. Join us to discover how this innovative tool is bridging the gap between traditional database operations and modern machine learning workflows.
Talk Title: Developers are decision-makers now. DevRel gets you there faster
DevRel as a role has existed since the 1990s, yet it remains one of the least understood roles in tech. Whether due to changing definitions, role titles, or evolving industries, DevRel has transformed significantly over the past few years—yet it continues to shape the devtool landscape. Since 2023, we’ve seen explosive AI growth alongside a surge in tech companies and technical talent. But who reaches these developers? Developers distrust traditional marketing. Who builds the samples, docs, tutorials, and SDKs they rely on? DevRel has become more critical than ever, especially as developers increasingly become decision-makers. In this talk, we’ll explore what DevRel is, how it drives impact, and how you can build an effective DevRel program.
Talk Title: DPDPA(Digital Personal Data Protection Act) Unleashed – Why It Matters for Women in Data
India’s Digital Personal Data Protection Act (DPDPA) is reshaping how organisations collect, store and use personal data, with a phased, 18‑month rollout. This presentation explores what’s in policy and law, then dives into what it unlocks for careers in data, security and consulting—especially for women. As data architect ,designing database architectures, will try connect legal constructs (Data Principals, Fiduciaries, Consent Managers, the Board) to real-world data and database practices, and show how DPDPA can be a powerful career accelerator, not just a compliance requirement.
Talk Title: Where Technology Meets Customer Needs: Lessons from a Newbie Solutions Engineer
When I stepped into the world of open-source databases as a Solutions Engineer, I expected to feel overwhelmed, but I found a role that made surprising sense. In this talk, I’ll share my journey navigating PostgreSQL with the help of modern cloud platforms like Aiven and DigitalOcean, tuning tools like DBtune, and migration partners like Hexacluster. This isn’t a deep-dive into internals, it’s a practical, beginner-friendly session to reducing the friction of managing PostgreSQL in real-world environments. Along the way, I’ll highlight the often-overlooked role of a Solutions Engineer: the human bridge between customer needs and engineering solutions. If you’re a student, a DBA, a DevOps engineer or just Postgres-curious, you’ll walk away with not only tools to explore, but also a career path to consider.

Talk Title: Architecting Ethical and Responsible AI with PostgreSQL 18
Have you ever developed an Agentic AI application using an agentic framework such as langGraph and pgai extension and noticed you don’t get good results during testing or the results are biased towards a demographic. You don’t know what to do. Organizations developing Agentic AI applications using an agentic framework such as LangGraph and pgai extension often encounter issues during implementation and testing, including suboptimal performance or bias in results such as demographic bias. Identifying the root causes of these issues can be difficult without proper tools and methodologies. This session addresses these challenges by introducing Responsible AI interpretability and explainability techniques. Participants will learn how to understand and trace the model’s decision-making process, enabling them to identify why specific results are generated. These capabilities are essential for meeting compliance requirements in regulated sectors, including banking and insurance. Attendees will gain practical knowledge on building Agentic AI applications that incorporate Responsible AI principles, ensuring transparent, accountable, and fair outcomes.
Rumi ![]()
Talk Title: New features of PostgreSQL 18
PostgreSQL 18 continues the PostgreSQL project’s long-standing focus on performance, scalability, reliability, and developer productivity, building incrementally on the improvements delivered in PostgreSQL 15–17.
Rather than introducing disruptive changes, PostgreSQL 18 is expected to emphasize refinement and maturity across core subsystems such as query execution, indexing, concurrency, replication, and observability, making PostgreSQL even more suitable for enterprise-scale and cloud-native workloads.
Talk Title: Platform Engineering Unpacked: Architecture, Evolution, and Hard-Won Lessons
The way engineering teams build and deliver software has changed dramatically. We’ve moved from manual server setups to automated pipelines, from ticket-based operations to self-service workflows, and from siloed teams to platform-driven organisations. This shift gave rise to Platform Engineering, a discipline focused on creating the internal systems, golden paths, and tooling that empower developers to move faster with less friction.
In this session, I’ll walk through the evolution that brought us here and why Platform Engineering has become a strategic priority across industries. I’ll share the architecture patterns that define successful platforms, how self-service emerges as a core capability, and the practical dos and don’ts learned from building real-world internal platforms.
Attendees will gain a clear understanding of:
Why DevOps wasn’t enough, and what Platform Engineering solves
The natural evolution from scripts → automation → abstractions → platforms
What makes a good platform (and what absolutely doesn’t)
How to design developer-centered systems and golden paths
My firsthand lessons from enabling engineering teams at scale
This talk gives a foundational, experience-driven view of what Platform Engineering really means today and how teams can start their journey the right way.
Our idea explores the implementation of AI-driven query optimization in PostgreSQL, addressing the limitations of traditional optimization methods in handling modern database complexities. We present an innovative approach using reinforcement learning for automated index selection and query plan optimization. Our system leverages PostgreSQL’s pg_stat_statements for collecting query metrics and employs HypoPG for index simulation, while a neural network model learns optimal indexing strategies from historical query patterns. Through comprehensive testing on various workload scenarios, we will validate the model’s ability to adapt to dynamic query patterns and complex analytical workloads. The research also examines the scalability challenges and practical considerations of implementing AI optimization in production environments.
Our findings establish a foundation for future developments in self-tuning databases while offering immediate practical benefits for PostgreSQL deployments. This work contributes to the broader evolution of database management systems, highlighting the potential of AI in creating more efficient and adaptive query optimization solutions.
This talk provides an introductory overview of Artificial Intelligence (AI) and Machine Learning (ML), exploring key concepts and their application in building intelligent systems. It will highlight the essential AI/ML techniques, such as supervised and unsupervised learning, and discuss practical use cases in modern industries. The session also focuses on how PostgreSQL, with its powerful extensions like PostgresML, TimescaleDB, and PostGIS, supports the development of AI-powered applications. By leveraging PostgreSQL’s ability to handle complex datasets and integrate machine learning models, participants will learn how to build scalable, intelligent solutions directly within the database environment.
Success is a multiplier of Action, External Factors and Destiny.
Out of these three, the only controllable aspect is our action. Again, action is the result of our EQ, IQ, SQ, and WQ (Willingness Quotient) together.
We all want to be successful and keep trying to motivate ourselves with external factors. We read inspirational books, listen to great personalities, and whenever possible upgrade ourselves with more knowledge and the list goes on.
Indeed these are excellent motivators, but in this process, we forget the most important source of energy, YOU!
We read other stories to feel inspired, thinking “I am not enough!”
But, the day we start accepting ourselves, introspect, understand, and align our life purpose with our routine, we find the internal POWER. This is a continuous source of motivation and energy which we need at down moments. When we feel, lonely, stuck and seek help, our inner voice is the greatest companion.
But, how many times do we consciously think about our “Subconscious”?
“Journey to Self” is our structured coaching program where we take back focus from the outside and delve deep inside to find our inner strength. Focusing on self-acceptance and personal growth
I believe everyone has POWER within them!
Let’s be the POWERHOUSE!
Human, AI, and Personalized User Experience for DB Observability: A Composable Approach
Database users across various technical levels are frequently frustrated by the time-consuming and inefficient process of identifying the root causes of issues. This process often involves navigating multiple systems or dashboards, leading to delays in finding solutions and potential downstream impacts on operations.
The challenge is compounded by the varying levels of expertise among users. It is essential to strike the right balance between specialized and generalized experiences. Oversimplification can result in the loss of critical information, while an overwhelming amount of data can alienate certain users.
Developers and designers are constantly navigating these trade-offs to deliver optimal user experiences. The integration of AI introduces an additional layer of complexity. While AI can provide personalized experiences within databases, it is crucial to maintain user trust and transparency in the process.
The concept of personalized composable observability offers a potential solution. By combining the strengths of human expertise, information balance, and AI-driven personalization, we can create intuitive and user-friendly experiences. This approach allows users to tailor their observability tools and workflows to their specific needs and preferences.