ÜberConf - July 18 - 21, 2017 - No Fluff Just Stuff

Rohit Bhardwaj

ÜberConf

Denver · July 18 - 21, 2017

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Rohit Bhardwaj

Director, AI & Data Architecture at Salesforce | Author | Enterprise AI

Rohit Bhardwaj is a Director of AI & Data Architecture at Salesforce, where he focuses on enterprise AI, agentic systems, cloud-native architecture, distributed systems, data platforms, security, and large-scale transformation.

Over his career, Rohit has designed and led complex enterprise platforms across AWS, Google Cloud, microservices, real-time data, API ecosystems, resilient distributed systems, and AI-enabled architectures. His work increasingly focuses on the challenges enterprises face as software evolves from deterministic services to AI-native and agentic systems—particularly around reliability, governance, evidence, security, observability, cost, and safe autonomy.

Rohit is the author of System Design with AI Interview Guide: Designing Scalable, Agentic, and Defensible Systems, published by Apress. The book presents a modern approach to system design covering scalability, distributed systems, AI architecture primitives, security, reliability, economics, agentic systems, and real-world architectures including e-commerce, ride sharing, payments, fraud detection, messaging, video streaming, file storage, and search. (Springer Link)

Book:
Amazon: https://a.co/d/09Zs1twa
Publisher / Springer Nature: https://link.springer.com/book/10.1007/979-8-8688-2782-2
O'Reilly: https://learning.oreilly.com/library/view/system-design-with/9798868827822/ 

Rohit is also an O’Reilly instructor and a frequent speaker at technology conferences including No Fluff Just Stuff, UberConf, GIDS, and other international events. His talks focus on practical architecture lessons from building and operating complex systems, including AI control planes, trusted agents, inference at scale, evidence-first RAG, AI security, distributed-system failure, and AI-era software architecture.

As a trusted advisor and architecture leader, Rohit works at the intersection of business strategy and deep technical architecture—helping teams translate complex business problems into scalable, resilient, secure, and economically sustainable systems.

Rohit holds an MBA in Corporate Entrepreneurship from Babson College and graduate-level education in Computer Science from Boston University and Harvard University.

Connect with Rohit:
LinkedIn: http://linkedin.com/in/rohit-bhardwaj-cloud
X / Twitter: @rbhardwaj1

Presentations

Apache Cassandra, Spark and Spark Streaming for Real Time Big Data Analytics

Apache Cassandra is one of the best solutions for storing and
retrieving data. We will explore data analytics cluster computing
framework with real-world examples. It is 100x faster than Hadoop!
We will start with an introduction to Apache Cassandra. We will explore challenges encountered when attempting to scale
with relational databases, and how NoSQL databases like Cassandra address those problems. It reviews the Cassandra architecture, benefits, and how to use the Cassandra read and write paths.

Later, you will learn how to effectively and efficiently solve analytical problems using Apache Spark, Apache Cassandra, and DataStax. You will learn about Spark API, Spark-Cassandra Connector, Spark SQL, Spark Streaming, and fundamental performance optimization techniques.
Big Data applications nowadays require a faster speed of data
processing and analysis.

Solving Analytical Problems using Apache Spark and Cassandra

This talk will explore why Spark is the most prominent solution compared to Hadoop. We will look at MapReduce and how Spark makes the creation of Big Data algorithms simple and faster. Next, we will explore Spark Context and how Resilient Distributed Dataset (RDD) helps establish Directed Acyclic Graph (DAG); Transformations using map and filter; Actions using collect, count, and reduce. Later we will explore the Spark Cassandra connector. We will look at Spark API and Spark SQL.

Key takeaways from this talk will be for a developer and architect to understand how Apache Spark and Apache Cassandra help implement enterprise-level analytical solutions. It is 100x faster than Hadoop!