ONLINE | MARCH 11-12, 2026
Discover how your peers are approaching real-time engineering challenges at massive scale.
Connect with other engineers designing, implementing, and optimizing systems that are pushed to their limits.
Roll up your sleeves and master best practices for predictable low latency at high throughput.
I am Staff software engineer at Rivian VW group, I have been a founding engineer at Rivian from October 2021 and we have built the entire realtime stream processing stack here. I am passionate about Realtime stream processing using Apache Flink, Kafka, Schema registry, Druid, Pinot, web application development using Spring-Boot MVC micro services framework, React and Javascript. Prior to Rivian, I was at Yahoo in feed Personalization team where I worked on streaming data for feature engineering and worked closely with data scientists to serve relevant content to users across Yahoo homepage, Yahoo finance etc.
At Stony Brook, Data Science, AI, Operating Systems, Database systems have been my favorite subjects to study. I am passionate about Systems, Networking, Machine Learning. I like to describe myself as a problem solver and I am never shy of adapting to a new technology, tool or language to solve a given problem.
Nishant Lakshmikanth is an Engineering Leader at LinkedIn, with over 12 years of experience designing and leading large-scale distributed systems and infrastructure. He currently drives LinkedIn’s recommendation infrastructure, including the People You May Know (PYMK) system, a critical initiative responsible for generating millions in annual revenue, engaging over one billion members worldwide. His work integrates cutting-edge technologies like graph-based models, entity-based recommender systems, and advanced machine learning frameworks.
In the realm of machine learning infrastructure, Nishant has spearheaded the development of distributed training systems, real-time feature population pipelines, and solutions for remotely hosting complex models, enabling seamless integration of large-scale AI systems into production environments and ensuring their accessibility and reliability. He has also contributed to building highly reliable tracking systems, GPU optimizations, and cost-efficient large language model (LLM) deployments tailored for recommendation systems, advancing the scalability and efficiency of LinkedIn’s ML-powered products.
Before LinkedIn, Nishant held key engineering roles at Amazon Web Services and Cisco. At AWS, he contributed to Elastic Block Storage (EBS), where he designed a distributed volume placement system and optimized replication strategies, earning seven patents. At Cisco, he advanced video streaming and encoding technologies, demonstrating expertise in backend systems.
Nishant’s technical contributions extend beyond systems design to fostering innovation, mentoring engineering talent, and advancing engineering standards. His extensive experience with control plane for managing complex distributed systems, bootstrapping cloud services and building machine learning infrastructures places him at the forefront of innovation.
Murat Demirbas is a Principal Research Scientist at MongoDB Research. Before joining MongoDB, he was a Principal Applied Scientist at AWS for 3 years, and a Professor of Computer Science at the University at Buffalo (SUNY) for 16 years. His work spans distributed systems and databases, with contributions to hybrid logical clocks, WPaxos, PigPaxos, and Paxos Quorum Reads. He received the NSF CAREER Award in 2008 and the UB School of Engineering Senior Researcher of the Year Award in 2016. Murat writes a widely read blog on distributed systems at http://muratbuffalo.blogspot.com, with over 5.6 million views.
Karthik Deivasigamani is VP Architect at MoEngage, leading their efforts to build a scalable MarTech SaaS platform. He helped Noon build their social learning graph that helped students discover the right content and teachers. Earlier at Walmart Labs, he was instrumental in developing a product knowledge graph for Walmart eCommerce to help customers discover products easily. He has also spent considerable time at Yahoo! working on their homepage and content recommendation systems.
Guruguha is a Staff Software Engineer at Rivian Volkswagen Group Technologies, where he leads multiple real-time data initiatives, mainly on event-driven platforms that cut across different domains. Some of the aspects include real-time event detection platform for telemetry data, near real-time ML inference platform for pre-trained ML models on vehicle telemetry.
Avi, CTO of ScyllaDB, is known mostly for starting the Kernel-based Virtual Machine (KVM) project, the hypervisor underlying many production clouds. He has worked for Qumranet and Red Hat as KVM maintainer until December 2012. Avi is now CTO of ScyllaDB, a company that seeks to bring the same kind of innovation to the public cloud space.
Dor is the CEO of ScyllaDB. Previously, Dor was part of the founding team of the KVM hypervisor under Qumranet that was acquired by Red Hat. At Red Hat Dor was managing the KVM and Xen development for several years. Dor holds an MSc from the Technion and a Phd in snowboarding.
Chris Riccomini is a software engineer, startup investor, and advisor, and author with more than 15 years of experience at major tech companies such as PayPal, LinkedIn, and WePay. He has been involved in open source throughout his career and is the author of Apache Samza. He’s co-author of The Missing README: A Guide for the New Software Engineer, and writes Materialized View, a weekly infrastructure newsletter.
Tzach has a B.A. and MSc in Computer Science (Technion, Summa Cum Laude), and has had a 15 year career in development, system engineering and product management. In the past he worked in the Telecom domain, focusing on carrier grade systems, signaling, policy and charging applications.
Tim has had his hands in all forms of engineering for the past couple of decades with a penchant for reliability and security. He served in the Australian Regular Army after completing his Bachelor of Information Systems (Honors) and retiring at the rank of Captain. In 2013 he founded Flood IO; a distributed performance testing platform. After it was acquired, he enjoyed scaling the product, business and team before moving on to other performance-related endeavors.
Benjamin Cane is a Distinguished Engineer at American Express, where he plays a pivotal role in the architecture, design, and engineering excellence of the Acquirer and Network Payments Platforms. With a focus on cloud-native technologies and practices, Ben specializes in building mission-critical and high-performance systems. His expertise has been instrumental in driving the evolution of American Express’ cloud-native payments platform. Beyond his contributions to American Express, Ben is an active open-source community member and has contributed to various projects.
30+ interactive sessions that explore “monster scale” challenges related to ScyllaDB, the monstrously fast database, and broader at-scale engineering feats. Industry experts share emerging trends, architecture deep dives, experience reports, infrastructure innovations, and hands-on labs.
The Monster Scale Summit community is all about discussing strategies for meeting performance expectations at extreme scale. Whether you’re designing, implementing, or optimizing systems that are pushed to their limits, we’d love to hear about your most impressive achievements and lessons learned.