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Nikhil Gopinath

VP of Engineering

Nikhil Gopinath is VP of Engineering at Sedai. Nikhil has also worked as a Solution Engineer and Data Scientist at H2O.ai and Teradata. Nikhil has experience in building analytical and machine learning solutions that help organizations adopt AI and ML solutions. Nikhil also has experience in providing Pervasive Intelligence, developing reusable IP, and working with large data sets. Nikhil has a Master's degree in Information and Data Science from UC Berkeley School of Information.

Cutting Serverless Latency by 50 with Autonomous Optimization

In this article, we will explore the world of optimization, with a special focus on serverless functions, particularly those leveraging Lambda. We will dive into how Sedai, a cutting-edge solution, helps in optimizing serverless functions. Sedai offers invaluable insights and tools that enable businesses to identify and address niche areas where optimization can make a significant impact.
Published on
August 22, 2022

Autonomous Builds on Observability: Picking the right metrics

Learn strategies for enhanced system performance and reliability. See how observability metrics lay the foundation for autonomous systems, and how Palo Alto Networks approaches production metrics. Explore the potential problems associated with an overwhelming influx of data and metrics and how ML-driven correlation analysis can identify truly predictive metrics in an environment with multiple monitoring providers, multiple resource types, real-time data stress and predictive analytics. See how Palo Alto Network uses a multi-stage approach that includes a notice filter, aggregation, analysis, auto-remediation and notifications.
Published on
August 22, 2022

The End of Cold Starts: Autonomous Concurrency for AWS Lambda

A comprehensive overview of how Sedai addresses the challenge of cold starts through the implementation of autonomous concurrency. We explore the history of cold starts, their underlying causes, and their relationship with concurrency before showing how an AI based approach can resolve cold starts.
Published on
August 22, 2022

A New Way to Virtually Eliminate Cold Starts for AWS Lambda: Autonomous concurrency 

Serverless computing has many benefits for application development in the cloud. It’s not surprising that given its promise to lower costs, reduce operational complexity, and increase DevOps efficiencies, serverless adoption is gaining more momentum every year. Serverless is now seeing an estimated adoption rate in over 50% of all public cloud customers. However, one of the prevailing challenges for customers using serverless has been performance, specifically “cold starts.” Here, I want to explore all the popular remedies available to reduce cold starts, their benefits, and pitfalls, and finally, how a new autonomous concurrency solution from Sedai may be the answer to solving cold starts once and for all.
Published on
November 28, 2022

Improving Lambda Performance & Availability at Scale with the New AWS Telemetry API

Sedai is a launch partner for AWS for their new Telemetry API for AWS Lambda. Sedai uses the telemetry API to improve availability for Lambda users of Sedai’s autonomous cloud management platform by providing additional insights and signals on Lambda functions on a cost-effective basis.
Published on
October 26, 2022

The End of Cold Starts: Autonomous Concurrency

Cold starts are the #1 performance problem for Lambda users. Autonomous concurrency provides a solution with fewer cold starts than warmup strategies, and lower cost than provisioned concurrency. Sedai VP of ML, Nikhil Gopinath explains the underlying challenge of cold starts and presents the autonomous concurrency solution and compares it to traditional solutions.
Published on
May 26, 2024

Autonomous FinOps: The Future of Cloud Cost Management

The role of autonomous FinOps in overcoming obstacles.
Published on
May 26, 2024

Empowering Modern App Developers in the Autonomous Cloud Era

Optimizing Kubernetes at Bill and serverless environments at Velocity Global
Published on
May 26, 2024