Speaker

Dr. Rahul Sharad Gaikwad

Dr. Rahul Sharad Gaikwad

Solutions Architect, AWS

Pune, India

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Dr. Rahul is a Solutions Architect at AWS, specializing in migrating and modernizing customer workloads on the AWS Cloud. He is a technology enthusiast with a keen interest in Generative AI and DevOps. He is recognised as APJC HashiCorp Ambassador. He received his Ph.D. in AIOps in 2022. He is recipient of the Indian Achievers’ Award (2024), Best PhD Thesis Award (2024), Research Scholar of the Year Award (2023) and Young Researcher Award (2022).

Area of Expertise

  • Information & Communications Technology

Topics

  • Artificial Inteligence
  • Machine Learning and Artificial Intelligence
  • Generative AI
  • Amazon Web Services
  • Cloud & DevOps

Improve operational performance by enabling Amazon DevOps Guru across multiple AWS Regions, accounts

This solution enables the Amazon DevOps Guru service across multiple AWS Regions, accounts, and organizational units (OUs) by using AWS CDK in TypeScript. You can use AWS CDK stacks to deploy AWS CloudFormation StackSets from the administrator (primary) AWS account.

CI/CD pipeline for hybrid workloads on Amazon ECS Anywhere by using AWS CDK and GitLab

This solution is designed to help those who use on-premises infrastructure to run container applications and use GitLab to manage the application code base. Customer can manage those workloads by using AWS Cloud services, without disturbing their existing, on-premises infrastructure.

Streamline your machine learning model deployment lifecycle with Terraform

Building and deploying custom ML models is often slow and error-prone, causing months-long delays. These challenges hinder customer innovation and responsiveness. In this session, we'll show how to use HashiCorp Terraform AWS and Cloud Control API (AWSCC) Provider to streamline and automate model preparation and deployment on Amazon Bedrock. This solution enables engineers to create environments and data scientists to develop custom models in under 30 minutes and accelerating model deployment lifecycle.

How to enhance architecture resiliency and deploy infrastructure with Amazon Q and Terraform

With the scale and complexity of modern architectures, building resilient and reliable infrastructure is a top challenge customers face in their cloud adoption journey. Generative AI offers a transformational approach to building resilient cloud architectures by providing failure mode and effects analysis (FMEA) , resiliency testing, catching bugs earlier in the development process, and more. In this session, learn how Amazon Q Developer helps customers built fault-tolerant infrastructure, develop custom chaos scripts, resilient infrastructure recommendations using infrastructure as code (IaC), and more, all without leaving the development environment.

Dr. Rahul Sharad Gaikwad

Solutions Architect, AWS

Pune, India

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