Dr. Rahul Sharad Gaikwad
Staff Resident Solutions Architect at HashiCorp, an IBM Company
Pune, India
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Dr. Rahul Gaikwad is a Staff Resident Solutions Architect at HashiCorp, an IBM company, and an AWS Ambassador and Community Builder. He is also an AWS Golden Jacket recipient. With over 15 years of experience in cloud architecture, DevOps, and AI-driven operations, he helps enterprises accelerate digital transformation and build scalable, automated cloud platforms.
Rahul holds a Ph.D. in AIOps and 3 Master’s degrees across engineering and technology disciplines. He has achieved all 12 AWS certifications and holds 35+ global technology certifications across cloud, DevOps, and platform engineering. His expertise spans Infrastructure as Code, platform engineering, and AI-driven infrastructure operations. He has delivered 40+ international technical talks across global conferences and community platforms.
His contributions to technology, research, and the global cloud community have been recognized with numerous honors including Top Icons of India, Man of Excellence, HashiCorp Ambassador, Indian Achievers Award, Best PhD Thesis, Research Scholar of the Year, Young Researcher Award, Best Scylla User Award at Scylla Summit, and Author of the Month by APG, AWS.
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Area of Expertise
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
Staff Resident Solutions Architect at HashiCorp, an IBM Company
Pune, India
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