Jayachandra Reddy Majjiga
Empowering DevOps and Cloud Innovations with Automation, Kubernetes and AI.
Bengaluru, India
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An experienced Senior Cloud Platform Engineer with a passion for driving innovation in DevOps, Cloud and AI/ML. I bring extensive expertise in AWS, Kubernetes, Terraform and Infrastructure as Code (IaC) and have delivered engaging presentations on topics like deploying infrastructure with Terraform and its advantages. Holding certifications in AWS, Kubernetes, and Terraform, I am continually expanding my skillset and currently aiming for Kubestronot certifications. Beyond work, I enjoy playing badminton, going for long drives and once reached a top speed of 180+ km/h in my car.
Area of Expertise
Topics
Modernizing Database Connectivity: Secure RDS Access via AWS Systems Manager
Managing secure database access for large teams is challenging, especially when dealing with VPNs, bastion hosts and credentials management. AWS Systems Manager (SSM) provides a more secure and scalable way to connect from local laptops to AWS RDS without exposing databases to the internet or using static credentials.
we will explore how to leverage AWS Systems Manager Session Manager and AWS IAM authentication to securely connect to Amazon RDS, reducing operational overhead and improving security posture.
This session is ideal for Platform Engineers, Security Teams and DevOps Engineers looking to improve secure database connectivity at scale while eliminating traditional networking complexities.
Kubernetes Cost Optimization – Stop Overprovisioning & Reduce Cloud Bills
Kubernetes makes it easy to deploy and scale applications, but cost management is often overlooked, leading to unnecessary cloud expenses. Over provisioned resources, inefficient autoscaling and idle workloads can significantly inflate cloud bills.
In this session, we will dive into practical strategies to optimize Kubernetes costs while maintaining performance and reliability. We’ll explore:
Common cost pitfalls in Kubernetes environments.
Right-sizing workloads using Vertical Pod Autoscaler (VPA) & Horizontal Pod Autoscaler (HPA).
Karpenter for dynamic, cost-effective node provisioning.
Monitoring cost & resource usage using OpenCost, AWS Cost Explorer, and Kubernetes-native tools.
Real-world best practices for cutting unnecessary expenses without impacting performance.
This session is designed for Cloud Engineers, DevOps Teams, SREs and FinOps Practitioners who want to gain actionable insights into reducing cloud costs while ensuring efficient Kubernetes operations.
From Chaos to Control: Simplifying Kubernetes Admission Policies with Kyverno on EKS
As Kubernetes adoption grows, clusters often become a mix of inconsistent configurations, missing security controls, and broken operational standards. Teams rely on documentation and code reviews to enforce best practices, but in production this is rarely enough. What’s needed are guardrails that work automatically, without slowing developers down.
In this talk, we’ll explore how Kubernetes admission control can be used to enforce security and operational standards, and why traditional approaches using custom webhooks or complex policy engines often create more friction than value. We’ll then introduce Kyverno, a Kubernetes-native policy engine that uses familiar YAML instead of custom policy languages, making policy-as-code approachable for both platform and application teams.
The session will include a live demo showing how misconfigured workloads are prevented or automatically fixed at admission time, and how teams can gradually roll out policies without breaking existing applications.
From Chaos to Control: Designing and Scaling an Internal Developer Platform on Kubernetes
Many teams adopt Kubernetes expecting faster delivery and better scalability, but end up with inconsistent deployments, manual governance, duplicated infrastructure, and frustrated developers.
In this session, I’ll walk through how we designed and evolved a production-grade Internal Developer Platform (IDP) to standardize delivery, enforce guardrails, and improve developer experience, while running on Amazon EKS.
This talk goes beyond theory and covers:
Designing golden paths for developers
Structuring infrastructure with Terraform
GitOps-based application delivery workflows
Multi-namespace governance patterns
Centralized logging architecture (Kinesis → OpenSearch pipeline)
Platform guardrails without blocking innovation
Trade-offs we faced and mistakes we corrected
We’ll discuss how the platform evolved from ad-hoc Kubernetes management to a structured, product-oriented internal platform.
While this implementation runs on Amazon EKS, the architectural patterns, governance strategies, and platform principles discussed are cloud-agnostic and applicable to any Kubernetes environment.
Key Outcomes Shared
Reduced onboarding time for new services
Improved deployment consistency across teams
Reduced policy violations through built-in guardrails
Improved observability through standardized logging patterns
Attendees will leave with a practical blueprint for building or maturing their own Internal Developer Platform — grounded in real implementation experience.
Building Production-Ready Serverless Generative AI Workflows on AWS using Step Functions and Amazon
Generative AI unlocks powerful new capabilities, but integrating it into production systems requires thoughtful architecture and operational discipline. In this session, we will explore how to design and build a scalable, secure, and cost-efficient serverless Generative AI workflow using AWS Step Functions, AWS Lambda, and Amazon Bedrock.
Using a practical document intelligence use case, we will demonstrate how serverless orchestration can automate document summarization, structured data extraction, and report generation without managing infrastructure. We will also cover key considerations such as prompt workflow design, error handling, security controls, and observability.
Attendees will gain practical insights into building production-ready Generative AI pipelines using AWS managed services and learn architectural patterns that can be applied across multiple real-world enterprise use cases.
Building a Production-Ready Kubernetes Platform: From App Templates to Resilient Operations
Platform engineering is not just about operating Kubernetes clusters—it is about enabling teams to build, deploy, and run applications reliably and repeatedly. In this session, I will walk through how to design a practical Kubernetes platform on Amazon EKS that balances strong operational foundations with a smooth developer experience.
The talk covers application definition using standardized templates, workload foundations such as resource management and autoscaling, and orchestration patterns for multi-environment deployments. I will also explain how policy-driven controls and automation help enforce best practices without slowing down delivery.
Finally, I will share operational resilience strategies for handling node failures, rolling upgrades, and common production incidents while keeping services available. The session is based on real production scenarios and focuses on actionable patterns that platform and DevOps teams can adopt immediately.
Simplifying Admission Controls in Kubernetes with Kyverno
In today's Kubernetes environments, ensuring security, compliance and best practices at scale can be complex. Traditional admission controllers rely on custom webhooks and intricate coding, making policy enforcement cumbersome. Kyverno, a Kubernetes-native policy engine, streamlines this process by allowing declarative, YAML-based policies without requiring external webhooks.
This session will demonstrate how Kyverno automates policy enforcement, validates resource configurations and dynamically mutates workloads. We will explore real-world use cases, including restricting privileged containers, enforcing Horizontal Pod Autoscaler (HPA) requirements and auto-generating security policies, helping teams achieve robust governance with minimal effort.
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