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Topics

Development

Featured in Development

How to Use Apache Spark to Craft a Multi-Year Data Regression Testing and Simulations Framework

Vivek Yadav, an engineering manager from Stripe, shares his experience in building a testing system based on multi-year worth of data. He shares insights into why Apache Spark was the choice for creating such a system and how it fits in the "traditional" engineering practices.

All in development

Architecture & Design

Featured in Architecture & Design

Architecting Planet Scale, Modern Apps in the Cloud

George Mao shares a deep dive into evolving a basic web application to a planet-scale, global architecture. He walks through five stages of maturity, focusing on adding enterprise-grade security, achieving global high availability and disaster recovery, optimizing content delivery costs with CDNs, and implementing globally consistent persistence using serverless technologies.

All in architecture-design

AI Infrastructure

Featured in AI, ML & Data Engineering

Securing AI Assistants: Strategies and Practices for Protecting Data

Andra Lezza explains the criticality of data security for AI copilots, detailing the OWASP AI Exchange threat model and the OWASP Top 10 LLM risks. She reviews two copilot architectures - independent (single domain) and integrated (multi-tenant) - listing specific threats, controls, and best practices like granular authorization, templates, and DevSecOps to secure the entire AI data supply chain.

All in ai-ml-data-eng

Culture & Methods

Featured in Culture & Methods

Empowering Teams: Decentralizing Architectural Decision-Making

Peter Hunter & Elena Stojmilova share Open GI's journey from a slow, legacy monolith to a cloud-native SaaS platform. They detail how adopting Team Topologies and a decentralized architectural approach empowered teams. Key practices discussed include utilizing Domain-Driven Design to create a Context Map, implementing the Advice Process with Architectural Principles, and more.

All in culture-methods

DevOps

Featured in DevOps

Overload Protection: The Missing Pillar of Platform Engineering

Overload protection is often overlooked in platform engineering, leaving teams to create inconsistent, fragile fixes. Centralized rate limits, quotas, adaptive controls, and clear visibility give services predictable ways to handle traffic spikes, reduce reliability debt, and prevent cascading failures across systems.

All in devops

Events

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QCon AI New York 2025

Go from AI demos to real engineering impact. Learn to embed LLMs, govern & scale securely.

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InfoQ Architect Certification

Join Luca Mezzalira for this 5-week online cohort. Master socio-technical architecture leadership.

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QCon London 2026

Learn what works in AI, architecture, data, security & FinTech.

Early Bird ends Dec 20.

QCon AI Boston

Learn how leading engineering teams run AI in production—reliably, securely, and at scale.

Early Bird ends Jan 13.

Balakrishna Sudabathula

Profile page created Jun 10, 2025

AI & Cloud Transformation Expert| Enterprise Tech Strategist

Summary

Balakrishna Sudabathula is an Expert Software Engineering leader with over eighteen years of experience in AI, cloud migration, and API management. Specializing in scalable architecture and DevOps practices, he has led multiple digital transformation projects, optimizing API management through automation and innovative cloud solutions.

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Topics

How to Use Apache Spark to Craft a Multi-Year Data Regression Testing and Simulations Framework

Architecting Planet Scale, Modern Apps in the Cloud

Securing AI Assistants: Strategies and Practices for Protecting Data

Empowering Teams: Decentralizing Architectural Decision-Making

Overload Protection: The Missing Pillar of Platform Engineering

Helpful links

Choose your language

Balakrishna Sudabathula

Summary

Magika 1.0: Smarter, Faster File Detection with Rust and AI

HL is a Fast, Rust-Based JSON Log Viewer Offering up to 2GiB/s Parsing Speed

Lessons Learned in Migrating to Micro-Frontends by Luca Mezzalira at QCon SF

Breaking Silos: Netflix Introduces Upper Metamodel to Bring Consistency Across Content Engineering

Architecting Planet Scale, Modern Apps in the Cloud

Architecture Through Different Lenses 2025

Empowering Teams: Decentralizing Architectural Decision-Making

Leading from Any Position: Richard Bown on Humane Engineering Organizations

Learnings from Cultivating Machine Learning Engineers as a Team Manager

Five AI Security Myths Debunked at InfoQ Dev Summit Munich

Securing AI Assistants: Strategies and Practices for Protecting Data

Platform Engineering for AI: Scaling Agents and MCP at LinkedIn

Yelp Publishes Blueprint for Managing S3 Server-Access Logs at Massive Scale

Google Cloud Demonstrates Massive Kubernetes Scale with 130,000-Node GKE Cluster

Overload Protection: The Missing Pillar of Platform Engineering

QCon AI New York

QCon London

QCon AI Boston

InfoQ Software Architects' Newsletter

Balakrishna Sudabathula

Summary