Data Engineering Resources

Finding bugs is what testing produces; understanding quality is why it exists. QA's future belongs to those who understand products, customers, and risks, not just bugs.

June 17, 2026

by Abhinav Garg

· 1,362 Views · 2 Likes

Parallel Kafka Batch Processing With Kotlin Coroutines in Spring Boot

Learn how Kotlin Coroutines improve Spring Boot Kafka batch processing with parallel execution, resource throttling, and faster database operations.

June 16, 2026

by Erkin Karanlık

· 2,222 Views · 1 Like

Cutting Data Pipeline Costs and Data Freshness Issues With Netflix Maestro and Apache Iceberg: A Practical Tutorial

Iceberg replaces filesystem state with a metadata tree (cheap queries, ACID snapshots). Maestro replaces cron with event signals (fresh data).

June 16, 2026

by Intiaz Shaik

· 5,067 Views · 2 Likes

Getting Started With GitHub Copilot CLI for Coding Tasks

This blog explores GitHub Copilot CLI, a terminal-based AI coding assistant that integrates with GitHub Copilot for users with a subscription.

June 16, 2026

by Gunter Rotsaert

CORE

· 1,277 Views

Your AI Is Not Failing, Your Context Is

RAG helps AI retrieve relevant data. GraphRAG connects entities and relationships. Context engineering turns both into accurate, safe, production-ready AI systems.

June 16, 2026

by Faisal Feroz

· 2,463 Views · 1 Like

Reducing RAG Hallucinations With Relationship-Aware Retrieval

An architectural idea and how it addresses the retrieval weaknesses that lead to hallucinations, with a reference implementation using RudraDB.

June 16, 2026

by Mahesh Vaijainthymala Krishnamoorthy

· 1,340 Views

Workflows vs AI Agents vs Multi-Agent Systems: A Practical Guide for Developers

Use workflows for control, agents for flexibility, and multi-agent systems only when complexity truly demands it. Add intelligence only where it makes a real difference.

June 15, 2026

by Raju Dandigam

· 11,461 Views · 3 Likes

Conversational Risk Accumulation: Stateful Guardrails Beyond Single-Turn LLM Checks

Learn how Conversational Risk Accumulation (CRA) helps detect session-level risks in long AI chats using telemetry, drift tracking, and soft guardrails.

June 15, 2026

by Sanjay Mishra

· 1,722 Views

Introducing RAI Audit Kit: Evidence-Grade Responsible AI Audits in Python

RAI Audit Kit is an open-source Python suite for repeatable, evidence-backed AI audits across ML, deep learning, LLMs, RAG, and agents.

June 15, 2026

by Sai Teja Erukude

· 2,292 Views

The Hidden Cost of AI-Generated Frontend Code

AI can create frontend code in a matter of seconds. However, subsequently, the team has to deal with reviews, accessibility, performance, and maintenance.

June 15, 2026

by Satyam Nikhra

· 1,366 Views · 1 Like

From ETL to Lakeflow: Shifting to a Declarative Data Paradigm

The article focuses on moving away from traditional, "imperative" ETL processes to a modern, "declarative" approach using the Databricks Lakeflow platform.

June 15, 2026

by Seshendranath Balla Venkata

· 1,920 Views · 1 Like

I Reverse-Engineered 50 API Breaches. The Same Five Mistakes Keep Appearing.

A cybersecurity and emerging tech correspondent analyzes 50 API breaches to reveal the five recurring mistakes behind major data exposures.

June 15, 2026

by Igboanugo David Ugochukwu

CORE

· 1,747 Views · 1 Like

Building a Vector Index in Azure AI Search: HNSW, Profiles, and RAG Retrieval

Use Azure AI Search as your RAG vector store. Build a Python example: define an HNSW vector index, upload embeddings, and run k-NN queries.

June 15, 2026

by Jubin Abhishek Soni

CORE

· 1,113 Views

Engineering Closed-Loop Graph-RAG Systems, Part 4: Evaluating a Graph-RAG System

Graph-RAG accuracy is only the starting point; evaluate the evidence path, rule compliance, latency, and feedback loop before calling it production-ready.

June 15, 2026

by Sriharsha Makineni

· 1,102 Views

Stop Loading Everything into Redshift: A Spectrum + Iceberg Pattern for Hybrid Analytics

Store large and cold datasets in Iceberg on S3, query them through Spectrum, and reserve Redshift local tables for workloads that need low latency or high concurrency.

June 12, 2026

by Vivek Venkatesan

· 2,087 Views

AI Assessments Are Everywhere

AI readiness assessments can spark valuable discussions, but self-reported scores have limits. Learn how to evaluate and apply them effectively.

June 12, 2026

by Rick Freedman

· 2,116 Views · 1 Like

Operationalizing Enterprise AI at Scale: Architecture, Governance, and Adoption

Enterprise AI success depends on scalable architecture, governance automation, AI operations, observability, and developer-first enablement strategies.

June 12, 2026

by Aravind Nuthalapati

CORE

· 2,074 Views · 3 Likes

Implementing the Planning Pattern With Java Enterprise and LangChain4j

Learn how to implement the Planning Pattern with Enterprise Java, Jakarta EE, CDI, and LangChain4j, enabling AI to transform business goals into executable workflows.

June 12, 2026

by Otavio Santana

CORE

· 1,865 Views · 1 Like

Engineering Closed-Loop Graph-RAG Systems, Part 3: Closing the Loop in Graph-RAG Systems

Closed-loop RAG needs feedback routing, not blind learning. Route signals carefully so the system improves without reinforcing bad answers.

June 12, 2026

by Sriharsha Makineni

· 1,346 Views

How to Build a Local LLM Agent to Automate Work List Generation from Monthly Reports (With Jira Integration)

Learn how a local LLM agent automates work list generation from reports, enriches tasks from Jira, detects duplicates, and keeps enterprise data secure.

June 11, 2026

by Sergey Laptick

· 2,675 Views · 2 Likes

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