Data Engineering Resources

Build AI Tools in Go With MCP SDK: Connect AI Apps to Databases

This article provides a hands‑on walkthrough for building MCP servers that integrate AI applications with Azure Cosmos DB.

January 20, 2026

by Abhishek Gupta

CORE

· 1,671 Views · 1 Like

Top 5 Payment Gateway APIs for Indian SaaS: A Developer’s Analysis

Compare 5 international payment APIs for Indian SaaS. Choose APIs that enable automated FIRC retrieval — and test the sandbox.

January 19, 2026

by Sarang S Babu

· 5,492 Views

Coding Exercise: Database Migration Tool in NodeJS

A practical example of a database schema migration tool written in pure NodeJS. We determine the requirements, design, and implement all components, including tests.

January 19, 2026

by Eduard Dykman

· 2,177 Views · 3 Likes

DeepSeek’s mHC: Manifold-Constrained Hyper-Connections, Explained for Practical Use

An overview of how DeepSeek’s manifold-constrained hyper-connections (mHC) stabilizes multi-stream residual networks while improving performance at scale.

January 19, 2026

by Praveen Kumar Myakala

· 1,574 Views · 2 Likes

Copilot, Code, and CI/CD: Securing AI-Generated Code in DevOps Pipelines

AI coding tools boost speed but weakens security and developer judgment. Here’s how hidden vulnerabilities escape review and what must change before a breach hits.

January 19, 2026

by Igboanugo David Ugochukwu

CORE

· 1,664 Views

RAG at Scale: The Data Engineering Challenges

The data engineering challenges that go beyond the basic concept of RAG when running RAG systems at scale in production.

January 16, 2026

by Guru Hegde

· 2,646 Views · 1 Like

Speeding Up BigQuery Reads in Apache Beam/Dataflow

Export BigQuery query results to GCS and read them in parallel with Beam; it’s dramatically faster and cheaper than reading directly from BigQuery.

January 16, 2026

by Rohit Muthyala

· 1,660 Views · 2 Likes

From RAG to RAG + RAV: A Practical Pipeline for Factual LLM Responses

RAG reduces hallucinations, RAV verifies each claim, and together they yield far more trustworthy LLM answers with optional corrections for accuracy.

January 16, 2026

by Sai Teja Erukude

· 4,311 Views · 3 Likes

From Chatbot to Agent: Implementing the ReAct Pattern in Python

This article provides a raw Python implementation, moving beyond high-level frameworks to show exactly how the agentic loop works under the hood.

January 16, 2026

by Nikita Kothari

· 2,769 Views · 2 Likes

Parallel S3 Writes for Massive Sparse DataFrames: How to Maintain Row Order Without Blowing Memory

Learn how to write massive sparse Pandas DataFrames to S3 without OOM errors by using Spark to parallelize index-based chunks while preserving row order.

January 16, 2026

by pooja chhabra

· 1,573 Views · 2 Likes

Integrating CUDA-Q with Amazon Bedrock AgentCore: A Technical Deep Dive

This integration lets AI agents use GPU-accelerated quantum simulations as tools in their workflows. Learn more in this deep dive.

January 16, 2026

by Rakesh Kumar Pal

· 1,640 Views · 1 Like

RAG on Android Done Right: Local Vector Cache Plus Cloud Retrieval Architecture

Most mobile RAG fails on latency and flaky networks. A local vector cache + cloud retrieval architecture keeps responses fast, fresh, and grounded.

January 16, 2026

by Mohan Sankaran

· 1,832 Views · 5 Likes

Securing AI-Generated Code: Preventing Phantom APIs and Invisible Vulnerabilities

AI coding tools accelerate delivery but create new security blind spots. Learn how phantom APIs emerge — and what developers can do to catch them early.

January 15, 2026

by Igboanugo David Ugochukwu

CORE

· 2,192 Views · 1 Like

DevSecOps for MLOps: Securing the Full Machine Learning Lifecycle

Why ML systems are uniquely vulnerable to security attacks — and how MLSecOps closes the gaps in data, models, and pipelines.

January 15, 2026

by Igboanugo David Ugochukwu

CORE

· 2,127 Views · 2 Likes

From Aspects to Advisors: Design Modular Cross-Cutting Features with Spring AI

Understand how Spring AI Advisors work and see how Aspect Oriented Programming concepts can be applied when interacting with LLMs.

January 15, 2026

by Horatiu Dan

CORE

· 2,338 Views · 5 Likes

Taming Reinforcement Learning Chaos: An MLOps Architecture for Experiment Management

Reinforcement learning is powerful, but managing thousands of iterations is a nightmare. Here is a practical architecture for building a lightweight experiment system.

January 15, 2026

by Dippu Kumar Singh

· 1,347 Views · 1 Like

Resilient API Consumption in Unreliable Enterprise Networks (TypeScript/React)

Build robust React clients with explicit timeouts, retries, circuit breakers, cancellation, idempotency, and optimistic UI, plus Axios–RTK Query integration guidance.

January 15, 2026

by Hanna Labushkina

· 3,467 Views · 3 Likes

Real-Time Recommendation AI Architecture: Streaming Events and On-Device Ranking

This Android recommendation architecture streams events to the backend and uses on-device ranking to deliver fast, resilient, privacy-aware recommendations.

January 15, 2026

by Mohan Sankaran

· 1,202 Views · 6 Likes