Projects using Kafka
Projects using Kafka
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Bob Cardenas
pro
Event Broker – Real-Time Payment Streaming
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10
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vansh patel
max
Watchman: security operations and threat triage dashboard
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2
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Aduraleke faith Akintade
Accessing my kafka cluster with EKS
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130
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Allen Tang
pro
During my five years at Wayfair (2015–2020), I spent my first two years building internal tools within Warehouse Management Systems. As the demands of our data workflows evolved, my work naturally led me to transition our legacy, cron-based pipelines into event-driven architecture. To overcome key limitations in the upstream open-source code, I researched, modified, and provisioned Wayfair’s earliest Kafka Connect clusters. To scale this impact, I founded a new Infrastructure team dedicated to supporting event-driven systems company-wide, serving as an internal consultant to help engineering teams migrate from database polling to real-time stream processing.
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58
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Aishwary Dhare
pro
Global FinTech Development for MishiPay
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14
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Jason Fricano
pro
StreamOtter — Live Browser State Toolkit
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6
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Michael Edou
Built a real-time fraud detection engine at Meridian FinTech (Python, Scikit-learn, Kafka) that reduced fraudulent transactions by 43%, saving $1.2M in year one. Also led a zero-downtime migration of core banking APIs to AWS Lambda + API Gateway, cutting server costs by 55% and p99 latency from 820ms to 94ms. #FinTech #Python #AWS #MachineLearning
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Soumabha Roy Chaudhuri
10x throughput · Kafka · 13 social channels · built for viral-scale message bursts Redesigned an enterprise social platform's data layer into an event-driven architecture on Apache Kafka, ingesting and analysing real-time social data from 13 channels. Sized for viral-scale bursts of 250–1,000 messages/minute per customer, with hybrid delivery paths: streaming (~15–20s average latency) and polling (~2 min), with a worst-case 5-minute latency ceiling. Also set architecture standards across application, data, and AI, and rebuilt the React/TypeScript frontend for multilingual workspaces with automated WCAG 2.2 / ADA Section 508 accessibility checks. End-to-end throughput improved 10x. Confidential client engagement.
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25
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Sreeram Melarkode
Near Real Time Data WareHouse
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21
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Eric Dharmawan
I built this Event-Driven Streaming Pipeline to make live analytics feel effortless and instantaneous. Watch how the data flows from source to warehouse, and leave a comment if you think low-latency engineering deserves an award! 🏆✨ 🚀 The Stack: Apache Kafka | Confluent | Snowflake | Data Engineering We broke free from the chains of slow batch processing. By engineering a highly scalable stream using Kafka and Confluent, we ingested live event data directly into Snowflake—slashing latency and unlocking immediate downstream reporting for the business. 📊🔥
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37
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Abel Adisu
Bilnk
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37
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Lakshmi Anne
Enterprise AI Workflow Platform Development
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Zain Ul abideen
Kafka Server Deployment on Ubuntu WSL
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ANIMESH SINGH
Problem: Many organizations still process invoices manually by reading PDF documents and entering key details (invoice number, vendor, amount, etc.) into systems. This process is slow, error-prone, and difficult to scale, and it also makes it harder to detect duplicate invoices or incorrect totals. Solution: This project builds an automated invoice processing pipeline that converts uploaded invoice PDFs into structured data. It uses OCR to extract text, LLMs to identify invoice fields, validation checks to ensure correctness, and Kafka-based event streaming to manage the processing pipeline. The extracted data is stored in PostgreSQL and visualized through a dashboard, enabling faster, scalable, and more reliable invoice processing.
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216
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Huzaifa Tahir
AI SepsisGuard: Sepsis Early Warning
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1
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kothakapu saikrishna reddy
banking-platform-microservices
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