Flamingo BigData Monitoring & AI Platform

AI-driven Hadoop ecosystem monitoring with anomaly detection

Project Overview

Flamingo big data solution architecture design and AI integration development. Built an intelligent platform providing comprehensive real-time monitoring of the entire Hadoop ecosystem, AI-based anomaly detection, and comprehensive workflow management. It was an innovative AI monitoring system from 2016 that automatically detects abnormal logs and metrics through machine learning model integration.

Challenge

Needed to monitor complex Hadoop ecosystems in real-time, detect anomalies in large-scale data streams, provide intelligent workflow management, and integrate machine learning capabilities for predictive analysis while maintaining low latency and high availability.

Solution

AI-Integrated Real-time Monitoring

Built comprehensive real-time monitoring system integrated with machine learning algorithms to automatically detect and predict anomalies in Hadoop clusters.

Real-time log collection and analysis: Comprehensive log aggregation across Hadoop clusters

Machine learning anomaly detection: Automatic identification of abnormal patterns and performance degradation

Predictive analysis: Future problem prediction based on historical data

Intelligent alerts: Context-aware notifications and automated response recommendations

Workflow Designer & Manager

Built intuitive platform for visually designing and managing complex big data workflows.

Drag-and-drop workflow builder: Complex data pipeline configuration without coding

Real-time workflow monitoring: Progress and performance tracking of running jobs

Dependency management: Automatic resolution of complex inter-job dependencies

Error handling and recovery: Intelligent error detection and automatic recovery mechanisms

Tech Stack

Hadoop

Distributed data processing platform

Apache Spark

High-speed data processing engine

Apache Kafka

Real-time streaming platform

Apache Hive

Data warehouse software

HBase

NoSQL distributed database

TensorFlow

Machine learning framework

Elasticsearch

Log search and analysis

Grafana

Monitoring dashboard and visualization

Key Results

Significantly enhanced Hadoop cluster visibility and control

Dramatically reduced system downtime through AI-based anomaly detection

Greatly improved workflow design and management efficiency

Implemented proactive maintenance through predictive analysis

Learnings

AI integration dramatically enhances traditional monitoring system capabilities

Scalable architecture design is essential for real-time big data processing

User-friendly workflow tools significantly simplify complex data pipeline management

Predictive analysis plays a key role in big data system stability and performance optimization

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