Why Choose This Project?
Businesses today rely on processing large volumes of real-time data—such as user activity, transactions, sensor data, and logs—for immediate decision-making. Kafka on AWS MSK (Managed Streaming for Apache Kafka) enables scalable, reliable, and low-latency streaming pipelines. This project is ideal for showcasing data ingestion, processing, and visualization using cloud-native tools.
Applicable for use cases in e-commerce, fraud detection, IoT data processing, and performance monitoring.
What You Get
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Kafka-powered data ingestion at scale
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Real-time stream processing (using Apache Flink or Spark)
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Dashboard for live analytics (e.g., active users, transaction count)
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Scalable and fault-tolerant architecture
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Fully managed Kafka on AWS MSK
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Real-time alerting and anomaly detection
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Logs and insights visualization on a web dashboard
Key Features
| Feature |
Description |
| Kafka Stream Ingestion |
High-throughput ingestion of real-time events from multiple sources |
| AWS MSK |
Managed Kafka cluster with high availability and auto-scaling |
| Stream Processing |
Real-time analytics using Apache Flink or Spark Streaming |
| Real-Time Dashboard |
Live charts and metrics using WebSocket or polling |
| Anomaly Detection |
Auto-detect unusual patterns (e.g., spike in activity) |
| Cloud Monitoring |
Metrics + alerts using AWS CloudWatch or Prometheus |
| Data Lake Storage |
Store raw + processed streams in S3 for batch processing |
| Alerts |
Email/SMS alerts for rule violations (via SNS or Lambda) |
| Authentication |
Basic auth/JWT login for analytics dashboard |
Technology Stack
| Layer |
Tools/Technologies Used |
| Stream Source |
Web apps, IoT devices, Logs, Transactions |
| Stream Ingestion |
Kafka (AWS MSK) |
| Processing Layer |
Apache Flink / Spark / KSQL |
| Data Storage |
Amazon S3 (Data Lake), DynamoDB / RDS (Processed results) |
| Dashboard Backend |
Node.js / Python Flask API |
| Dashboard Frontend |
HTML, Bootstrap, JavaScript, Chart.js / D3.js |
| Authentication |
JWT or AWS Cognito |
| Alerting |
AWS SNS, Lambda, CloudWatch |
| Deployment |
AWS EC2, ECS, or Fargate |
| Monitoring |
Prometheus + Grafana or AWS CloudWatch |
Cloud Services Used
| AWS Service |
Purpose |
| AWS MSK |
Managed Kafka for stream ingestion |
| S3 |
Data lake for raw and processed streams |
| CloudWatch |
Metrics and logs monitoring |
| EC2 / Fargate |
Hosts stream processing jobs or API server |
| SNS + Lambda |
Alerting on anomalies |
| IAM |
Role-based permissions |
| Cognito |
Secure dashboard authentication (optional) |
Working Flow
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Data Producers (apps, sensors) publish real-time events to Kafka topics on AWS MSK.
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Stream Processor (Flink/Spark/KSQL) consumes, filters, and transforms this data.
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Processed insights (e.g., count per minute, alerts) are stored in DynamoDB / S3.
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Frontend dashboard polls API or uses WebSocket to show live graphs.
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Alerts are triggered if thresholds are crossed, using AWS SNS or Lambda.
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CloudWatch or Prometheus monitors system health and performance.
Main Modules
| Module |
Description |
| Producer Module |
Sends real-time data to Kafka |
| Streaming Module |
Filters, aggregates, and processes events |
| Storage Module |
Persists both raw and processed data |
| Dashboard Module |
Displays real-time graphs and alerts |
| Auth Module |
Secures access to analytics dashboard |
| Alert Module |
Detects anomalies and sends notifications |
Security Features
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AWS IAM roles for fine-grained access control
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Kafka access controlled by MSK IAM policies + TLS
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JWT or Cognito login for frontend dashboard
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SSL for API communication
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API Gateway or Nginx for throttling and rate-limiting
Customization
Fully
Security
High
Performance
Fast
Future Updates
Free
Total Buyers
500+
Support
Lifetime
