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CryptoViz
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Technical Overview
DOCKER
KUBERNETES
GRAFANA
FASTAPI
KAFKA
PYTHON
APACHE SPARK
Project Description
For this project, I acted as a solution architect to build a complex data pipeline using Kafka for message buffering and Apache Spark for heavy analytical processing. I implemented scrapers to collect live Bitcoin prices and news, storing the processed results in Parquet files for efficiency. The final architecture uses DuckDB as a fast query engine and FastAPI to serve data to a Grafana dashboard, where I visualized technical indicators like Simple Moving Averages (SMA) and sentiment scores calculated via VADER and TextBlob.
Tech Stack
DOCKERKUBERNETESGRAFANAFASTAPIKAFKAPYTHONAPACHE SPARKProject Gallery
Project Info
Status
Completed
Type
📈 Data Science
☁️ DevOps & Cloud
🤖 AI
SPOTLIGHT
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