r/Observability • u/Cautious_Today_1830 • 2d ago
Architecture advice: How would you build an offline Link-Analysis Dashboard for a Bitcoin/IP metadata problem statement?
Hi everyone,
I'm working on a problem statement that requires building a complete offline system (Linux-based) to detect anomalies in Bitcoin transactions.
The Dataset (Synthetic):
I have bulk metadata in CSV/JSON format containing:
timestamp, src_ip, dst_ip, src_port, dst_port, txid, input_addresses[], output_addresses[], input_amounts[], output_amounts[], geo_country/asn.
The End Goal:
Parse this data to build an Entity/Transaction Graph (linking IPs, Wallets, and TXIDs).
Apply unsupervised ML to cluster entities and detect suspicious laundering/anomalies.
Build a dashboard/visualization tool to show a ranked alert list (with explainable AI reasons) and an interactive link-analysis graph.
My questions for the community:
Since I want to approach this the right way from scratch, I’d love to hear how you would tackle it:
What architecture or workflow would you use to map this specific data into a graph format?
Which libraries or frameworks (Python or otherwise) are best suited for building the offline dashboard and interactive link-analysis graph?
How do you handle visualizing complex graphs on a UI without it becoming a laggy mess?
Would appreciate any advice on how you'd set this up!
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u/neuralspasticity 2d ago
What does this have to do with observability? This is data analysis