Estimatein 1 hourEstimate a projectreply within 1 hourA private Binance trade-collection service with analytical summaries for BTC and USDT markets, built to watch large-player market activity.
The client needed a private service that collects trade data across many key Binance pairs and returns analytical summaries in different slices — to watch market swings and spot large-player activity without sitting in a terminal or taking one-off chart screenshots.
Public widgets and one-off exports do not keep history or the needed detail by time of day, volume and anomaly spikes. They needed a durable collect → normalize → aggregate pipeline without manual babysitting, with series kept for period comparison and activity windows.
We built a closed contour: continuous trade collection, raw and aggregated series storage, and dashboards for BTC and USDT markets. The project stays a private analytics tool for the client’s team — not a public SaaS with a marketing storefront and open signup.
The pipeline uses Python WebSocket clients to catch Binance trades, Apache Kafka to buffer peaks, and ClickHouse for minute-level queries. Separate jobs reconcile gaps and recompute windows so history stays comparable after short disconnects. Critical spikes go to a Telegram bot so the team sees large volume early.
Analytical slices follow the client’s scenarios: volatility, volumes, anomalies by time of day. The UI is closed — working panels only, where the team watches BTC and USDT markets and flags unusual large-player activity without a marketing shell.
Active development took about a month, then slice tuning for BTC and USDT market watching. The project remains private and is not published as SaaS: focus stays on collection reliability, history integrity and aggregation usefulness for team decisions.
The client got a continuous Binance trade-collection service and analytical summaries in the slices they need — to watch market swings and large-player activity without manual terminal monitoring. The trade stream becomes history and aggregates the team can act on.
BTC and USDT markets live in one closed contour: history is kept, anomalies are sought by volume and time windows — not by one-off terminal screenshots. Slices can be compared across periods and tuned to the client’s observation scenarios.
The project stays a private team tool: no public landing, with focus on collection reliability, series integrity and slice usefulness for decisions. Further tuning centers on aggregations and windows without breaking the pipeline core.
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