Deploying a Kalshi Bot to Production: 24/7 Without DevOps
How to run a Kalshi trading bot 24/7 in production: process management, secrets, reconnect logic, idempotency, and the failure modes that cost money.
What running the product teaches us about execution, risk, and reliability.
What running the product teaches us about execution, risk, and reliability. 4 articles
How to run a Kalshi trading bot 24/7 in production: process management, secrets, reconnect logic, idempotency, and the failure modes that cost money.
Risk management keeps an automated Kalshi bot alive. The four controls every bot needs: position sizing, stops, daily loss caps, and exposure limits.
Legacy Kalshi order responses can omit a usable fill price. Reconcile current count_fp and yes_price_dollars fill records to keep bot P&L accurate.
Bots now dominate prediction market trading. We analyze the data: how much volume is automated, what strategies they run, and what it means for you.
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