Many projects like to draw pancakes, but in the end, the filling is often exposed. @OstiumLabs' recent approach has a bit of an engineer's flavor, not shouting slogans, first connecting the underlying data flow, and then considering expanding the scale It has reprocessed the data sources of traditional markets through pipeline processing, separating and synchronizing the three core data types of price, depth, and trading volume. With this change, the pricing delay of perpetual contracts has been significantly reduced, and there will be no awkward situation of "slow on chain" during high-frequency fluctuations. At the same time, they have implemented an error damping algorithm in price synchronization, which can automatically filter out abnormal jump points in the market and improve the steady-state range of the contract At the transaction execution level, Ostium has introduced a lightweight matchmaking scheduler specifically designed to optimize small order volumes and high-frequency suspensions. The common queue blocking problem of traditional on chain contracts is alleviated here, and the transaction experience for new users is also smoother Another noteworthy feature is their monitoring plugin, which is used to analyze the exposure distribution of the risk pool in real-time, including indicators such as peak volatility, order density, and position offset. For those who do risk control in the field, these data can significantly improve judgment efficiency and be publicly available on the entire chain @OstiumLabs is not following the flashy facade, it is polishing the basic actions and using a solid foundation to make the derivative environment cleaner and more controllable @OstiumLabs @Bantr_fun @0xMantleCN Ostium Bantr