This is a work which includes collecting various performance metrices( system and custom), along with database and service related data. This data is coming from various sources. I am working on designing the backbone for this data to make it available in influx db which is the data source for Grafana dashboards, for active monitoring.

These are services which collect tick data from pricing systems which gives as many as 600,000 updates per second. There are separate instances of these services running for separate asset types like stocks, futures, forex. The data is save d in various forms like CSV, In memory and kdb.

This was an integration project which used a third party portfolio management tool. Daily end of the day data used to be uploaded on the DB of this tool to show the trades and positions of customers which they have done.

This was a server that used to do validation of all the orelders coming from gui and then pass them on to different tools to process.

This was a framework to assist market analyst in writing their strategies. Similar products in the market are ninja trader, Mera trader. This tool was able to integrate any trading engine whose basis could have been a machine learning algo or a pattern recognition algorithm. This tool was having it's own Grammer as well, which could have been used to write strategies. Writing the parsing algorithm was a challenge which I enjoyed here.

This was a connectivity solution with National stock exchange using Omnesys API. This was used to collect orders from the various data bases from analysts's machines and send them to exchange fortrade by placing price on them. This solution was designed for high frequency orders and everything was in memory. I used data structures like circular ring buffer in this along with multiplexer and demilultiplexer.