Wallaroo Labs helps companies productionize AI algorithms with their simple, fast, and low-cost platform. I was the first employee and right-hand to the CEO involved in every aspect of the business, from operations to strategy. Currently, I continue my involvement as an advisor. For a time, I spearheaded developer relations for the open-source product, managing the production and promotion of content related to the platform. Many of the posts had wide distribution, including several posts to the front page of HackerNews.
Real-time Streaming Pattern: Fast Algorithmic Trading Check
Electronic trading requires fast and reliable processing of trade requests and push them out to the various exchanges as quickly as possible. This is why much of the infrastructure used for electronic trading is located as physically close to the trading venue as possible and runs on custom built hardware that is tuned to get the maximum performance
Real-time Streaming Pattern: Triggering Alerts
When you think about event triggered applications, sending an alert based on an event is one of the first things to come to mind. The triggering alerts pattern involves monitoring a stream of even data and triggering some action when a threshold is reached.
Real-time Streaming Pattern: Preprocessing for Sentiment Analysis
It’s not unusual to see the preprocessing pattern used in many use cases and combined with other patterns. One excellent example use case is removing stop words for sentiment analysis. Sentiment analysis is used by data scientists to look at a piece of text and determine whether the underlying sentiment is positive or negative.
How to Build a Thriving Open-source Community
Building a community of developers was one of the key motivations that led Wallaroo Labs to open-source our distributed data engine, Wallaroo.But it’s not always easy. There are millions of public, open-source repositories on GitHub. How do you stand out from the crowd and build a thriving developer community around your project?