A Random Walk Down Wall Street – First Run Analysis Using Stock News Sentiment System

I figured I would go off and run the tool on a few prominent tickers, make a prediction for a time period, and revisit later to see how those predictions fared.

Keep in mind, this is rather unscientific.  I’ll be updating throughout the day as the analysis finish. Largely a task illustrating how long this takes to do without architectural enhancements we do in upcoming steps.

Continue reading A Random Walk Down Wall Street – First Run Analysis Using Stock News Sentiment System

Part 8: From Microservice to Microservice Ecosystems – Using Docker Compose To Orchestrate a Microservice Harness

In our previous post we finally began to see the individual microservices coming together to create an  abstract plausible data flow. In this post, we are going to chain our microservices together to run an entire calculation stream sequentially. We are going to illustrate how to orchestrate a collection of microservices using Docker Compose, and we are going to illustrate how to use the Docker Registry to avoid recreating the wheel when creating microservice ecosystems.

Continue reading Part 8: From Microservice to Microservice Ecosystems – Using Docker Compose To Orchestrate a Microservice Harness

Part 7: Creating a Latest Stock Ticker News Microservice

In our series we have constructured two microservices. The first would submit a string of text, or a message, to IBM Watson’s tone analysis service and report back tonal analytics based on the input. The second microservice would accept a URL and return a text scrape of the content of that page. Continue reading Part 7: Creating a Latest Stock Ticker News Microservice

Part 5: Making Watson Microservice using Python, Docker, and Flask

Creating a Python Microservice using Flask

We already have a Python application we wrote back in part 3.  This application takes in a text string and submits the text to IBM Watson to return an analysis of the text. The next step in building our application would be to take this piece of code and turn it into a Microservice.

The first step of creating a microservice from our code is to expose the functionality through some sort of interface. We will use Flask to expose our functionality via a HTTP (1.1. we will work on a 2.0 architecture update in a future post). Additionally we will set our BlueMix credentials from environment variables where the Python is executed. Continue reading Part 5: Making Watson Microservice using Python, Docker, and Flask