Integration Tests for your Kafka Producer with “Testcontainers” in C#

An article about integration tests for your Kafka workflow. Using C# and the “Testcontainers” framework, we first run Kafka in Docker, call an API that will push a message to Kafka, consume the produced Kafka message ensuring it’s correct, and finally drop the created containers.

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Running Containerized .NET Scheduled Tasks with AWS Fargate – Part 2

In this article, we’ll continue where we left off and see how to properly handle the networking issues we had last time. Concretely, we need to find a way to host our Fargate Task in a private subnet (so it’s not reachable publicly) but also allow for outbound internet traffic through a static public IP address. We will whitelist this IP in Atlas, making the Mongo cluster accessible from the running container.

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Sentiment Analysis of Stocktwits Messages using LSTM in PyTorch

In this article, I’ll present a demo project for classifying the sentiment of posts from the Stocktwits social media. The community on Stocktwits is full of investors, traders, and entrepreneurs. Each message posted is called a Twit. This is similar to Twitter’s version of a post, called a Tweet. Using Pytorch, we’ll build a model around these twits that generate a sentiment score.

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GraphQL, Node, Apollo and React (Social Media Demo Project) –  Part 2

In this article, I’ll present the UI part of the Social Media demo project we started exploring last time. In the previous post, you dug into the GraphQL API and how to send queries via the Apollo Playground. Now it’s time to bring it all together and see how the React front-end integrates with the API using Apollo Client.

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GraphQL, Node, Apollo and React (Social Media Demo Project) –  Part 1

It can’t go unnoticed that GraphQL is being adopted by plenty of reputable companies like Facebook, Shopify, Twitter, and many more. For quite some time, I hadn’t had the chance to explore it and understand what it brings to the table. Still, probably like many of you, I’ve read some isolated references here and there, gaining intuition about what kind of API design pain points GraphQL is meant to solve. So I decided to spend some time learning GraphQL, its

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