While many tools exist to build and deploy your no-code APIs, your options are limited when your solution requires a custom or highly bespoke APIs that execute custom logic.

In part one of this series, we walked through how to use Streamlit, Apache Kafka, and Apache Flink to create a live data-driven user interface for a market data application to select a stock (e.g., SPY) and discussed the structure of the app at a high level. First, data with information on stock bid prices is moved via an Alpaca websocket, then, it’s produced to a Kafka topic in Confluent Cloud where it is also processed with Flink SQL.

Two of the main tenets of Zero Trust are encryption between services and managing the connections each service is allowed to use. Achieving this generally falls to running a service mesh in a Kubernetes cluster. Refactoring applications to run properly in Kubernetes takes time and considerable investment. For many organizations, running their applications on virtual machines will be a necessity for years to come. However, this doesn't mean security should fall behind.

As a developer, you usually work with JSON data, and may need to compare JSON files. This might involve checking a list of products from the database against a previous version or comparing an updated user profile returned by your REST API with the original data sent to the server. In this article, we’ll explore several methods and tools developers can use to compare two JSON files effectively.

You've likely heard the term webhook at some point. But what are webhooks? Five key takeaways from What Are Webhooks.

How to use Gemini generative AI models through BigQuery to boost productivity in Google productivity tools like Sheets.

In today's rapidly evolving digital landscape, superior software is essential, whether it be the apps on our phones or the intricate systems supporting various business requirements. The process known as Software Testing (ST) has undergone an immense transformation in order to meet this necessity where Artificial intelligence (AI) and machine learning (ML) play a great role in QA solutions.