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Unified Namespace and xRegistry at Contoso Autowerks
This article describes how Contoso Autowerks uses a Unified Namespace (UNS),
captured formally in an CNCF xRegistry, to integrate its manufacturing systems.
Mind that this is a fictional example tro illustrate the concepts of a Unified
Namespace and how CNCF xRegistry can be used to capture the metadata of the
namespace.
This project provides a web application for real-time monitoring of ADS-B messages using dump1090. The application consists of a FastAPI backend and a frontend that displays various statistics in real-time using Chart.js.
I don't have time to package this up at the moment.
Features
Message Rate Statistics: Computes and displays message rates over different intervals (5s, 15s, 30s, 60s, 300s).
Signal Strength Statistics: Computes and displays minimum, maximum, and average signal strength over 30 seconds.
Outlook Macro to revert safelink URLs while composing a reply.
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Illustration for how to use the Service Bus emulator in a C# test fixture
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The Apache Avro project defines a JSON Encoding, which is optimized for encoding
data in JSON, but primarily aimed at exchanging data between implementations of
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I wrote the code, ChatGPT the text. I'll eventually write an actual article, but this will do:
### Consuming and Creating (Structured, JSON) CloudEvents in Azure Stream Analytics
Hey devs, today we're going to talk about working with structured JSON CloudEvents in Azure Stream Analytics. We'll be using some straightforward SQL-like queries to get this done, and I promise to keep the jargon to a minimum. Let's get started.
#### Setting Up Your Event Stream
We assume that the input is an Event Hub that multiplexes CloudEvents in structured JSON format.
Resolving Competing, Paradoxical Validation/Code-Gen Constraints in JSON Schema
Resolving Paradoxical Constraints in JSON Schema
Introduction
JSON Schema is a versatile tool for defining the structure of JSON data and ensuring its validation. However, as powerful as it is, complex scenarios can sometimes lead to paradoxical constraints, especially when used in combination with code generation tools. In this article, we'll take an in-depth look at one such paradox that emerged while defining message structures for various protocols and discuss a practical solution.
The Problem Statement
Imagine a system where messages are passed using different protocols, such as AMQP, HTTP, MQTT, Kafka, and CloudEvents. Each protocol has a distinct message structure but shares certain common attributes. These shared attributes are consolidated in a base message definition, called definition in our JSON Schema.
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