How to choose a decoupling service that suits your use case? In this article we’ll take you though some comparisons between AWS services – Kinesis vs SNS vs SQS – that allow you to decouple sending and receiving data. We’ll show you examples using Python to help you choose a decoupling service that suits your use case. Decoupling offers a myriad of advantages, but choosing the right tool for the job may be challenging.

Daniel is a Site Reliability Engineer at k6.io. He’s especially interested in observability, distributed systems, and open source. During his free time, he helps maintain Grafana Tempo, an easy-to-use, high-scale distributed tracing backend. Distributed tracing is a way to track the path of requests through the application. It’s especially useful when you’re working on a microservice architecture.

In our last blog, we introduced OpenTelemetry Python v1.0.0 and walked you through instrumenting a Python application and install both the OpenTelemetry API and SDK.

Performance optimization is a basic need for software development. When it comes to optimizing app performance, tracking frequency, maintaining production, or perpetuation method calls, profilers play a vital role. Learn why Python cProfile is a recommended profiling interface and how it enhances your software performance.

Have you ever tried to search for objects in images? Elasticsearch can help you store, analyze, and search for objects in images or videos. In this quick tutorial, we’ll show you how to build a system for facial recognition with Python. Learn more about how to detect and encode facial information — and find matches in search.

Since the OpenTelemetry Tracing Specification reached 1.0.0 — guaranteeing long-term stability for the tracing portion of the OpenTelemetry clients, the community has been busy working to get the SDKs and APIs for popular programming language ready to be GA. Next in our ‘Getting Started with OpenTelemetry’ Series, we’ll walk you through instrumenting a Python application and install both the OpenTelemetry API and SDK.

For many software engineers and developers, using standard libraries or built-in objects is just not enough. To save time and increase efficiency, most developers build on work done by others. Whatever the coding problem, there is likely another programmer who has already created a solution for it. There is usually no need to repeat the problem-solving process. This principle is known as Do not Repeat Yourself or DRY.

Python is one of the best programming resources available for designing machine learning systems. With a variety of technical abilities and potentially time-saving loops and processes, it can be an invaluable tool. However, it’s these capabilities that also make Python difficult to use. In many cases, Python may seem sluggish as it tries to navigate intricate, complicated strings of code.