Structure, not spaghetti! Our secrets to faster, less error-prone development
From test automation strategies to fault-tolerant distributed systems, this edition is all about building smarter systems through structure, not shortcuts.
Today’s engineering challenges in developer productivity, AI integration, or system design often demand more than just the newest flashy tools.
They require clarity of thought, strong architectural patterns, and a healthy respect for the complexity to come.
This month, we’re highlighting content that shows off best practices, declarative design, and intentional automation, even when things inevitably get messy.
In this edition, you’ll find:
📖 Blogpost: Why You Should Use the Testing Pyramid in Test Automation
🎥 Video: Architecture as Code with Garden
📖 Blogpost: Effortless Declarative Data Validation with Pydantic
📖 Blogpost: A Closer Look at Raft Internals and Why They Matter
📖 Blogpost: Give Python More Speed with Type Annotations
#blogpost
Why You Should Use the Testing Pyramid in Test Automation
The classic testing pyramid still holds up today, and this article explains why. If you’re struggling with brittle UI tests, slow CI pipelines, or unclear test coverage, it might be time to revisit your test automation strategy.
This guide walks through:
The purpose of each layer: unit, service, and end-to-end tests
How to avoid costly overlap and flakiness
Tools to speed up and stabilize your pipelines
Why shift-left testing and clean test code matter more than ever
How to avoid the dreaded “ice cream cone” anti-pattern
Whether you’re building a new test suite or trying to clean up an inherited one, this piece helps you rethink where your tests live and how they should work together.
#video
Architecture as Code with Garden
In this demo, we show how Garden helps you manage development and infrastructure workflows as code. It automates build/test/deploy steps and creates ephemeral environments on demand, perfect for simplifying complex Kubernetes workflows.
#blogpost
Effortless Declarative Data Validation with Pydantic
Build cleaner, safer Python apps with less code. Learn how Pydantic uses type hints and constraints to enforce structure, catch inconsistencies early, and make error handling a breeze.
#blogpost
A Closer Look at Raft Internals and Why They Matter
Raft powers many modern distributed systems, but how does it really work? This deep dive covers leader election, log replication, and failure recovery, with diagrams and expert insights.
#blogpost
Give Python More Speed with Type Annotations
Type annotations won’t make your Python code run faster, but they will certainly make your team faster. Learn how adding simple type hints can reduce bugs, speed up development, and unlock smarter tooling and collaboration.