The Pipeline pattern is a fundamental concurrency pattern that connects multiple stages of processing where each stage processes data and passes it to the next stage. This pattern is particularly useful for data transformation workflows, stream processing, and multi-step computations.
NOTE: For other posts on concurrency patterns, check out the index post to this series of concurrency patterns.
Concurrency is one of those topics that can make even experienced developers break out in a cold sweat. It’s like trying to juggle flaming chainsaws while riding a unicycle on a tightrope. But here’s the thing – in today’s world of multi-core processors, distributed systems, and high-performance applications, understanding concurrency isn’t just a nice-to-have skill; it’s absolutely essential.
Go, with its goroutines and channels, makes concurrency more approachable than most languages. But just because it’s easier doesn’t mean it’s easy. You still need to understand the patterns, the pitfalls, and the best practices to build robust, scalable systems.
That’s what this series is about. We’re going to dive deep into the concurrency patterns that every Go developer should know. Not just the theory – we’ll look at real, working code examples that you can run, modify, and learn from. This blog post is going to also act as the index to the posts, with today starting with the Pipeline Pattern.
This series covers 12 essential concurrency patterns, each with practical examples and detailed explanations. Here’s what’s coming:
Continue reading “Concurrency Patterns in Go: A *Short* Deep Dive Series”I’ve been diving deep into implementing Datadog in iOS applications and wanted to share my experience with both SwiftUI and UIKit approaches and the related elements of the work. Let’s break this down into what works, what doesn’t, and why you might choose various options when using Datadog (or deciding not to use Datadog).
First things first, you’ll need these Datadog SDK packages:
dependencies: [
.package(url: "https://github.com/DataDog/dd-sdk-ios", from: "2.27.0")
]You’re cruising along, vibe-coding your way through a new feature, and—poof—the AI assistant goes dark. Maybe it hallucinated a library that doesn’t exist. Maybe it repeated the same wrong snippet ad nauseam. Welcome to the moment of reckoning: your blind faith in “make me the code” meets cold, hard compiler errors.
Spinning the wheel of madness: You tweak a comment here. You change “public” to “private” there. You pray to the Codegen Deity. You hope it understands your increasingly desperate prompts.
Lose an hour or a day: You still haven’t fixed the NullReferenceException, and your caffeine cold-brew is now room temperature.
Blame the tool that’ll fix it!: It’s obviously a bug in the AI, right? Right? RIGHT? Your sanity is going to ebb, beware the blaming of tools!
This cycle feels familiar because it is, the tooling is great at scaffolding code, less so at understanding your context. When it bails on you, you’ll need a plan B.
Continue reading “When the AI Ghost Vanishes”Git. It’s the tool that makes some of us developers wonder why they didn’t become a carpenter. But let’s face it: Git is here to stay. And for a small team—like, say, 3-4 developers working on the same codebase—getting your branching strategy right can be the difference between smooth sailing and a storm of merge conflicts that will make you question every decision you’ve ever made in life.
So let’s dive into a “simple” strategy for keeping Git under control. No complex workflows, no corporate jargon—just a few solid, time-tested practices to keep you from drowning in source control hell. Because seriously, git is actually super easy and a thousand times better than all the garbage attempts at source control that came before.
If you’re working on a small team, you don’t need to be fancy. Forget about multiple branches for every single thing under the sun—just stick with main and feature branches. That’s it. Keep it simple. We don’t need a thousand different integration branches or some mythical release branch. Keep it neat.
main: This is your production-ready code. The one branch that should always work, always deployable, and always sacred. No exceptions.main.
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