Tag: container

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AI Management & Organizational Restructuring

The Foreman Problem: Managing Teams When Your Best Worker Isn't Human - Willian Correa

Every major technology shift invented a new management role. Steam power → foreman. Office computing → project manager. Internet → product manager. AI is doing the same, but this time the failure mode is invisible: confident, polished, wrong output. The new job is not directing effort but verifying that things that look like they're running actually are.

Who Will Be the Senior Engineers of 2035? - James Stanier

The traditional junior-to-senior pipeline is breaking: entry-level tech postings down 67% since 2022, junior employment down ~20%. Firms adopting AI saw junior employment fall 7.7% vs non-adopters. 54% of engineering leaders plan to hire fewer juniors.

Compound Engineering & Code Health

The Compounding Software Factory - Luca Rossi (Software Factory series, Part 3 of 3)

What causes teams to degrade: poor coding hygiene (bad testing, poor code health, missing abstractions), failure to capture knowledge (no ADRs, no playbooks, no snapshots), and building the wrong things.

AI Coding Meets Code Health - Stuart Caborn

Loveholidays' journey to becoming an AI-first engineering organization. Core thesis: code health is the foundation for successful AI adoption. By deliberately investing in code health metrics before adopting AI, they achieved 80+ deployments/month, 60% AI-written code, <1% change failure rate, all while maintaining elite code health.

Security & Infrastructure

The (In)security Landscape of AI-Powered GitHub Actions - Shay Berkovich

AI-powered GitHub Actions from vendors like OpenAI, Anthropic, and Google are now running in thousands of public workflows. Research found bypasses of non-default configurations letting any external attacker trigger AI execution, a novel secret exfiltration vector for dynamically-created credential files, and widespread misconfigurations in production workflows.

The Invisible Engineering Behind Lambda's Network - Werner Vogels

A decade-long story of invisible infrastructure engineering by Lambda's networking team.

Career & Token Economics

Tokenmaxxing Is the Budget Game Played With AI Tokens - Willian Correa

Tokenmaxxing — maximising AI token consumption for visibility — is the corporate "use it or lose it" budget game in a new currency. Meta's internal "Claudeonomics" leaderboard ranked 85K employees by token consumption; top user burned 281B tokens in 30 days.

Tools

Use Compose Watch

Docker bind volumes gets a supercharge. Compose Watch does not replace bind mounts but exists as a companion specifically suited to developing in containers.

More importantly, watch allows for greater granularity than is practical with a bind mount. Watch rules let you ignore specific files or entire directories within the watched tree.
For example, in a Node.js project, it's not recommended to sync the node_modules/ directory. Even though JavaScript is interpreted, npm packages can contain native code that is not portable across platforms.

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Why I Will Never Use Alpine Linux Ever Again

Alpine image is heavily use as a base image for all sort of applications. Some applications, usually running in Kubernetes, are facing issues due to Alpine implementation of musl. This article describes how those issues can cause a great amount of grief.

3 years of lift-and-shift into AWS Lambda

Let’s set the scene. We’re looking for scaling a PHP application. Googling around take us to find out that AWS Lambda is the most scalable service out there. It doesn’t support PHP natively, but we got https://bref.sh. Not only that, we also have Serverless Visually Explained which walk us through what we need to know to get PHP up and running on AWS Lambda. But we have a 8 year old project that was not designed from the ground up to be serverless. It’s not legacy. Not really. It works well, has some decent test coverage, a handful of engineers working on it and it’s been a success so far. It just has not been designed for horizontal scaling. What now?

Different beliefs about software quality

Good advices on how to deal with an environment where you have conflicts about your beliefs and how the environment work.

Increase code coverage successively

I often come across legacy projects that have a very low code coverage (or none at all). Getting such a project up to a high code coverage can be very frustrating as you will have a poor code coverage for a very long time.

So instead of generating an overall code coverage report with every pull request I tend to create a so called patch coverage report that checks how much of the patch is actually covered by tests.

Conway's Law

Pretty much all the practitioners I favor in Software Architecture are deeply suspicious of any kind of general law in the field. Good software architecture is very context-specific, analyzing trade-offs that resolve differently across a wide range of environments. But if there is one thing they all agree on, it's the importance and power of Conway's Law. Important enough to affect every system I've come across, and powerful enough that you're doomed to defeat if you try to fight it.

Is it a DTO or a Value Object?

A common misunderstanding in my workshops (well, whose fault is it then? ;)), is about the distinction between a DTO and a value object. And so I've been looking for a way to categorize these objects without mistake.

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https://extendsclass.com/

ExtendsClass provides tools directly usable in a browser. It saves you from having to install add-ons to your browser in order to add features.

You have at your disposal syntax validators, code formatters, testers, HTTP clients, mock server, but also a SQLite browser.

These are small and easy-to-use tools that can help when you do not want to install software on your workstation.

Solid Relevance

More topics that highlighs the importance of SOLID concepts. How they are key to develop a solid application.

Kubernetes: ClusterIP vs NodePort vs LoadBalancer, Services, and Ingress — an overview with examples

Dockerfile best practices

Writing production-worthy Dockerfiles is, unfortunately, not as simple as you would imagine. Most Docker images in the wild fail here, and even professionals often[1] get[2] this[2] wrong[3].

This repository has best-practices for writing Dockerfiles that I (@slimsag) have quite painfully learned over the years both from my personal projects and from my work @sourcegraph. This is all guidance, not a mandate - there may sometimes be reasons to not do what is described here, but if you don't know then this is probably what you should be doing.

How to Make Your Code Reviewer Fall in Love with You

When people talk about code reviews, they focus on the reviewer. But the developer who writes the code is just as important to the review as the person who reads it. There’s scarcely any guidance on preparing your code for review, so authors often screw up this process out of sheer ignorance.

This article describes best practices for participating in a code review when you’re the author. In fact, by the end of this post, you’re going to be so good at sending out your code for review that your reviewer will literally fall in love with you.