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7 daily crons, 2 starvation incidents that triggered the rewrite Health checks before work, not after, catch silent failures Queue-low alarm fires at 5 items, not at zero A cron is ignorable for 3 weeks only when failures are loud I run 7 GitHub Actions crons every day, and for two months I never looked at them. Then a content queue starved silently and I posted nothing for 4 days before noticing. Here is what I changed so a cron can stay green and be ignorable for 3 weeks straight. The Two Incidents That Forced The Rewrite The first starvation happened on a Tuesday. My image generation cron pulled prompts from a queue, made the assets, and pushed them to a publish queue. The image API returned a 429 (rate limited) and the job exited cleanly with a green checkmark. GitHub Actions reported success. The workflow logs said "0 prompts processed" in a line I never read. For 4 days the publish queue drained and nothing refilled it. I found out because a follower asked why I went quiet. The second incident was sneakier. A cron that calls an external API hit an auth token that had expired. The script caught the error, logged it, and returned exit code 0 because I had wrapped the whole thing in a try/except that swallowed everything. Green check, no work done. This one ran for 6 days before I caught it during an unrelated debug session. Both failures shared one root cause: a green checkmark in GitHub Actions means the process exited zero, not that the work happened. Those are completely different claims. A cron that catches its own errors and exits clean is lying to you in the most polite way possible. After the second incident I sat down and wrote out what I actually wanted. I wanted to never look at these workflows unless something was wrong. I wanted "wrong" to be loud. And I wanted the loudness to arrive before the damage, not after. That meant three changes. First, the exit code had to reflect real work, so swallowed exceptions had to re-raise or set a failure flag. Sec

Laravel API Development in Morocco: Architecture Guide 2026 Laravel remains the #1 PHP framework for API development in 2026 Laravel remains the #1 PHP framework for API development in 2026, and Morocco has become a hub for quality Laravel freelancers and teams. Here is the complete guide to building production-grade APIs with Laravel, based on 40+ projects shipped. Why Laravel for APIs in 2026 Eloquent ORM — most expressive DB layer in any framework Sanctum for SPA/mobile auth (simpler than Passport for most cases) Scout for Meilisearch / Algolia / Elastic full-text search Queues with Horizon for background jobs Octane for performance (Swoole / RoadRunner) Deep ecosystem : Telescope, Pulse, Forge, Vapor REST vs GraphQL — What to Choose Criteria REST GraphQL Learning curve Low Medium-high Caching Easy (HTTP) Complex Over-fetching Common Solved Mobile bandwidth Higher Optimized Best for Public APIs, simple CRUD Complex dashboards, mobile apps My default : REST with Laravel API Resources unless the client has clear GraphQL-specific needs (mobile app with variable fields, highly nested data). Standard Laravel API Architecture app/ ├── Http/ │ ├── Controllers/Api/V1/ │ ├── Requests/ (FormRequest for validation) │ └── Resources/ (API Resources for shaping output) ├── Models/ ├── Services/ (business logic) ├── Repositories/ (optional, if complex queries) ├── Jobs/ └── Events/ Key architectural decisions Versioning via URL (/api/v1/users) not headers — simpler FormRequest for validation (never validate in controller) API Resources for every response (shape, transforms, conditionals) Services layer when controllers exceed 100 lines Dedicated DTOs for complex payloads (spatie/laravel-data) Authentication — Sanctum Setup SPA on same domain : cookie-based, CSRF protected Mobile app / 3rd party : personal access tokens Revocation endpoint for logout Token abilities for granular permissions Rate Limiting & Security RateLimiter facade — per user, per IP, per endpoint CORS : use c

An innovative Moroccan platform for finding, renting, and selling real estate, offering a simple and seamless experience tailored to the local market. Challenge Launch Sarout.ma, an innovative Moroccan platform dedicated to searching, renting and selling real estate, on an ultra-competitive market dominated by a few historical players often criticized for dated ergonomics and uneven listing quality. The challenge: build an intuitive, modern real estate marketplace able to connect individual owners, agencies and tenants across all of Morocco — Casablanca, Rabat, Marrakech, Tangier, Agadir — with clear navigation and smart search. It also required enriched, geolocated listings updated in real time, and a journey differentiated by user profile (searcher, owner, professional agency). Solution Development of a site with a clean, fully responsive interface, designed mobile-first since most real estate searches in Morocco happen on smartphones. Integration of advanced dynamic filters (city, neighborhood, price, surface, number of rooms, property type, furnished/unfurnished) with instant result refresh. Listing management via a complete owner dashboard: creation, editing, view statistics, photo management with multi-upload and automatic compression, scheduling of paid promotions. Each property page has an SEO-optimized URL, rich descriptive content, precise geolocation on an interactive map, and the option to directly request a viewing. SEO architecture focused on local ranking: category pages per city and neighborhood, Schema.org RealEstateListing markup, dynamic sitemap. Email alert system for saved searches, listing moderation, and a professional agency dashboard for premium accounts. Results A high-performing, accessible real estate portal that significantly simplifies property search for individuals and strengthens listing visibility across Morocco. The interface fluidity stands out in a market where competition remains rough around the edges. Steady growth in publishe

Lab 1 – Linux Navigation & Files (20 points) Task 1 Create the following structure. /home/student/ ├── project │ ├── logs │ ├── scripts │ └── backup Requirements create all directories create app.log error.log install.sh inside correct folders. Task 2 Move app.log into backup Task 3 Delete error.log Task 4 Find install.sh using only one command. Lab 2 – Permissions (20 points) Create secret.txt Requirements Owner read/write Group read Others no access Verify permissions. Create a new user developer Switch to that user. Can the user read secret.txt Explain why. Lab 3 – Processes (20 points) Start a process Example sleep 500 Questions Find PID Kill the process Verify it stopped. Bonus Find the top five processes using the most memory. Lab 4 – Disk Space (20 points) Create a directory practice Generate a file about 100 MB. Questions How much disk space is used? How much free disk space remains? Which command shows directory size? Lab 5 – Networking (30 points) Find Your hostname private IP default gateway DNS server Ping 8.8.8.8 Questions Did it work? Ping google.com If this fails but 8.8.8.8 works, what is the problem? Display All listening ports. What service is listening on port 22? Lab 6 – Troubleshooting (40 points) Scenario 1 A user says "Internet is not working." Show the commands you would run. Expected ideas ip addr ping 8.8.8.8 ping google.com ip route cat /etc/resolv.conf Explain each step. Scenario 2 A website is down. Questions How do you verify server is running? nginx is running? port 80 is listening? firewall issue? logs? Commands should include systemctl status nginx journalctl -u nginx ss -tuln curl localhost systemctl restart nginx Scenario 3 SSH stopped working. How would you troubleshoot? Expected ping server ssh localhost systemctl status ssh ss -tulpn journalctl -xe systemctl restart ssh Lab 7 – Mixed Practical (Best Assessment) Tell students: You are the new Junior DevOps Engineer. The manager asks you to prepare a server. Complete all tasks. Ta

GitHub added an enterprise setting this week that looks like the kind of thing most developers will never read about unless it breaks their editor. Enterprise managed settings now support strictKnownMarketplaces for VS Code and GitHub Copilot CLI. In plain English: an organization can restrict which extension and plugin marketplaces are known and allowed inside the developer tools people actually use. That sounds like desktop management. I think it is more interesting than that. If coding agents can discover tools, install plugins, call commands, read repositories, modify files, and run workflows from the IDE or terminal, then plugin marketplace policy is no longer a minor preference. It is part of the runtime boundary. The agent does not only need permission to think. It needs permission to reach for tools. And the place where those tools come from is now a security surface. the tool catalog moved closer to the developer For a long time, extension marketplaces felt like productivity infrastructure. You installed a formatter, a theme, a language server, a test explorer, a Docker helper, a cloud plugin, a database browser, maybe three things you forgot existed. Some companies cared a lot. Many mostly hoped the endpoint security product would notice anything truly bad. That world was already risky, but the blast radius was usually framed around the human developer. A plugin could read files, run code, exfiltrate data, or weaken the local environment. Bad, but familiar. Agents change the framing. An AI coding assistant sitting in the IDE or CLI may use plugins as capabilities. It may call into developer tooling, use installed extensions as context, or depend on local integrations to perform work. Even when the agent itself does not directly install anything, the available tool environment shapes what it can do. So the question stops being "which extensions are developers allowed to install?" It becomes "which tool supply chains are allowed to become part of our automat

penAI reportedly plans to share its newest model, GPT 5.6, with a select group of partners instead of to the broader public. The reason: the Trump administration told it to.

What is your opinion on this? Norway banned smart phones and now AI. > Prime Minister Jonas Gahr Støre argues that using AI could increase the risk that young children miss important steps in their education.

source files + final paper pdf. ZIP containing the source files and final paper.pdf. Where does the supplemental materiel get uploaded? Because in that email it says include it in a "supplementary_materiel" folder. this is all very confusing. can someone clarify? submitted by /u/redskydawns [link] [留言]

Amazon-owned MGM Studios’ decision to drop the OpenAI movie is just part of AI and film industries becoming increasingly intertwined. On Uncanny Valley, we take a look at where this is all headed.

Explore how the GitHub Copilot agentic harness delivers strong results across multiple benchmarks and leading token efficiency, while maintaining flexibility to choose among more than 20 models. The post Evaluating performance and efficiency of the GitHub Copilot agentic harness across models and tasks appeared first on The GitHub Blog .

Run best open-weights models in Cline for $9.99/month Discussion | Link

So much for voluntary review.

Android 17 is getting a dedicated gaming mode for foldables that will put a virtual gamepad with touch controls on half of your screen to theoretically make it easier to play games. With foldable gaming mode, which is set to launch in the coming months, the virtual controller emulates physical button presses at a system […]

The country was hit hard by a pair of quakes that happened in quick succession and were likely driven by stress being transferred from one part of the fault that runs through the country to another.

The code runs. That's not the question. There's a failure mode with AI-generated code...

YouTube is adding even more TikTok-like features to Shorts, including a new "clear screen" mode that removes the icons and text from the video you're watching. In a blog post on Thursday, YouTube says it's also replacing the "thumbs-up" button with a "heart" icon, and is introducing a new option that lets you watch Shorts […]

I spent three iterations on an auto-fix pipeline that still doesn't work reliably. Here's what I learned. Loop 1 Wrote a background script. Pull tickets from Azure DevOps, run them through a local model, hand to a coding agent, push the result. Poll → triage → fix → push. Worked 40% of the time on trivial tickets. Anything that crossed file boundaries or needed real context — stalled or hallucinated. I shipped it anyway. That was naive. Loop 2 Made it smarter. Pre-selected relevant files. Broke big tickets into subtasks. Turned complex edits into atomic steps with verification between each. Got it to 55% or so. But every fix created two new edge cases. The complexity was compounding faster than the reliability. Loop 3 Went all in. Embeddings for dedup. Multi-repo routing. Auto-revert. A learning loop that fed failures back into future runs. The model server started dying. 890 memory errors in a day. Root cause: two independent consumers hitting the same local model server, each with its own retry loop. When memory filled up, retries amplified instead of staggering. The system was making itself worse. Fixes were simple in hindsight — stop retrying OOM, serialize access, use the local binary not npx. But the pattern kept repeating: add more to fix the last thing, break something else. Where I'm At The pipeline still only works on easy tickets. Hard ones need a human. After three rounds, the main thing I learned is that local models hit a wall before your ambition does — not in quality, in working memory. And adding features doesn't fix reliability gaps. It just moves them around. The 507 retry spiral taught me more than any successful deploy this year. Because it was entirely my fault. Not the model's, not the framework's. I built concurrent consumers with independent retry loops and expected them to coordinate. They didn't. What's Next I'll do a fourth loop. Smaller. A dedicated fast model for cheap work, the big model only for editing. One consumer at a time. Might