Every few years the industry rediscovers that programming languages are not religions. Then we immediately behave like they are religions. Someone posts a benchmark. Someone else says memory safety. Someone says developer experience. A distributed systems person appears from under a bridge and whispers “Erlang solved this in 1998.” A startup founder announces they are rewriting their CRUD app in R
Or: how we learned that “eventually” isn’t good enough when you’re bleeding file descriptors Or: how we learned that “eventually” isn’t good enough when you’re bleeding file descriptors Deterministic cleanup means knowing exactly when resources are freed — the difference between memory chaos and predictable system behavior in production environments. So our video transcoding service was… how d
Our goal has always been to be the go-to blockchain node platform across any chain and environment. Today, that includes the nodes you run on your own hardware. Running your own Ethereum infrastructure should be the basic right of every individual and household. Nodes should be easy. The catch? Self-hosting has always meant complexity. Manual setup, client updates, nodes falling out of sync, moni
This article was originally published on https://forg.to/articles/how-to-stop-hitting-claude-usage-limits *You're Paying for Claude. You're Also Wasting Most of It. I used to hit my usage limit by 2pm every day. Not because I was doing too much work. Because I had no idea how Claude actually charges you. Once I understood the real mechanic, everything changed. I now hit my limit maybe once a mont
The Challenge of Scalable Secrets Management in GitHub Actions For development teams scaling beyond a handful of repositories, managing environment-specific variables and secrets in GitHub Actions can quickly become a significant bottleneck. The manual duplication of configurations across multiple repos, especially when dealing with distinct environments like development, staging, and production
Most async APIs commit to one thing: starting your job. They return 202 Accepted, hand you a job ID, and that's where the contract ends. The rest is your problem. I do something different. I make one promise: When your job is done, I'll tell you accurately. Until then, I'll keep retrying. That's the entire contract for everything I've ever shipped. It sounds small. In practice, it's the only thing
Three weeks later, backup verification jobs are silently failing. Monitoring dashboards are dark. The on-call team is operating without baselines. Nobody knows what normal looks like on the new platform. The VM conversion worked. The migration did not. This is the lift-and-shift KVM fallacy — and it isn't a KVM problem. It's a scoping problem. Most VMware-to-KVM migration plans capture the visible
Harbor cities understand accumulated risk. Cargo moves in quietly. Weather shifts by degrees. One bad assumption can sit unnoticed until it reaches critical mass. Halifax has lived with that kind of memory for more than a century. On December 6, 1917, a collision in Halifax Harbor triggered the largest man-made explosion prior to the atomic bomb, a disaster that directly changed the lives of over