The Node (and more) Banter

Nitro gives you a clean, portable server. Whether you use it on its own or with Vite, you get consistent builds, familiar routing, and a smooth development workflow. But Nitro doesn’t explain what to do when you have several instances and a cron job, or when you need a gateway, metrics, and worker health checks. Nitro handles the server, but someone still has to manage the whole fleet.

In this episode of The Node (and more) Ba...

You spot a critical bug in production, fix it, deploy, and feel relieved. But then you notice the workflows that need the fix most, like 30-day subscription cycles, compliance timers paused for months, or approvals waiting on a signature, are still stuck on the old version. They never get the fix. That’s not a safety net. It’s a risk that never disappears.

In this episode of The Node (and more) Banter, Luca Maraschi and ...

Eve is a well-designed open-source agent framework. It offers a clean programming model, filesystem-based instructions and tools, and durable sessions built on the Workflow SDK. However, running Eve in a real enterprise Kubernetes environment needs extra infrastructure that isn't included by default. We built that missing piece, and in this episode, we share the full story of how Watt made it possible.

In this episode of The Node (a...

People keep saying that AI helps developers get more done. But few are asking who pays for the computing power, tokens, and time needed to keep the open-source projects behind AI running. Node.js maintainers often use their own servers, patch together free subscriptions, and struggle to get access to the latest models they need to strengthen the core infrastructure that supports the AI industry. So who ends up paying for all this?

I...

You launch a new product. Thousands of users click the same link at the same time. The cache is cold, and your Node.js app starts generating the exact same response hundreds of times simultaneously, burning CPU, hammering your database, and slowing down for everyone. This is the thundering herd problem, and most teams only discover it the hard way. So what if your gateway could just... not do that?

In this episode of The Node (and m...

"Zero downtime" doesn’t mean there’s no risk. When you release new code, some users still have the old version open in their browser, using outdated JS bundles and React state, without realizing anything has changed. Teams usually find out when a checkout fails or a form resets in the middle of a session.

In this episode of The Node (and more) Banter, Luca Maraschi and Matteo Collina break down the version skew problem f...

You deploy several times a day. Your team moves quickly, and your lead time is short. But each deployment can quietly disrupt users already on your site. There are no big warnings, just someone clicking around, suddenly running into errors because the app in their browser and your updated server are out of sync.

In this episode of The Node (and more) Banter, Luca Maraschi and Matteo Collina talk about version skew: what it is, why i...

A default set in May 2015 just got its first change. One constant. One number. And it was silently costing Node.js up to 26% throughput on some of the most common workloads in the ecosystem: file reads, HTTP parsing, stream chunking. Nobody broke it. Nobody was ignoring it. It was just stuck in a world that no longer existed.

In this episode of The Node (and more) Banter, Luca Maraschi and Matteo Collina explain how they investigate...

Memory and performance often compete with each other. Most developers only notice this tradeoff when something goes wrong, not during the initial design. At that point, the key decisions are already set.

In this episode of The Node (and more) Banter, Luca Maraschi and Matteo Collina talk about the memory-performance tradeoff from two sides: how to plan for it during design, and how to handle it at runtime if it becomes an issue. The...

Your Node.js service has rate limiting. You tested it, it worked, you shipped it. But your limit lives in the memory of a single process, and the moment you run more than one instance behind a load balancer, every replica enforces its own private budget. Ten instances means ten times the traffic you thought you were allowing. That is not a smaller problem at scale, it is a different problem entirely. So what does rate limiting that...

You set a CPU limit on your pod, the node has plenty of capacity to spare, and yet your Node.js service is throttled to a crawl. How does that happen? The answer lives deep in the Linux kernel, in the CFS bandwidth controller and cgroups, and most teams never look there. Requests and limits are not two knobs for the same thing. One drives scheduling, the other enforces a hard quota, and confusing them is how you end up paying for C...

Bun made the switch. Zig is out, Rust is in, and AI handled most of the work, with 98% of the test suite passing. The question is no longer hypothetical; it's real now. If an AI can port an entire runtime, why are so many enterprise teams still stuck on a Node 12 codebase they're afraid to update?

In this episode of The Node (and more) Banter, Luca Maraschi and Matteo Collina talk about the Bun Zig-to-Rust port, including the memory...

What started as a joke at the Node Collaborator Summit turned into the most compelling argument yet for why enterprises have no excuse left to avoid modernizing their native code.

In this episode of The Node (and more) Banter, Luca and Matteo are joined by Paolo, Principal Software Engineer at Platformatic, who built "Project Destino" — because in Italian, destino means doom, and yes, that's exactly how we name things.

That co...

Many teams believe autoscaling is simple: set a CPU threshold and let Kubernetes handle it. But if you get a three-minute traffic spike and your pods need two minutes to start, users feel the lag, the spike ends, and your new pods show up too late. What if your infrastructure could predict traffic instead of just reacting?

In this episode, Luca Maraschi and Matteo Collina challenge the usual autoscaling approach—HPA, KEDA, ECS...

Running AI agents in production isn't just about picking the right LLM. It's about the infrastructure decisions that make them safe, fast, and deployable at scale. Choosing between micro VMs, gVisor, Firecracker, or eBPF sounds like a systems engineering rabbit hole, until you realize the wrong choice can mean seconds of startup latency, infrastructure bloat, or an isolation model that doesn't match your actual threat surface.

In th...

Most teams building AI agents treat Kubernetes like it's optional. They spin up a Mac Mini, run their agent locally, and call it a day, until someone asks how to scale it, govern it, or deploy it across the enterprise. That's when the architecture falls apart. The question is: what does it actually take to run agents in production, at scale, inside the infrastructure you already have?

In this episode of The Node (and more) Banter, M...

Full-stack development is moving fast. TanStack Start is changing how we handle data fetching, routing, and server-client boundaries. AI tools like Claude are speeding up how we build and test these systems. But when it’s time for production, one question matters: how do you scale CPU-bound workloads like SSR without losing performance?

Luca Maraschi and Matteo Collina sit down with Tanner Linsley, creator of TanStack, to dig ...

Most developers let their AI assistant guess how to write Node.js. No context, no constraints, no history, just vibes and generic output. The result is code that ignores the event loop, skips proper error handling, and looks nothing like how senior engineers actually build. The question is: can you actually teach your AI to code like you?

In this episode of The Node (and more) Banter, Luca Maraschi and Matteo Collina dive into the e...

Workflows look easy… until they corrupt your data.

Durable workflows in Node.js promise retries, persistence, and long-running execution. On platforms like Vercel, everything just works. But the moment you move to Kubernetes, a hidden problem appears: version mismatch. A small code change can replay the wrong steps, mix results, and silently break your system.

The question: how do you run durable workflows safely in productio...