标签：#ha

Every time your bot merges a two-hour-old release into main, you are trusting a stranger's freshly published tarball to be the same one everyone else is looking at. Sometimes that release is a real bugfix. Sometimes it is a maintainer who fat-fingered a token, or an attacker who did not, and either way your CI cheerfully rebases against it before anyone had a chance to notice. On 2026-07-14, GitHub added a pause. Not a big one. But a real one. The actual change Dependabot version updates now sit on their hands for three days after a package is published. According to the GitHub Changelog, a release has to have been available on its registry for at least that long before Dependabot will open a version-update pull request against your repository. The cooldown is on by default and requires no configuration. It applies across every ecosystem Dependabot supports on github.com, and GitHub Enterprise Server picks it up in GHES 3.23. Security updates are exempt. If a fix for a known vulnerability lands, Dependabot will still open the PR the moment it can, because a three-day delay on the patch defeats the entire point of shipping the patch. That single carve-out is the whole design. Why three days is doing so much work Three days is not enough time to audit a package. Nobody is pretending otherwise. What three days is enough for is someone else to notice. Most malicious releases that end up on a public registry get pulled quickly once security researchers, downstream maintainers, or the registry's own scanners spot the pattern. The typosquats, the hijacked accounts, the crypto miners buried in a postinstall script: they all rely on being pulled into build automation before the pattern is visible. Dependabot's old default was to be that automation. Its new default is to let the pattern show up first. You can read this change as GitHub quietly admitting that "always up to date" was the wrong marketing promise for a supply-chain tool. The knob, and what shifted about it Cooldo

I found a slow, insidious memory leak in a Node.js API gateway caused by lingering event listeners; I fixed it by scoping emitters per request, enforcing cleanup in finally blocks, and adding leak‑aware tests and runtime safeguards—memory usage flattened and OOM restarts stopped. The Incident The gateway handled TLS termination, auth, and request fan‑out for many microservices. Over weeks its resident set size climbed in a staircase pattern until Kubernetes began OOM‑killing pods under load. The failure was gradual —light traffic ran for days, peak traffic crashed in hours—so it escaped casual monitoring. Investigation Heap snapshots and allocation profiles showed growing counts of small objects —closures, request metadata, and event listeners—rather than one giant allocation. Tracing revealed an internal event bus where request‑scoped listeners were attached but not always removed: an early‑exit authentication path returned before the cleanup function ran, leaving listeners that held references to request state. The GC saw those objects as live and never reclaimed them. The Fix (technical details) 1. Scoped emitters per request. Replace global emitters for request‑local concerns with a short‑lived EventEmitter created at request start. When the request ends, the emitter goes out of scope and the whole closure graph becomes collectible. 2. Guaranteed teardown via try/finally . Wrap the entire request pipeline so cleanup runs on success, error, or early return; the finally detaches any remaining listeners, clears timers, and releases caches. 3. Leak‑aware CI tests and runtime metrics. A harness simulated thousands of requests across code paths, captured heap snapshots, and asserted bounded object counts. Production metrics tracked listener counts and emitted alerts when thresholds were exceeded. 4. Operational safeguards. Added backpressure on accept queues, a soft memory threshold that disabled nonessential tracing, and rollout halting on excessive crash loops. Thes

The device is weirdly described as involving "mechanical elements that can move on their own" and the Bloomberg report includes the detail that the device is designed to "feel like a companion and become a physical manifestation of OpenAI’s ChatGPT."