🔥 shanraisshan / claude-code-best-practice - from vibe coding to agentic engineering - practice makes cla
GitHub热门项目 | from vibe coding to agentic engineering - practice makes claude perfect | Stars: 59,083 | 329 stars today | 语言: HTML
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GitHub热门项目 | from vibe coding to agentic engineering - practice makes claude perfect | Stars: 59,083 | 329 stars today | 语言: HTML
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GitOps policy drift is what happens when a control plane keeps a policy perfectly reconciled long after the reason for that policy has stopped being true. Every commit is applied. Every pull request is merged cleanly. Every dashboard reads green. And the rule being enforced no longer reflects anything anyone would choose to enforce today — it just hasn't been told to stop. That gap is the subject of this post. Not configuration drift — the thing GitOps was built to kill — but a second, quieter failure mode that lives one layer above it: the policy is right by every technical measure and wrong by every practical one, and nothing in the reconciliation loop is capable of telling the difference. The Promise GitOps Actually Kept GitOps earned its place in the infrastructure as code architecture stack by solving a real and expensive problem: state drift. Before declarative reconciliation, infrastructure diverged from its source of truth constantly — a console change here, an emergency hotfix there, a manual override nobody logged. The git repository said one thing. Production said another. Reconciling the two was a forensic exercise. GitOps closed that gap with a simple, durable mechanism: a controller that continuously compares declared state to actual state and corrects the difference without waiting for a human to notice. That's not a small win. It's the reason platform teams can run infrastructure at a scale that would have been operationally unmanageable a decade ago, and it's why GitOps controllers sit at the center of nearly every modern infrastructure as code architecture built since. This post isn't an argument against that mechanism. It's an argument that the mechanism's success created a blind spot nobody designed for. What GitOps Never Promised to Solve Here's the boundary GitOps was never built to cross: reconciliation proves that declared state and actual state match. It says nothing about whether the declared state should still exist in its current form. A
GitHub热门项目 | Use claude code and codex for free in the terminal, VSCode extension, and discord like OpenClaw (voice supported) | Stars: 36,218 | 258 stars today | 语言: Python
As of June 1, 2026, all GitHub Copilot plans run on usage-based billing. Premium request units are gone. What replaced them is a token-metered currency called GitHub AI Credits: one credit equals one cent, and every model interaction converts into credits based on the input, output, and cached tokens it consumes, charged at each model's published rate. GitHub's framing is that Copilot outgrew its old pricing. A one-line completion and a multi-hour autonomous run used to cost the same, and once agentic use went mainstream, that flat rate stopped matching the compute behind it. Tying the price to tokens fixes the mismatch. If your Copilot use is mostly autocomplete, this barely registers. If you drive Copilot as an agent from the terminal, it changes which moves cost money. Here's the practical shape of it. Requests out, tokens in Old model: each interaction cost one premium request, scaled by a per-model multiplier, drawn from a monthly request allowance. New model: each interaction costs whatever its tokens cost on the model you picked. Every paid plan still ships with a monthly pool, now denominated in credits, with the option to set a budget for usage past it. Published figures put the included pool at 1,500 credits for Pro, 7,000 for Pro+, and 20,000 for Max, with pooled per-user allowances on Business and Enterprise. Worth knowing if you pay yearly: annual Pro and Pro+ subscribers stay on the request-based model until the term ends, and several model multipliers went up for them on June 1. An annual plan doesn't dodge the change. It postpones part of it while making the strong models eat more of the old allowance. Autocomplete is untouched Before anyone starts rationing, here's the part that didn't move. Inline completions and Next Edit Suggestions are still unlimited and still free. If your day is mostly tab-completion in the editor, your costs read identical to May. Nothing to monitor there. The meter lands on the rest: chat, and especially the agentic runs th
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