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EN — 2026

分享我们的思考与学习。

WYN 关于定制软件、AI、技术 SEO、性能与安全的笔记。

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关于定制软件、人工智能、网络安全、最新软件公告和可见性的备注,这些都能真正帮助您做出决策。

首先显示最新帖子·4 / 6

SYSTEMS

Logs, metrics and traces: what do we see before the system breaks?

Observability is not about finding someone to blame after an error; it is about making system behaviour understandable.

29 September 20268 min read
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CURRENT / AI SECURITY

Which risks does the OWASP LLM Top 10 2026 remind us of?

Protecting the model is not enough; the output, plugins, data sources and agent permissions need protection too.

29 September 20269 min read
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RELIABILITY

SLO, SLA and error budget: what does 99.9% really say?

Instead of presenting uptime percentage alone, tie user experience to measurable goals and technical priorities.

29 September 20268 min read
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PRIVACY

Privacy by design: a decision from the start, not a document afterwards

Protecting personal data is not only about writing a notice; it is about designing the product so it never needs unnecessary data.

28 September 20268 min read
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CURRENT / GOVERNANCE

What does NIST’s AI-assisted cyber security approach say?

Using AI in security requires increasing analysis and reporting capacity without removing human decision responsibility.

28 September 20267 min read
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DATA & OPERATIONS

How do you plan a zero-downtime data migration?

Moving users to a new structure without making them wait needs a controlled transition plan, not a one-off copy.

28 September 20269 min read
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COOKIES

Cookie consent is not just a pop-up

Instead of bundling mandatory technical records with ad tracking in one button, what is required must be separated clearly.

27 September 20266 min read
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CURRENT / CLOUD

Why is following the Kubernetes CVE feed not enough?

Whether a vulnerability affects your cluster depends on configuration and components, not only on the CVE title.

27 September 20268 min read
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SEO & CONTENT

Content decay: when should old articles be updated?

SEO is not only producing new articles; it is regularly improving content that is no longer correct, complete, or meeting search intent.

27 September 20267 min read
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LOCAL ARTIFICIAL INTELLIGENCE

When is local AI the right choice?

An in-house model or local inference makes sense not for every problem, but when data control, latency and operations needs are clear.

26 September 20269 min read
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