tag: conflict-resolution
articles: 2 · beats: 1
latest: July 31, 2026
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Conflict Resolution
2 Crashtech articles on Conflict Resolution, filed under System Design, published in July 2026. Every piece is full-text HTML with sources, structured data and an authored FAQ.
All 2 sit in the System Design beat. System Design
Vector Clocks: Detecting Causality in Distributed Systems
Vector clocks solve distributed ordering: when wall-clock timestamps fail to detect concurrent writes, vector clocks reveal true causality and conflicts.
Operational Transforms vs CRDTs
Why Google Docs needs a server and Figma doesn't: how two competing approaches to concurrent editing resolve the same-string conflict, and when each wins.
Questions we answer about Conflict Resolution
- Why can't we just use wall-clock timestamps to order events across machines?
- How does a vector clock detect concurrent events?
- What is the 'happened-before' relationship and why does it matter?
- Why do vector clocks grow in size as clusters scale?
- What systems actually use vector clocks in production?
- What is the index-shift problem in concurrent editing?
- Why does Operational Transform require a central server?
- How do CRDTs avoid needing a server?
- What's the metadata cost of using CRDTs?
- When is OT the better choice?
Covered alongside
Frequently asked questions
What does Crashtech publish about Conflict Resolution?
2 articles tagged Conflict Resolution, the most recent published July 31, 2026. All 2 sit in the System Design beat. Each carries numbered sources, an authored FAQ and full structured data.
What questions about Conflict Resolution does Crashtech answer directly?
10 questions have a dedicated answer page under this tag, including “Why can't we just use wall-clock timestamps to order events across machines?”. Each answer is authored prose from the article it belongs to, not a generated summary.
Can AI assistants read Crashtech's Conflict Resolution coverage?
Yes. Crashtech serves full static HTML to every crawler, allows all major AI user agents in robots.txt, and publishes an llms.txt manifest plus a full-text corpus, so assistants can retrieve and cite these articles directly.