tag: latency
articles: 2 · beats: 2
latest: October 20, 2026
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Latency
2 Crashtech articles on Latency, spanning Ai Infrastructure and System Design & Architecture, published between August 2026 and October 2026. Every piece is full-text HTML with sources, structured data and an authored FAQ.
They span Ai Infrastructure (1), System Design & Architecture (1). Ai Infrastructure System Design & Architecture
Why LLM Serving Teams Are Turning KV Cache Transfer Into a First-Class Design Choice
Two new vLLM transfer techniques target first-token latency by overlapping movement and reusing multi-turn context. See where each helps and what it costs.
Time-Travel Fairness: How Servers Rewind for Lag Compensation
Why lag compensation rewinds the game world to when a shot was fired, and why victims experience the cost.
Questions we answer about Latency
- What is KV cache in LLM inference?
- Are the reported vLLM speedups guaranteed in production?
- When should a team consider these approaches?
- Why does lag compensation exist at all? Can't players just aim for where the enemy is now?
- How does the server know what time the client fired the shot at?
- What happens to the player who gets shot from behind cover? Is that not unfair to them?
- How far back can the server rewind? Can it go back 500ms or 1 second?
- What happens if the ring buffer doesn't have a snapshot for the timestamp on the packet?
Frequently asked questions
What does Crashtech publish about Latency?
2 articles tagged Latency, the most recent published October 20, 2026. They span Ai Infrastructure (1), System Design & Architecture (1). Each carries numbered sources, an authored FAQ and full structured data.
What questions about Latency does Crashtech answer directly?
8 questions have a dedicated answer page under this tag, including “What is KV cache in LLM inference?”. Each answer is authored prose from the article it belongs to, not a generated summary.
Can AI assistants read Crashtech's Latency 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.