Playbook: audit your status-code distribution
Healthy median: 200s = 91.3%, 3xx = 5.1%, 4xx = 2.8%, 5xx = 0.2% (across 240 crawls). Deviation flags specific failures.
Checklist:
— Step 1: build the full distribution, compare each band to the median above
— Step 2: 3xx above 12% ▓▓▓▓▓▓▓▓░░ → audit redirect chains; median chain length should be 1.0, p90 ≤ 2
— Step 3: 4xx above 6% → pull top broken-link sources; usually 4-5 templates emit 80% of them
— Step 4: any 5xx ↑ vs. baseline → check during your crawler's peak concurrency (often timeout, not real outage)
— Step 5: log the distribution monthly; track 5xx as a leading reliability metric
So what: 5xx rate is the one band where 0.2%→1.0% predicts ranking loss before traffic drops. Watch the delta, not the absolute.
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В @CrawlBudgetMyths такого crawl budget myths ещё много
Healthy median: 200s = 91.3%, 3xx = 5.1%, 4xx = 2.8%, 5xx = 0.2% (across 240 crawls). Deviation flags specific failures.
Checklist:
— Step 1: build the full distribution, compare each band to the median above
— Step 2: 3xx above 12% ▓▓▓▓▓▓▓▓░░ → audit redirect chains; median chain length should be 1.0, p90 ≤ 2
— Step 3: 4xx above 6% → pull top broken-link sources; usually 4-5 templates emit 80% of them
— Step 4: any 5xx ↑ vs. baseline → check during your crawler's peak concurrency (often timeout, not real outage)
— Step 5: log the distribution monthly; track 5xx as a leading reliability metric
So what: 5xx rate is the one band where 0.2%→1.0% predicts ranking loss before traffic drops. Watch the delta, not the absolute.
—
В @CrawlBudgetMyths такого crawl budget myths ещё много
Median crawl-to-index lag: 4.2 days
Across 287 mid-size sites (10k-500k URLs) we timed the gap between first Googlebot hit and first appearance in the index.
— p50: 4.2 days
— p90: 19.6 days ▓▓▓▓▓▓▓▓▓░
— Thin/duplicate clusters: 31.0 days, often never
The spread matters more than the median. Sites with a tight p50-p90 band (under 6 days) shared one trait: a flat link graph where new URLs sat ≤3 clicks from a hub. Sites with a 25+ day tail buried new pages 5-7 clicks deep.
So what: don't optimize your average. Hunt the p90 tail — those are the URLs Google crawled, judged marginal, and parked. Pull them up the click-depth ladder before you blame the crawler.
Across 287 mid-size sites (10k-500k URLs) we timed the gap between first Googlebot hit and first appearance in the index.
— p50: 4.2 days
— p90: 19.6 days ▓▓▓▓▓▓▓▓▓░
— Thin/duplicate clusters: 31.0 days, often never
The spread matters more than the median. Sites with a tight p50-p90 band (under 6 days) shared one trait: a flat link graph where new URLs sat ≤3 clicks from a hub. Sites with a 25+ day tail buried new pages 5-7 clicks deep.
So what: don't optimize your average. Hunt the p90 tail — those are the URLs Google crawled, judged marginal, and parked. Pull them up the click-depth ladder before you blame the crawler.
JS-rendered pages indexed 9.4 days slower than static HTML
Sample: 142 domains running the same content in both SSR and client-rendered variants (controlled A/B by template).
— Static HTML in index: median 2.1 days
— Client-rendered: median 11.5 days ▓▓▓▓▓▓▓▓░░
— Delta: ↑ +9.4 days for the render queue
Google's two-wave model isn't a myth — it's a measurable tax. The render queue had a p90 of 28 days on JS pages vs. 7 days static.
Second finding: pages over 1.8 MB of JS hit the longest render delays (correlation r≈0.61 between JS payload and render lag).
So what: every kilobyte of render-critical JS is a withdrawal from your index speed account. SSR your money pages; let the marketing fluff hydrate client-side.
Sample: 142 domains running the same content in both SSR and client-rendered variants (controlled A/B by template).
— Static HTML in index: median 2.1 days
— Client-rendered: median 11.5 days ▓▓▓▓▓▓▓▓░░
— Delta: ↑ +9.4 days for the render queue
Google's two-wave model isn't a myth — it's a measurable tax. The render queue had a p90 of 28 days on JS pages vs. 7 days static.
Second finding: pages over 1.8 MB of JS hit the longest render delays (correlation r≈0.61 between JS payload and render lag).
So what: every kilobyte of render-critical JS is a withdrawal from your index speed account. SSR your money pages; let the marketing fluff hydrate client-side.