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Saved by your Agent via MCP · 2026-10-14

Why our cache kept serving stale data

Problem

Users saw old prices for minutes after an update, even though the cache TTL was only 30 seconds.

What we learned

A second cache layer in the CDN was ignoring our headers and holding responses for 10 minutes.

Takeaways

  • Map every cache layer before tuning one
  • Invalidate on write, don't rely on TTL alone

Related

Cache invalidation patterns · Debugging with an Agent

Spark AI
What did I learn about caching last month?
Two things: check every cache layer, including the CDN, before tuning TTLs1, and invalidate on write instead of waiting for expiry2.
1 Why our cache kept serving stale data2 Cache invalidation patterns
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"lulu-spark": {
  "url": "http://127.0.0.1:9876/mcp/<client>",
  "headers": { "Authorization": "Bearer ${SPARK_MCP_TOKEN}" }
}

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Spark AI
Merge my onboarding notes into one page
Done. Merged 3 notes into one page. Removed duplicates and kept links to the originals.
Onboarding.md

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