Advanced · Remember answers so you don't ask twice.
Caching
Reading from memory takes milliseconds; asking a database or an API takes hundreds. A cache trades freshness for speed, and the hard part is deciding how stale is acceptable.
Try this
Run each experiment in the simulator above, then tick it off.
Key ideas
Hit, miss, TTL
A hit is served from memory. A miss goes to the source and fills the cache. TTL is how long an entry lives.
Invalidation is the hard part
When the source changes, either wait out the TTL or delete the cached entry yourself.
Cache what's read often and changes rarely
Catalogs, settings, exchange rates. Not account balances.
In your Pabbly workflows
If a workflow looks up the same thing on every run (a price list, a mapping table, a token), fetch it once and keep it in a sheet or variable instead of calling the API each time. Fewer calls, fewer rate-limit errors, fewer tasks.
Check yourself
0/2Get every question right to mark this lab done. Wrong answers let you try again.
Q1. TTL is…
Time To Live: once it runs out, the next read is a miss and fetches fresh data.
Q2. The main risk of a long TTL?
A long TTL means more hits and less load, but a change at the source stays invisible until the entry expires.
Lab complete
Marked done on this device. On to the next one.
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