Our AWS server costs tripled overnight due to unoptimized database queries on our Magento ecommerce backend and I need immediate ways to cache catalog pages today
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Fan-out diagram
The searches the AI actually ran for this prompt.
SEED QUERY
Our AWS server costs tripled overnight due to unoptimized database queries on our Magento ecommerce backend and I need immediate ways to cache catalog pages today
2 real searches · 1 real-search pass
Badge and edge weight = share of passes that produced the query. Hover a query for its intent and routing format.
Query classes
Google's semantic query class for every sub-query: what kind of answer each search is after, simulated vs real.
Classifying 2 queries…
Searches and sources
ChatGPT2 real searches · gpt-6
Adobe Commerce Magento 2 full page cache Varnish Redis configuration official documentation CloudFront caching AWS architecture Google ↗
AWS CloudFront caching dynamic ecommerce Magento cache policy cookies query strings official documentation Google ↗
- Cache management · experienceleague.adobe.com
- Reference Architecture · experienceleague.adobe.com
- Caching Overview and Configuration Options · experienceleague.adobe.com
- Understand cache policies · docs.aws.amazon.com
- Cache content based on query string parameters · docs.aws.amazon.com
- Cache Backend Options and Storage Reference · experienceleague.adobe.com
- Configure Redis for Default and Page Cache · experienceleague.adobe.com
Queries
2 queries · click a column to sort
| Query / type | Search | Intent | Query class | Routing format | Cluster | Freq ↓ | Weight |
|---|---|---|---|---|---|---|---|
Adobe Commerce Magento 2 full page cache Varnish Redis configuration official documentation CloudFront caching AWS architecture OBSERVED | Google ↗ AI Mode ↗ | — | — | — | — | 1x of 1 | |
AWS CloudFront caching dynamic ecommerce Magento cache policy cookies query strings official documentation OBSERVED | Google ↗ AI Mode ↗ | — | — | — | — | 1x of 1 |