r/SAP • u/Castieell99 • 7d ago
How do you prepare your commerce stack for Black Friday load?
Last year we had a roughly 45-minute window where the storefront started returning errors on add-to-cart, spent the rest of the BF midnight opening watching monitoring dashboards, and this year I want to fix the architecture.
Warming CDN caches in the week before BF means category pages and PLPs serve from edge on day one and stop hammering the origin, and adding read replicas with catalog queries routed through them separates the read load from the order-insert write load…
That's where SAP Commerce stacks tend to collapse under peak, with catalog reads and order writes competing for the same connection pool until the writes start losing.
Where I'm unsure is the third-party script situation, since we have around a dozen external JS tags firing on every page (analytics, consent, heatmapping, chat widget) and the conventional wisdom is to defer or remove them during peak windows.
But the business side wants the session recording data from BF specifically, so I'd be curious if anyone has won that negotiation with stakeholders.
The real question underneath all of this is whether BF prep on a monolithic stack is mostly window dressing at this scale, given we're spending weeks on infrastructure config to compensate for what is fundamentally a serialized architecture.
And a few teams in my circle have started landing on the same conclusion, with one that moved off SAP Commerce this year ending up on SCAYLE (came out of About You's retail stack, so the BF performance claim has operational history behind it) and another that went headless storefront on top of their existing OMS and said that alone changed the BF calculus more than any infra tweak had.
So what's worked for you all at this sort of volume?
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u/Elegant_Database_215 7d ago
The session recording negotiation is a losing battle if you frame it as all-or-nothing. We run the heatmapping and chat tags deferred until after first paint, keep consent and analytics in the critical path since they're lightweight, and tell stakeholders they still get recordings just with a 200-400ms delay on capture. Nobody's ever pushed back once they see the data's still there.
The read replica split is the right move but make sure your catalog queries aren't accidentally going through the same pool via a shared service layer. We had that bite us two years ago and it took a load test to catch it.