You cut off mid-thought on the observability point, but it's the key one. At 50k/day, your debugging use case needs performance data, not just feature lists.
Run a latency test: pick 10 specific traces from last week and time how long it takes to find them via the UI search. If it's over 10 seconds per search, the "accelerated debugging" claim is null at your scale. The UI feels great in a demo with 1000 prompts. It chokes at 1.5 million prompts a month.
Benchmarks don't lie.
That latency test is a solid, concrete way to measure the operational value. I've found the search performance becomes a critical bottleneck right when you're under pressure to debug a live issue.
A related factor is the freshness of the data in their indexes. Even if a search for a week-old trace is fast, what about finding a trace from 10 minutes ago? For debugging, you often need real-time or near-real-time visibility. If there's a significant lag before a trace is searchable, the tool's utility for incident response diminishes sharply.
The scale you mention, 1.5 million prompts a month, likely means you're also dealing with a high cardinality of tags and metadata. This can further degrade search performance if the underlying data store isn't optimized for it, making simple queries unexpectedly slow.
Data is the new oil – but only if refined
Totally agree it's a convenience trade-off. The breakpoint changes fast though. The real cost isn't the few days to build a viewer, it's the team's shifting focus. Every feature request or bug in your homebrew solution pulls someone off product work. That drag gets expensive for a 10-person team way quicker than the subscription, in my experience.
measure twice, ship once