I’m working through a tutorial series on LangSmith and I’ve reached the final part about dashboards. I need help understanding how to set up and use the dashboard functionality effectively.
I’ve completed the previous steps in the tutorial but I’m struggling with the dashboard section. Can someone explain how to create custom dashboards and what metrics I should be tracking? I want to make sure I’m getting the most out of this feature.
Any tips on best practices for dashboard configuration would be really helpful. I’m particularly interested in knowing which widgets are most useful for monitoring my LangSmith projects and how to organize them properly.
Dashboard setup becomes manageable once you understand the widget hierarchy. Start by separating your dashboards into development and production environments; mixing metrics can lead to confusion. I recommend placing latency and token usage widgets at the top, followed by error rates. Over time, I’ve found it’s effective to group related metrics together rather than overcrowding a single view. Organizing by themes is beneficial—keep cost monitoring distinct from performance metrics and include a time-range selector aligned with your deployment cycles. Many overlook the filtering options, but applying project-specific filters can save substantial time as projects scale. My initial mistake was tracking too many metrics simultaneously; it’s wiser to select three core metrics that genuinely impact your application and build from there.
Dashboard configuration finally clicked when I stopped copying tutorials and started solving my actual problems. Don’t add every widget you see - that just creates noise instead of useful insights. Work backwards: figure out what decisions you need to make about your LangSmith projects, then build dashboards that show exactly that data. Worried about costs? Focus on token consumption and request volume across different timeframes. Care more about performance? Track response times and success rates. Refresh intervals matter way more than people think. Set them right and you’ll avoid stale data without hammering the API. Here’s what worked for me: start with a simple dashboard showing 2-3 key metrics. Then expand it based on questions that come up during daily use. This way every widget actually serves a purpose instead of just filling space.
hey! i totally get how dashboards can be tricky. start with key metrics like run rates and errors. don’t overcomplicate it at first, just play around with it and see what suits your needs. you’ll get the hang of it!
Been there. LangSmith’s native dashboards turn into a mess once you’re tracking multiple projects.
I skip them entirely and pull data into automated workflows instead. Set up triggers to grab trace counts, latency, error rates - whatever you need - then push it to any dashboard tool you like.
The automation is key. Instead of wrestling with LangSmith widgets, my workflows track what matters for each project and alert me when stuff breaks.
If you’re just starting out, don’t bother with LangSmith’s dashboard setup. Build a simple automation that pulls your metrics and shows them however you want. Much more flexible and you’ll actually use it.