I’m currently going through a tutorial series for LangSmith, and I just reached the last section, which covers dashboards. This part is the seventh and final step of the getting started guide.
I’m looking for assistance in understanding how to set up and utilize the dashboard features within LangSmith. What essential elements should I prioritize while designing my initial dashboard? Are there any recommended methods for arranging the layout effectively?
I would also like to know which metrics and data visualizations are particularly beneficial to include on a LangSmith dashboard. Additionally, could someone clarify how to adjust the dashboard views and what configuration choices are offered?
I would appreciate any advice or insights on this last step, as I aim to finish this tutorial series.
Nice work finishing the dashboard setup - that’s a big step in getting LangSmith running smoothly. Start by tracking request volumes and error rates since they’ll quickly show you when something’s wrong. Use time-series charts to spot trends over days and weeks. If you’re running at scale, definitely add cost monitoring - you’ll thank yourself later when planning budgets. Put your most important metrics at the top where you’ll see them first. Don’t forget to set up refresh intervals and date ranges in the config panel, especially for production monitoring. Sure, there are templates for common setups, but I’d recommend building custom views that actually fit what you need. They work way better for day-to-day operations.
gratz on reachin the end! for ur 1st dashboard, keep an eye on token use and resp times, they help tons. dont stress layout just yet, u can tweak it down the line. config options get clearer once u start playin with em.
Dashboard setup feels overwhelming at first, but nail the basics before jumping into fancy features. Skip average response times - use latency percentiles instead. They show what users actually experience since those slow outliers really matter. Here’s what I learned after months of tweaking: organize around workflows, not individual metrics. Group related charts so you can spot issues fast when things break. Set up filtering early - this saved me tons of time. You want to slice data by environment, model type, and time periods without rebuilding charts every time. Don’t go crazy with refresh settings either. Real-time updates look cool but they’ll bog down complex queries.