add boomlet info

src/about.py

@@ -26,7 +26,10 @@ TITLE = """<h1 align="center" id="space-title">BOOM 💥 Observability Time-Seri
 
 # What does your leaderboard evaluate?
 INTRODUCTION_TEXT = """
-BOOM (**B**enchmark **o**f **O**bservability **M**etrics) is a large-scale, real-world time series dataset designed for evaluating models on forecasting tasks in complex observability environments. Consisting of around 350 million time-series data points spanning 32,887 variables, the benchmark is derived from real-world metrics collected via Datadog, a leading observability platform. It therefore captures the irregularity, structural complexity, and heavy-tailed statistics typical of production observability data. 
+**BOOM** (**B**enchmark **o**f **O**bservability **M**etrics) is a large-scale, real-world time series dataset designed for evaluating models on forecasting tasks in complex observability environments. Consisting of around 350 million time-series data points spanning 32,887 variables, the benchmark is derived from real-world metrics collected via Datadog, a leading observability platform. It therefore captures the irregularity, structural complexity, and heavy-tailed statistics typical of production observability data. 
+
+To support research in resource-constrained settings, we also introduce **BOOMLET**, a smaller yet representative subset of the **BOOM** benchmark. It includes 32 metric queries, covering 1,627 variates and approximately 23 million observation points. It preserves key distributional properties while focusing on queries with more variates to ensure meaningful coverage.
+
 For more information, please refer to the [BOOM Dataset Card](https://huggingface.co/datasets/Datadog/BOOM) and the [BOOM GitHub repository](https://github.com/DataDog/toto?tab=readme-ov-file#boom-benchmark-of-observability-metrics)
 """