Bluesky formally launched with its first product that provides visibility into Snowflake workload usage and costs as well as actionable insights and workload specific recommendations for maximum optimization. The company has raised $8.8 million in seed funding led by Greylock with participation from angels Ashish Thusoo (co-founder of Qubole), Jeff Hammerbacher (co-founder of Cloudera) and Johannes Gehrke (Microsoft Redmond research director).

Bluesky plans to use the funding to expand its offerings for Snowflake users and to span other cloud-based data systems.

Bluesky co-founders Mingsheng Hong (CEO) and Zheng Shao (CTO) used their rich experience building global scale data systems at Google and Uber to ensure Bluesky goes beyond mere cost visibility to provide deep insights into how data is being used and the wider implications.

Bluesky provides high-value, actionable insights, driven by intelligent automation that understands the data-specific challenge of workload optimization and cost governance. Bluesky analyzes query workloads to detect similar groupings, using an innovative technology it calls query patterns.

By intelligently watching for similar query patterns, Bluesky can detect complex situations that simplistic visibility tools miss. Bluesky can suggest high-impact tuning options for valuable workloads, increasing efficiency while also looking out for clear savings hiding inside the noise of regular operations, such as long-running queries that fail repeatedly without providing any value.

Tuning data layouts and warehouse settings is complex, particularly at scale. Bluesky’s smart workload analysis looks at the impact of warehouse idle time, instance startup time, cache warmup duration, and other parameters to provide recommendations specific to each organization, not generic rules-of-thumb.