Snowflake Optimization Startup Bluesky Launches With $8.8M in Funding

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Smart workload optimization and cost governance startup Bluesky launched its first product today and announced it has raised $8.8 million in a funding round led by Greylock Partners to extend its offerings to Snowflake Inc. users and to cover other cloud-based data systems.

The company was founded by CEO Mingsheng Hong and CTO and Zheng Shao, two engineers who previously worked at Google LLC and Uber Technologies Inc. Bluesky’s first product provides visibility into usage and costs Snowflake’s workload. The service provides actionable insights and workload-specific recommendations for maximum optimization.

Bluesky says that while modern cloud-based data systems like Snowflake have helped data teams find insights with new techniques, existing tools make managing data at scale a challenge. Manual tuning is complex and time-consuming, while in-house developed tools divert resources and attention from busy data teams to keep up with the scale and pace of the business they serve. This is where Bluesky comes in.

The company says its product goes beyond simple cost visibility to provide deep insights into how data is being used and the broader implications. Bluesky’s actionable insights are driven by intelligent automation that understands the data-specific challenge of workload optimization and cost governance.

Bluesky’s service analyzes query workloads to detect similar groupings, using a technology it calls “query patterns.” By intelligently monitoring similar request patterns, the service can detect complex situations that simplistic visibility tools miss, suggesting high-impact tuning options for valuable workloads and increasing efficiency. It does this while looking for clear savings hidden in the noise of regular operations, such as long-running queries that repeatedly fail without delivering any value.

To adjust data layouts and warehouse settings at scale, Bluesky’s intelligent workload analysis examines the impact of warehouse idle time, instance startup time, cache warm-up time and other parameters to provide organization-specific recommendations. Data teams can use the service to skip manual trial-and-error tuning processes and instead use Bluesky’s automation to quickly find optimal data layouts and warehouse settings, allowing them to focus on generating business value from data.

“The dual trend of increasing consumption of enterprise cloud and large data scale presents a huge opportunity for Bluesky,” said Jerry Chen, partner at Greylock Partners. “Companies are already getting tremendous value from data clouds, but the market is still in its infancy. As companies expand and mature their use of data clouds, they will increasingly need products like Bluesky to help their data teams manage complexity and scale.

Although Bluesky is only releasing its first product into general availability today, the company already has a large customer base. Notable clients include Coinbase Inc., Certik, Nextbite Brands LLC, Overlay, Houseware, and Mux.

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