Bluesky formally launched with its first product that provides unprecedented visibility into Snowflake workload usage and costs as well as actionable insights and workload specific recommendations for maximum optimization. Bluesky is already delivering value at well-known brands.

“At Coinbase, our in-house data teams are always trying to improve how we use data to drive business value. Bluesky’s continuous cost governance capabilities and actionable insights have helped us to cut costs and improve the performance of query workloads without any reduction in functionality,” said ​​Michael Li, VP of Data at Coinbase. “With Bluesky’s intelligent monitoring and smart alerting, we’re able to simultaneously reduce waste while improving the value we get from our data.”

Modern cloud-based data systems like Snowflake have helped data teams find incredible insights with novel techniques but existing tools make efficient management of data at scale challenging. Manual tuning is complex and time-consuming while homegrown tools divert resources and attention from data teams busy keeping up with the scale and pace of the business they serve.

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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 understands how patterns across the whole data fleet combine to add value or waste money. We’re able to clearly explain how to achieve the business value our customers are looking for. Bluesky’s intelligent monitoring ensures our recommendations stay relevant as our customers innovate with data. With Bluesky, customers can make informed decisions with confidence, now and in the future,” said Mingsheng Hong, co-founder and CEO of Bluesky.

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. Data teams can skip the tedious manual trial-and-error process of tuning and use Bluesky’s automation to quickly find optimal data layouts and warehouse settings, letting them focus on generating business value from data.

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Industry Analysts on Bluesky: 

• “The same traits that make cloud data easy to use also make it hard to manage from a financial perspective,” said Hyoun Park, Chief Analyst of Amalgam Insights. “Bluesky has developed an elegant solution for handling cost and workload governance challenges of cloud data and solving the challenges of the IT Rule of 30 that states that any unmanaged IT spend category averages 30% in waste. Data is no exception and Bluesky is a valuable prescription for unwieldy cloud data environments.”
• “Enterprises embrace cloud data warehouses such as Snowflake in part because the elastic infrastructure gives them unprecedented flexibility to support dynamic workloads. But elastic infrastructure can have elastic costs that break budgets when workloads increase,” said Kevin Petrie, VP of Research at Eckerson Group. “Bluesky seeks to address this problem by giving enterprises new visibility into the cost implications of workload changes and recommending ways to optimize performance more cost-effectively.”
• “As many enterprise practitioners have discovered, moving analytical data to the cloud opens up a host of opportunities to put data to work with greater ease and greater efficiency,” said Bradley Shimmin, Chief Analyst, AI Platforms, Analytics and Data Management. “However, with greater access to powerful cloud-native functionality such as immediate and automated resource provisioning, comes the even greater responsibility to understand, control and optimize the incredibly complex dance of underlying resources that underpin even the simplest of tasks, beginning with the execution of a set of SQL queries together constituting a business task, as we see with Bluesky and Snowflake together.”

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Bluesky Raises $8.8 Million in Seed Funding Led by Greylock

Today Bluesky also announced that it has raised $8.8 million in seed funding. The round was 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).

Jerry Chen, partner at Greylock Partners, said: “The dual trends of increasing enterprise cloud consumption and vast data scale provide a huge opportunity for Bluesky. Enterprises gain enormous value from data clouds already, but the market is still in its infancy. As enterprises expand and mature their use of data clouds, they will increasingly need products like Bluesky to assist their data teams to manage complexity and scale, just as we’ve seen in other markets. Bluesky has already moved beyond simple visibility tooling to provide the intelligent monitoring and smart tuning recommendations more advanced enterprises need. Bluesky is well positioned to capture a substantial portion of the value in this growing market, and we’re excited to see the team continue to execute on their vision.”

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