Smarter Snowflake budgets & adaptive warehouses in Slingshot

Maximizing the full potential of your investment in Snowflake requires more than just powerful infrastructure. It demands full visibility, control and proactive optimization. Today, we’re excited to share new features designed to help you take charge of your Snowflake environment, mainly:

  1. Adaptive warehouses and Gen2 warehouses impact to understand if Snowflake’s new warehouses have the ROI for you.

  2. Snowflake budgets and alerts for warehouses, accounts or LOB spending managed within Slingshot.

  3. ML forecasts for spend on the hourly level for speedy reactions to anomalies and cost spikes.

These new features help you optimize spend, boost performance and maintain operational excellence across your data ecosystem. Whether you’re looking to manage costs, test-drive Snowflake’s adaptive warehouses, or understand and react to cost anomalies, Slingshot has you covered.

By combining budget controls with actionable insights and ML-forcasts, you can transform Snowflake optimization from a reactive task into a strategic initiative. Read on for all the details. 

Adaptive and generation 2 standard warehouse optimization

Screenshot of Slingshot UI

Snowflake has recently launched two new compute types with the ultimate goal of simplifying warehouse management and improving query performance. These are the new generation 2 standard warehouses announced in early May 2025 and the most recently announced adaptive warehouses. 

We’re thrilled to share that Slingshot lets you easily try Gen1 vs Gen2 warehouses or go completely serverless with adaptive warehouses to see which option best matches your goals and needs. It helps you choose the right option for you, based on your actual costs and exhibited performance.

See the impact of adaptive warehouses

Snowflake’s newest adaptive warehouse capability is an exciting new feature that further simplifies warehouse management. With an adaptive warehouse, users don’t even need to select a warehouse size. Instead, Snowflake automatically routes each query to an appropriately sized compute, based on the individual query’s needs.

We’re excited to share that Slingshot can now help you verify whether adaptive warehouses are right for you. You can create adaptive warehouses in Slingshot, as well as seamlessly migrate existing standard warehouses to adaptive warehouses and see the before and after figures. Comparing the actual costs and warehouse performance before and after the change takes the guesswork out of compute optimization, grounding it in facts. 

Test generation 2 standard warehouses  

Snowflake’s second generation of standard warehouses are a recent upgrade to the original virtual warehouse offered by the platform. Gen2 warehouses run on faster hardware and come with smarter software optimizations to offer improved performance for some queries, especially DML operation (DELETE, UPDATE, MERGE) and table scans. 

With Gen2 warehouses, you still have control over the same parameters available for Gen1 warehouses, such as warehouse size and cluster count. And while the platform is not forcing an upgrade to the newer generation of warehouses, it is clear that this is the next step in the evolution of the standard virtual warehouse. 

We’re excited to share that you can now easily create, migrate, or otherwise test Gen2 warehouses directly from the Slingshot UI. Slingshot will then automatically log that action for easy before and after reporting. These reports help you see the impact of adaptive warehouses or Gen2 warehouses on your workloads, based on actual spend and warehouse performance. 

Snowflake budgets

Screenshot of Snowflake budget alert

Spend can easily grow beyond what was forecasted as workloads evolve and input sizes grow. Slingshot’s new Snowflake budget feature enhances Snowflake’s native budgets feature by adding the ability to set budgets that go across warehouses, teams and even accounts. This enables you to:. 

  • Set daily, weekly, or monthly Snowflake budgets within Slingshot

  • Determine your maximum spend by creating budgets for an individual warehouse, groups of resources, your entire Snowflake account or event cross-account budgets

  • Associate budgets with custom tags for additional flexibility to easily set spend limits for projects, customers, lines of business or any other tag 

But we didn’t stop there. As you approach your limit Slingshot will automatically notify the relevant users via email and onsite notifications, so that they can take action. 

Warehouse owners will automatically receive budget alerts for the resource they own and additional recipients can be added during the set up process. Recipients will be notified once you spend 80% of the budget and again when the budget has been completely exhausted.

ML forecasts for warehouses

Screenshot of ML forecasts in Slingshot

Sometimes costs spike unexpectedly. Slingshot’s new ML-powered cost forecasts for Snowflake warehouses helps you understand cost anomalies and react accordingly. See yesterday’s observed spend and today’s forecasted spend by the hour, along with min and max thresholds, to make better informed decisions.  

The ML model analyzes historical data to detect patterns it then uses to forecast cost trends with confidence intervals, based on the amount of variance seen historically. The result is an easy way to identify when actual costs deviate significantly from those expected and alert users when that occurs so that they can take action.

In the coming weeks and months, we aim to add more visualizations and alerting capabilities to help you transform Snowflake optimization from a reactive process to a proactive effort, so stay tuned!

Bonus feature: Data lineage costs

Screenshot of Slingshot features

As organizations scale on Snowflake, so do their data loading and transformation costs.  Slingshot data lineage addresses this head on with insights into inefficiencies in your data pipelines that are inflating costs with insights into the way data moves in your Snowflake account. 

This feature shows you data lineage throughout your Snowflake ecosystem, as well as the frequency in which tables are used. Seeing the cost of data movement through a lineage workflow provides you with context into your total cost per lineage.

Summary

Slingshot’s newest features put powerful tools at your fingertips for managing and optimizing Snowflake. With adaptive warehouse recommendations, flexible budgeting and alerts, and machine learning-powered spend forecasts you can make smarter decisions, prevent costly surprises, and ensure you're maximizing your investment in Snowflake. 

As you scale on the platform, Slingshot is here to help you stay ahead. With Slingshot, Snowflake optimization is no longer reactive but a proactive and strategic part of your data operations. 

Interested in learning more? Click here to book time with our data experts today!


Salim Syed, Vice President and Head of Engineering, Capital One Slingshot

Salim Syed is Vice President and Head of Engineering for Capital One Slingshot. He led Capital One’s data warehouse migration to AWS and is a specialist in deploying Snowflake to a large enterprise. Salim’s expertise lies in developing Big Data (Lake) and Data Warehouse strategy on the public cloud. Salim has more than 25 years of experience in the data ecosystem. His career started in data engineering where he built data pipelines and then moved into maintenance and administration of large database servers using multi-tier replication architecture in various remote locations. He then worked at CodeRye as a database architect and at 3M Health Information Systems as an enterprise data architect. He has a bachelor’s degree in math and computer science from Lewis & Clark College and a master’s degree from George Washington University.

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