ML-powered optimization for Databricks Jobs
ML-powered optimization for Databricks Jobs
The ease of serverless without the limitations. Slingshot's advanced ML models provide custom-tailored optimization for Databricks Jobs.
Custom-tailored optimization
High-impact optimization for your workloads
Slingshot's ML models are automatically fine-tuned on your workloads for data-driven modeling that result in high-impact optimizations.
Self-improving optimization
Self-improving machine learning models
Slingshot uses closed-loop feedback to continuously improve its recommendations based on the impact of the previous ones.
Variable-sized data
Seamlessly adapt to workload changes
A closed feedback loop enables ML models to adapt to changes, like data size growth or cost anomalies, before they impact the business.
Any workload
Works with your jobs
Our ML models can automatically train on any workload, including ETL jobs, LLM jobs, ML jobs, periodic jobs, large jobs and short jobs.
Additional features