SOLUTIONS

Control runtimes to
hit critical SLAs

Save up to 50% on your compute costs with a ML-powered optimization engine that continuously monitors and fine-tunes
your compute clusters

Book a demo
See it in action

Control runtimes and meet all your critical SLAs with Gradient

Performance co-pilot/autopilot

The convenience of serverless with complete control over your compute infrastructure

Intelligent cluster config control

Pull the right levers. Gradient makes it easy to fine-tune your compute infrastructure to align with your business requirements and goals. Apply recommendations in a click, or auto apply them for scale.

Gradient optimized cluster configurations to meet your data pipelines and needs

Goal-based optimization

Determine compute resources by business objectives. Input your goals – whether it’s maximizing cost savings, minimizing runtimes, or meeting critical SLAs – and Gradient will optimize your clusters accordingly.

Set an SLA for Gradient to meet and it will hit it a the most cost-effective rate

SLA management

Ensure your data pipelines consistently meet runtime service level agreements without over-provisioning resources. Gradient enables you to obey strict runtime SLAs at the lowest price point.

Meet all your critical runtime SLAs, consistently

Cost-effective performance

Strike a balance between runtimes and cost. Gradient finds the most economical cluster configuration that still meets your runtime and SLA requirements. Cut costs while obeying SLAs.

Meet your SLAs as the lowest price point with Gradient

Fully customized models

Optimize runtimes per job. Our machine-learning models are fine-tuned to your workloads, ensuring you get the most relevant cluster optimization recommendations for your needs.

Get custom tailored optimizations based for your data pipelines

Adaptive resource allocation

Our machine learning models continuously learn from your workload patterns to dynamically adjust resources, ensuring optimal performance as your needs evolve.

Closed-loop feedback ensures our models improve over time

Built for complex pipelines

Gradient makes cluster optimization easy. Seamlessly adapt to varying data sizes and cyclic patterns. Effortlessly manage DAG dependent jobs and parallel jobs running on multiple nodes.

Optimize cyclic data pipelines and variable sized data pipelines with Gradient

Understand performance tradeoffs

Gradient shows you the cost and/or performance tradeoffs so you can decide if hitting a runtime SLA is “worth the cost,” or if a slower SLA will suffice.

Understand the tradeoffs between costs and SLAs

Key
benefits:

Precision control, goal-based performance, and SLA compliance

Shorten runtimes
and cut costs

Gradient reduces your Databricks compute costs while ensuring job performance meets your requirements and customer SLAs.

Granular
configuration control

Control every configuration setting, and tweak them to perfectly match your requirements in a matter of minutes with Gradient.

Continuous
improvements

Our ML models continuously monitor and optimize your compute infrastructure based on your workloads, even when they vary in size.

Self-improving
custom models

Each model is fine-tuned on a job using historical data, to ensure the recommendations are 100% customized to your data pipeline.

Co-pilot and
autopilot modes

Start with passive recommendations and transition to full autopilot mode as you scale on Databricks. Switch between co-pilot and autopilot modes in a click.

I’d be surprised if there was any data team on the planet that wouldn’t save money and time from using Gradient.

Jesse Lancaster, CTO, Forma.ai

“Gradient is an excellent tool that delivers real results that you can see in your monthly [data infrastructure] bill.”

Deniz Parmaksız, Sr. Data Engineer, Insider

“With automated optimization and scalable solutions, Gradient guarantees seamless pipeline operation.”

Blaine Elliot, Data Engineer, Abnormal

Explore
additional
use cases

Get started today

Take control of your Databricks runtimes and meet your SLAs with precision and efficiency

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