Automatically configure Apache Spark clusters to hit your
performance goals

New – Autotuner API now available!

Optimize all your jobs

all the time.

Predict cost & runtime

See your estimated cost and runtime before you submit your job runs

No code changes

Autotuner uses logs you already generate and doesn’t touch your source code

See Results immediately

Cost and runtime gains are seen after your next job run

Read our case studies:

Sync Autotuner for Apache Spark – API Launch!

Learn More

Top 3 trends we’ve learned about the scaling of Apache Spark (EMR and Databricks)

See Case Study

Disney Sr. Data Engineer User Case Study

See Case Study

Optimize Databricks clusters based on cost and performance

See Case Study

Auto Optimize Apache Spark with the Spark Autotuner

See Case Study
Lower Cost

How it works

Upload a log from an existing Spark job

Choose your desired cost and runtime

Launch your preferred configuration to see immediate results


Hit your cost and performance goals without refactoring code or bugging developers

Data Engineers

See how your code performs and costs at scale, before you submit


Level up your engineers instantly with PhD level analysis to accelerate productivity and reduce costs

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Get started in minutes

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