Faster and cheaper, or you don't pay.

Yes. LakeSail charges no service fee to prove one qualifying recurring Spark workload on Sail. You cover only the infrastructure and third-party costs used for the test. There is no obligation to migrate.

No. Your raw data and credentials never have to leave your environment. We prepare and version the run package, your operator reviews and runs it, and any sensitive correctness checking happens inside your environment. You share only the evidence you have approved, and your team authorizes every production command, cutover, and rollback.

You get the before-and-after result. If Sail earns a production move, LakeSail proposes one fixed production scope and price. You can approve it or stop. Nothing converts automatically.

We agree the scope of the production work and what it has to achieve before anything starts. That scope has to come back correct, faster, and cheaper. If it still misses after our remediation cycle, you do not pay LakeSail for the engineering on it. Anything else we delivered that did pass is unaffected, so one scope falling short never voids the rest. Your infrastructure costs remain yours.

Yes. The guarantee is about the workload, not the platform it runs on today. Databricks, Amazon EMR, AWS Glue, and self-managed Spark are the usual starting points. What decides whether a job qualifies is the job itself: whether its Python runtime, dependencies, and data access can be reproduced in the target deployment, and whether there is a baseline we can measure fairly against. Anything that depends on a proprietary feature of your current platform is identified during qualification rather than discovered mid-migration.

Sail runs Python inside the engine rather than shuttling rows across a JVM boundary, so Spark jobs that lean on Python, including feature engineering, embedding, and model scoring steps, are usually where the most headroom is. Recurring batch jobs remain the most straightforward starting point, and if something in yours is a poor fit we say so instead of guaranteeing it blind.

LakeSail handles the work between a promising test and an operable production job: compatibility changes, setup, integration, tuning, correctness validation, cost modeling, orchestration, monitoring, cutover, rollback, runbooks, and stabilization. Most of that is untangling what has built up around the job over the years rather than the job itself, and it is the part teams most want off their plate. We provide the custom features your workload needs. Sail is open source, so you can run it yourself. The service is for teams that do not want to discover the production path alone.