Run any python function, in any docker container, on any hardware, on thousands of VM's, until it's done.
Burla comes with a dashboard where I can monitor long running background jobs, it's open-source, and can be installed with one command. Even with thousands of vm's running (tested at 10K!), changes to code deploy and start running in around 2 seconds, vastly shortening the developer cycle compared to tools like GCP-batch and AWS-Batch.
Hi Product Hunt!
We're Jake, Jack, and Joe, and we're the makers of Burla, an open-source, batch-processing platform for python.
We were frustrated by how slow and difficult it can be to iterate on large batch processing pipelines.
Simple small changes necessitated rebuilding docker containers, waiting for GCP-batch, or AWS-batch pipelines to redeploy, and waiting for vm's to cold boot, a >5minute per iteration dev cycle, all just so I can see what error my code throws this time, then do it all over again!
Many other tools in the space were either too complicated, closed-source / managed only, too difficult to setup and manage, or simply too expensive.
This is why we created Burla, a way to just run my stupid python function, in whatever docker container I want, on whatever hardware I want, on thousands of VM's, until it's done.
It comes with a dashboard where I can monitor long running background jobs. It's open-source, and can be installed with one command.
Even with thousands of vm's running, changes to code deploy and start running in around 2 seconds, vastly shortening the developer cycle compared to tools like GCP-batch and AWS-Batch.
Our long term goal is to just make more cloud services simple, fast, and open-source.
We believe that, in general, whether you're coding locally, or on a cluster of 1000 machines, infrastructure should update and react quickly, like under-a-second quickly. We should be able to iterate at the speed of thought, not at the speed my lambda function, batch workload, ETL-pipeline, or Kubernetes service takes to redeploy!
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nice product - love how it simplifies running large-scale python jobs across vms, and the fast deploy time is impressive
congrats! we launched today too
upvoted!