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We started with an open-source framework to help data practitioners make their work reproducible. However, after months of building and learning from our community, we realized that many needed help with the setup: getting Python installed, getting dependencies, running experiments locally, etc.
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Judoscale
Save 47% on cloud hosting with autoscaling that just works. Judoscale integrates with Django, FastAPI, Celery, and RQ to make autoscaling easy and reliable. Save big, and say goodbye to request timeouts and backed-up task queues.
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soopervisor
Discontinued ☁️ Export Ploomber pipelines to Kubernetes (Argo), Airflow, AWS Batch, SLURM, and Kubeflow.
NOTE:
The number of mentions on this list indicates mentions on common posts plus user suggested alternatives.
Hence, a higher number means a more popular project.
Related posts
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Show HN: Ploomber Cloud (YC W22) – run notebooks at scale without infrastructure
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Lessons Learned from Running Apache Airflow at Scale
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[D] Productionalizing machine learning pipelines for small teams
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[D] Why aren't workflow management tools used to ensure reproducibility in the ML world?
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Ask HN: What's the right tool for this job?