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Enterprise Layer Intelligence
Categories/DevOps & CI/CD/Coiled
Coiled

Coiled

Founded 2020

Run Python data workloads across thousands of cloud machines without managing Docker or Kubernetes

Pricing model

Free Tier, Paid

You can use Coiled to scale Python workloads to thousands of cloud servers directly from your local development environment. It lets data scientists and engineers request specific hardware instances on AWS, GCP, or Azure using simple Python commands. You do not need to configure Docker containers or manage Kubernetes clusters. Coiled mirrors your local environment on the remote machines, executes distributed tasks using tools like Dask and Prefect, and automatically shuts down all resources when your computations finish to prevent unnecessary cloud spending.

What Coiled does

Provision temporary cloud virtual machines using Python codeSync local package environments to remote cloud serversRun distributed computations across multiple cloud workersSubmit parallel batch jobs using bash or Python scriptsMonitor cloud instance usage and active compute expensesExecute large data transformations across multi-node clustersShut down idle cloud instances automatically after jobs finishSpin up thousands of virtual machines directly from Python functionsAutomatic synchronization of your local Python environment to remote clustersRuns directly inside your own AWS, GCP, or Azure accountAutomatic cluster teardown immediately after computations completeSupport for batch processing and bash scripts with hardware tags in commentsNative compatibility with distributed tools like Dask, Prefect, and XarrayWeb dashboard for tracking active compute instances and cost monitoring

Pricing breakdown

Pricing model: Free tier, Paid

PlanList price
FreeFree
Basic$100 / mo
Professional$500 / mo

Frequently asked

AWSAWSMicrosoft AzureMicrosoft AzurePrefectPrefectPyTorchPyTorch

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Coiled, Python, Dask, cloud computing, distributed computing, AWS, GCP, Azure, data science, batch jobs, Prefect, machine learning, Pandas, Xarray, cloud clusters